WorldWideScience

Sample records for nanochip electronic microarray

  1. SNP typing on the NanoChip electronic microarray

    DEFF Research Database (Denmark)

    Børsting, Claus; Sanchez Sanchez, Juan Jose; Morling, Niels

    2005-01-01

    We describe a single nucleotide polymorphism (SNP) typing protocol developed for the NanoChip electronic microarray. The NanoChip array consists of 100 electrodes covered by a thin hydrogel layer containing streptavidin. An electric currency can be applied to one, several, or all electrodes...

  2. Multiplex PCR, amplicon size and hybridization efficiency on the NanoChip electronic microarray

    DEFF Research Database (Denmark)

    Børsting, Claus; Sanchez, Juan J; Morling, Niels

    2004-01-01

    . Hybridization to individual amplicons in multiplexes was less efficient suggesting that intramolecular and intermolecular interactions may block access to the target sequence on the NanoChip array. We observed a high risk of contamination with amplicons shorter than 60 bp and therefore, we recommend the use...

  3. Plasmonic SERS biosensing nanochips for DNA detection.

    Science.gov (United States)

    Ngo, Hoan T; Wang, Hsin-Neng; Fales, Andrew M; Vo-Dinh, Tuan

    2016-03-01

    The development of rapid, cost-effective DNA detection methods for molecular diagnostics at the point-of-care (POC) has been receiving increasing interest. This article reviews several DNA detection techniques based on plasmonic-active nanochip platforms developed in our laboratory over the last 5 years, including the molecular sentinel-on-chip (MSC), the multiplex MSC, and the inverse molecular sentinel-on-chip (iMS-on-Chip). DNA probes were used as the recognition elements, and surface-enhanced Raman scattering (SERS) was used as the signal detection method. Sensing mechanisms were based on hybridization of target sequences and DNA probes, resulting in a distance change between SERS reporters and the nanochip's plasmonic-active surface. As the field intensity of the surface plasmon decays exponentially as a function of distance, the distance change in turn affects SERS signal intensity, thus indicating the presence and capture of the target sequences. Our techniques were single-step DNA detection techniques. Target sequences were detected by simple delivery of sample solutions onto DNA probe-functionalized nanochips and measuring the SERS signal after appropriate incubation times. Target sequence labeling or washing to remove unreacted components was not required, making the techniques simple, easy-to-use, and cost-effective. The usefulness of the nanochip platform-based techniques for medical diagnostics was illustrated by the detection of host genetic biomarkers for respiratory viral infection and of the dengue virus gene.

  4. Nanochips of Tantalum Oxide Nanodots as artificial-microenvironments for monitoring Ovarian cancer progressiveness

    Science.gov (United States)

    Dhawan, Udesh; Wang, Ssu-Meng; Chu, Ying Hao; Huang, Guewha S.; Lin, Yan Ren; Hung, Yao Ching; Chen, Wen Liang

    2016-08-01

    Nanotopography modulates cell characteristics and cell behavior. Nanotopological cues can be exploited to investigate the in-vivo modulation of cell characteristics by the cellular microenvironment. However, the studies explaining the modulation of tumor cell characteristics and identifying the transition step in cancer progressiveness are scarce. Here, we engineered nanochips comprising of Tantalum oxide nanodot arrays of 10, 50, 100 and 200 nm as artificial microenvironments to study the modulation of cancer cell behavior. Clinical samples of different types of Ovarian cancer at different stages were obtained, primary cultures were established and then seeded on different nanochips. Immunofluorescence (IF) was performed to compare the morphologies and cell characteristics. Indices corresponding to cell characteristics were defined. A statistical comparison of the cell characteristics in response to the nanochips was performed. The cells displayed differential growth parameters. Morphology, Viability, focal adhesions, microfilament bundles and cell area were modulated by the nanochips which can be used as a measure to study the cancer progressiveness. The ease of fabrication of nanochips ensures mass-production. The ability of the nanochips to act as artificial microenvironments and modulate cell behavior may lead to further prospects in the markerless monitoring of the progressiveness and ultimately, improving the prognosis of Ovarian cancer.

  5. Electronic hybridization detection in microarray format and DNA genotyping

    Science.gov (United States)

    Blin, Antoine; Cissé, Ismaïl; Bockelmann, Ulrich

    2014-01-01

    We describe an approach to substituting a fluorescence microarray with a surface made of an arrangement of electrolyte-gated field effect transistors. This was achieved using a dedicated blocking of non-specific interactions and comparing threshold voltage shifts of transistors exhibiting probe molecules of different base sequence. We apply the approach to detection of the 35delG mutation, which is related to non-syndromic deafness and is one of the most frequent mutations in humans. The process involves barcode sequences that are generated by Tas-PCR, a newly developed replication reaction using polymerase blocking. The barcodes are recognized by hybridization to surface attached probes and are directly detected by the semiconductor device. PMID:24569823

  6. Nanochip-induced Epithelial to Mesenchymal Transition: Impact of physical microenvironment on cancer metastasis.

    Science.gov (United States)

    Dhawan, Udesh; Sue, Ming-Wen; Chun Lan, Kuan; Buddhakosai, Waradee; Huang, Pao Hui; Chen, Yi Cheng; Chen, Po-Chun; Chen, Wen-Liang

    2018-03-20

    Epithelial to Mesenchymal transition (EMT) is a highly orchestrated process motivated by the nature of physical, chemical composition of Tumor Microenvironment (TME). The role of physical framework of the tumor microenvironment in guiding cells towards EMT is poorly understood. To investigate this, breast cancer MDA-MB-231 and MCF-7 cells were cultured on nanochips comprising of Tantalum oxide nanodots ranging in diameter from 10 to 200nm, fabricated through electrochemical approach and collectively referred to as artificial microenvironments. The 100 and 200nm nanochips induced cells to adopt an elongated or spindle shaped morphology. The key EMT genes, E-Cadherin, N-Cadherin and Vimentin, displayed the spatial control exhibited by the artificial microenvironments. The E-Cadherin gene expression was attenuated while of N-Cadherin and Vimentin was amplified by 100, 200nm nanochips indicating the induction of EMT. Transcription factors Snail, Twist were identified for modulating modulate EMT genes in the cells on these artificial microenvironments. Localization of EMT proteins observed through Immunostaining indicted the loss of cell-cell junctions on 100, 200nm nanochips, confirming the EMT induction. Thus, by utilizing an in-vitro approach, we demonstrate how the physical framework of TME may possibly trigger or assist in inducing EMT in-vivo. Applications in the fields of drug discovery, biomedical engineering and cancer research are expected.

  7. A multiplex reverse transcription PCR and automated electronic microarray assay for detection and differentiation of seven viruses affecting swine.

    Science.gov (United States)

    Erickson, A; Fisher, M; Furukawa-Stoffer, T; Ambagala, A; Hodko, D; Pasick, J; King, D P; Nfon, C; Ortega Polo, R; Lung, O

    2018-04-01

    Microarray technology can be useful for pathogen detection as it allows simultaneous interrogation of the presence or absence of a large number of genetic signatures. However, most microarray assays are labour-intensive and time-consuming to perform. This study describes the development and initial evaluation of a multiplex reverse transcription (RT)-PCR and novel accompanying automated electronic microarray assay for simultaneous detection and differentiation of seven important viruses that affect swine (foot-and-mouth disease virus [FMDV], swine vesicular disease virus [SVDV], vesicular exanthema of swine virus [VESV], African swine fever virus [ASFV], classical swine fever virus [CSFV], porcine respiratory and reproductive syndrome virus [PRRSV] and porcine circovirus type 2 [PCV2]). The novel electronic microarray assay utilizes a single, user-friendly instrument that integrates and automates capture probe printing, hybridization, washing and reporting on a disposable electronic microarray cartridge with 400 features. This assay accurately detected and identified a total of 68 isolates of the seven targeted virus species including 23 samples of FMDV, representing all seven serotypes, and 10 CSFV strains, representing all three genotypes. The assay successfully detected viruses in clinical samples from the field, experimentally infected animals (as early as 1 day post-infection (dpi) for FMDV and SVDV, 4 dpi for ASFV, 5 dpi for CSFV), as well as in biological material that were spiked with target viruses. The limit of detection was 10 copies/μl for ASFV, PCV2 and PRRSV, 100 copies/μl for SVDV, CSFV, VESV and 1,000 copies/μl for FMDV. The electronic microarray component had reduced analytical sensitivity for several of the target viruses when compared with the multiplex RT-PCR. The integration of capture probe printing allows custom onsite array printing as needed, while electrophoretically driven hybridization generates results faster than conventional

  8. Programmable bio-nanochip-based cytologic testing of oral potentially malignant disorders in Fanconi anemia.

    Science.gov (United States)

    Floriano, P N; Abram, T; Taylor, L; Le, C; Talavera, H; Nguyen, M; Raja, R; Gillenwater, A; McDevitt, J; Vigneswaran, N

    2015-07-01

    Fanconi anemia (FA) is caused by mutations of DNA repair genes. The risk of oral squamous cell carcinoma (OSCC) among FA patients is 800-folds higher than in the general population. Early detection of OSCC, preferably at it precursor stage, is critical in FA patients to improve their survival. In an ongoing clinical trial, we are evaluating the effectiveness of the programmable bio-nanochip (p-BNC)-based oral cytology test in diagnosing oral potentially malignant disorders (OPMD) in non-FA patients. We used this test to compare cytomorphometric and molecular biomarkers in OSCC cell lines derived from FA and non-FA patients to brush biopsy samples of a FA patient with OPMD and normal mucosa of healthy volunteers. Our data showed that expression patterns of molecular biomarkers were not notably different between sporadic and FA-OSCC cell lines. The p-BNC assay revealed significant differences in cytometric parameters and biomarker MCM2 expression between cytobrush samples of the FA patient and cytobrush samples of normal oral mucosa obtained from healthy volunteers. Microscopic examination of the FA patient's OPMD confirmed the presence of dysplasia. Our pilot data suggests that the p-BNC brush biopsy test recognized dysplastic oral epithelial cells in a brush biopsy sample of a FA patient. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  9. Close-To-Practice Assessment Of Meat Freshness With Metal Oxide Sensor Microarray Electronic Nose

    International Nuclear Information System (INIS)

    Musatov, V. Yu.; Sysoev, V. V.; Sommer, M.; Kiselev, I.

    2009-01-01

    In this report we estimate the ability of KAMINA e-nose, based on a metal oxide sensor (MOS) microarray and Linear Discriminant Analysis (LDA) pattern recognition, to evaluate meat freshness. The received results show that, 1) one or two exposures of standard meat samples to the e-nose are enough for the instrument to recognize the fresh meat prepared by the same supplier with 100% probability; 2) the meat samples of two kinds, stored at 4 deg. C and 25 deg. C, are mutually recognized at early stages of decay with the help of the LDA model built independently under the e-nose training to each kind of meat; 3) the 3-4 training cycles of exposure to meat from different suppliers are necessary for the e-nose to build a reliable LDA model accounting for the supplier factor. This study approves that the MOS e-nose is ready to be currently utilised in food industry for evaluation of product freshness. The e-nose performance is characterized by low training cost, a confident recognition power of various product decay conditions and easy adjustment to changing conditions.

  10. Carbohydrate microarrays

    DEFF Research Database (Denmark)

    Park, Sungjin; Gildersleeve, Jeffrey C; Blixt, Klas Ola

    2012-01-01

    In the last decade, carbohydrate microarrays have been core technologies for analyzing carbohydrate-mediated recognition events in a high-throughput fashion. A number of methods have been exploited for immobilizing glycans on the solid surface in a microarray format. This microarray-based technol......In the last decade, carbohydrate microarrays have been core technologies for analyzing carbohydrate-mediated recognition events in a high-throughput fashion. A number of methods have been exploited for immobilizing glycans on the solid surface in a microarray format. This microarray......-based technology has been widely employed for rapid analysis of the glycan binding properties of lectins and antibodies, the quantitative measurements of glycan-protein interactions, detection of cells and pathogens, identification of disease-related anti-glycan antibodies for diagnosis, and fast assessment...

  11. Advancement in stationary phase for peptide separation helps in protein identification: application to atheroma plaque proteomics using nano-chip liquid chromatography and mass spectrometry.

    Science.gov (United States)

    Delporte, Cédric; Noyon, Caroline; Raynal, Pierre; Dufour, Damien; Nève, Jean; Abts, Frederic; Haex, Martin; Zouaoui Boudjeltia, Karim; Van Antwerpen, Pierre

    2015-03-13

    In the last decades, proteomics has largely progressed. Mass spectrometry and liquid chromatography (LC) are generally used in proteomics. These techniques enable proper separation of peptides and good identification and/or quantification of them. Later, nano-scaled liquid chromatography, improvements of mass spectrometry resolution and sensitivity brought huge advancements. Enhancements in chemistry of chromatographic columns also brought interesting results. In the present work, the potency of identification of proteins by different nano-chip columns was studied and compared with classical LC column. The present study was applied to cardiovascular field where proteomics has shown to be highly helpful in research of new biomarkers. Protein extracts from atheroma plaques were used and proteomics data were compared. Results show that fewer spectra were acquired by the mass spectrometer when nano-chip columns were used instead of the classical ones. However, approximately 40% more unique peptides were identified by the recently optimized chip named Polaris-HR-chip-3C18 column, and 20% more proteins were identified. This fact leads to the identification of more low-abundance proteins. Many of them are involved in atheroma plaque development such as apolipoproteins, ceruloplasmin, etc. In conclusion, present data shows that recent developments of nanoLC column chemistry and dimensions enabled the improved detection and identification of low-abundance proteins in atheroma plaques. Several of them are of major interest in the field of cardiovascular disease. Copyright © 2015 Elsevier B.V. All rights reserved.

  12. DNA Microarrays

    Science.gov (United States)

    Nguyen, C.; Gidrol, X.

    Genomics has revolutionised biological and biomedical research. This revolution was predictable on the basis of its two driving forces: the ever increasing availability of genome sequences and the development of new technology able to exploit them. Up until now, technical limitations meant that molecular biology could only analyse one or two parameters per experiment, providing relatively little information compared with the great complexity of the systems under investigation. This gene by gene approach is inadequate to understand biological systems containing several thousand genes. It is essential to have an overall view of the DNA, RNA, and relevant proteins. A simple inventory of the genome is not sufficient to understand the functions of the genes, or indeed the way that cells and organisms work. For this purpose, functional studies based on whole genomes are needed. Among these new large-scale methods of molecular analysis, DNA microarrays provide a way of studying the genome and the transcriptome. The idea of integrating a large amount of data derived from a support with very small area has led biologists to call these chips, borrowing the term from the microelectronics industry. At the beginning of the 1990s, the development of DNA chips on nylon membranes [1, 2], then on glass [3] and silicon [4] supports, made it possible for the first time to carry out simultaneous measurements of the equilibrium concentration of all the messenger RNA (mRNA) or transcribed RNA in a cell. These microarrays offer a wide range of applications, in both fundamental and clinical research, providing a method for genome-wide characterisation of changes occurring within a cell or tissue, as for example in polymorphism studies, detection of mutations, and quantitative assays of gene copies. With regard to the transcriptome, it provides a way of characterising differentially expressed genes, profiling given biological states, and identifying regulatory channels.

  13. Architecture of ZnO nanosheets and nanochips via zinc oxalato-hydrazinate complex

    Science.gov (United States)

    Thorat, Jyoti H.; Chaudhari, Prasad D.; Tamboli, Mohaseen S.; Arbuj, Sudhir S.; Patil, Dilip B.; Kale, Bharat B.

    2014-07-01

    We report the synthesis of ZnO using a zinc oxalato-hydrazinate complex method. The zinc oxalato-hydrazinate complex was synthesized at room temperature using the precursors zinc acetate and oxalic acid. Thermogravimetric studies of zinc oxalato-hydrazinate showed complete phase formation of ZnO at 450 °C. The phase purity and formation of zinc oxalato-hydrazinate prepared in aqueous and organic solvents were confirmed by X-ray diffraction. The zinc oxalato-hydrazinate was calcined and decomposed at 450 °C to obtain phase-pure ZnO. XRD pattern of ZnO showed the existence of hexagonal wurtzite structure. Field emission scanning electron microscopy and transmission electron microscopy (TEM) demonstrate nanosheet-like morphology along with hexagonal nanoparticles. TEM images of aqueous-mediated ZnO clearly show nanosheets having dimensions 1 × 1.7 μ made up of hexagonal nanoparticles of size 10-25 nm. However, ZnO prepared in methanol showed bunch of uniform spherical particles. Further, ethylene glycol-mediated ZnO shows uniform well-aligned spherical particles with chip-like morphology. We have also performed the photocatalytic activity of ZnO samples for methylene blue degradation. The ethylene glycol-mediated ZnO showed extremely good activity ( k = 6.44 × 10-2 min-1) compared to aqueous ( k = 4.42 × 10-2 min-1)- and methanol ( k = 2.92 × 10-2 min-1)-mediated ZnOs. The higher activity in ethylene glycol-mediated ZnO is due to lower size and good crystallinity.

  14. Programmable Bio-nanochip Platform: A Point-of-Care Biosensor System with the Capacity To Learn.

    Science.gov (United States)

    McRae, Michael P; Simmons, Glennon; Wong, Jorge; McDevitt, John T

    2016-07-19

    The combination of point-of-care (POC) medical microdevices and machine learning has the potential transform the practice of medicine. In this area, scalable lab-on-a-chip (LOC) devices have many advantages over standard laboratory methods, including faster analysis, reduced cost, lower power consumption, and higher levels of integration and automation. Despite significant advances in LOC technologies over the years, several remaining obstacles are preventing clinical implementation and market penetration of these novel medical microdevices. Similarly, while machine learning has seen explosive growth in recent years and promises to shift the practice of medicine toward data-intensive and evidence-based decision making, its uptake has been hindered due to the lack of integration between clinical measurements and disease determinations. In this Account, we describe recent developments in the programmable bio-nanochip (p-BNC) system, a biosensor platform with the capacity for learning. The p-BNC is a "platform to digitize biology" in which small quantities of patient sample generate immunofluorescent signal on agarose bead sensors that is optically extracted and converted to antigen concentrations. The platform comprises disposable microfluidic cartridges, a portable analyzer, automated data analysis software, and intuitive mobile health interfaces. The single-use cartridges are fully integrated, self-contained microfluidic devices containing aqueous buffers conveniently embedded for POC use. A novel fluid delivery method was developed to provide accurate and repeatable flow rates via actuation of the cartridge's blister packs. A portable analyzer instrument was designed to integrate fluid delivery, optical detection, image analysis, and user interface, representing a universal system for acquiring, processing, and managing clinical data while overcoming many of the challenges facing the widespread clinical adoption of LOC technologies. We demonstrate the p

  15. DNA Microarray Technology

    Science.gov (United States)

    ... this page. En Español: Tecnología de micromatriz de ADN DNA Microarray Technology What is a DNA microarray? ... this page. En Español: Tecnología de micromatriz de ADN Get Email Updates Privacy Copyright Contact Accessibility Plug- ...

  16. Electron beam agrobionanotechnologies for agriculture and food industry enabled by electron accelerators

    Science.gov (United States)

    Pavlov, Y. S.; Revina, A. A.; Souvorova, O. V.; Voropaeva, N. L.; Chekmar, D. V.; Abkhalimov, E. V.; Zavyalov, M. A.; Filippovich, V. P.

    2017-12-01

    Electron beam (EB) radiation technologies have been employed to increase efficiency of biologically active nanochips developed for agricultural plants seed pre-treatment with purpose of enhancing crop yield and productivity. Iron-containing nanoparticles (NPs), synthesized in reverse micelles following known radiation-chemical technique, have served as a multifunctional biologically active and phytosanitary substance of the chips. Porous chip carriers activation has been performed by EB ionization (doze 20kGy) of the active carbons (AC) prepared from agricultural waste and by-products: Jerusalem artichoke (Helianthus tuberosus) straw, rape (Brassica napus L. ssp. oleifera Metzg) straw, camelina (Camelina sativa (L.) Crantz) straw, wheat (Triticum aestivum) straw. Three methods, UV-VIS spectrophotometry, Electron Paramagnetic Resonance (EPR) spectroscopy, cyclic voltammetry (CV) have been used for process control and characterization of radiation-activated and NPs-modified ACs. The results show a notable effect of ACs activation by electron beam radiation, evidenced by FeNPs-adsorption capacity increase. Studies of the impact of Fe NPs-containing nanochip technology on enhancement of seeds germination rate and seedlings vigour suggest that reported electron beam radiation treatment techniques of the ACs from selected agricultural residues may be advantageous for industrial application.

  17. DNA Microarray Technology; TOPICAL

    International Nuclear Information System (INIS)

    WERNER-WASHBURNE, MARGARET; DAVIDSON, GEORGE S.

    2002-01-01

    Collaboration between Sandia National Laboratories and the University of New Mexico Biology Department resulted in the capability to train students in microarray techniques and the interpretation of data from microarray experiments. These studies provide for a better understanding of the role of stationary phase and the gene regulation involved in exit from stationary phase, which may eventually have important clinical implications. Importantly, this research trained numerous students and is the basis for three new Ph.D. projects

  18. Nanotechnologies in protein microarrays.

    Science.gov (United States)

    Krizkova, Sona; Heger, Zbynek; Zalewska, Marta; Moulick, Amitava; Adam, Vojtech; Kizek, Rene

    2015-01-01

    Protein microarray technology became an important research tool for study and detection of proteins, protein-protein interactions and a number of other applications. The utilization of nanoparticle-based materials and nanotechnology-based techniques for immobilization allows us not only to extend the surface for biomolecule immobilization resulting in enhanced substrate binding properties, decreased background signals and enhanced reporter systems for more sensitive assays. Generally in contemporarily developed microarray systems, multiple nanotechnology-based techniques are combined. In this review, applications of nanoparticles and nanotechnologies in creating protein microarrays, proteins immobilization and detection are summarized. We anticipate that advanced nanotechnologies can be exploited to expand promising fields of proteins identification, monitoring of protein-protein or drug-protein interactions, or proteins structures.

  19. The Stanford Microarray Database

    Science.gov (United States)

    Sherlock, Gavin; Hernandez-Boussard, Tina; Kasarskis, Andrew; Binkley, Gail; Matese, John C.; Dwight, Selina S.; Kaloper, Miroslava; Weng, Shuai; Jin, Heng; Ball, Catherine A.; Eisen, Michael B.; Spellman, Paul T.; Brown, Patrick O.; Botstein, David; Cherry, J. Michael

    2001-01-01

    The Stanford Microarray Database (SMD) stores raw and normalized data from microarray experiments, and provides web interfaces for researchers to retrieve, analyze and visualize their data. The two immediate goals for SMD are to serve as a storage site for microarray data from ongoing research at Stanford University, and to facilitate the public dissemination of that data once published, or released by the researcher. Of paramount importance is the connection of microarray data with the biological data that pertains to the DNA deposited on the microarray (genes, clones etc.). SMD makes use of many public resources to connect expression information to the relevant biology, including SGD [Ball,C.A., Dolinski,K., Dwight,S.S., Harris,M.A., Issel-Tarver,L., Kasarskis,A., Scafe,C.R., Sherlock,G., Binkley,G., Jin,H. et al. (2000) Nucleic Acids Res., 28, 77–80], YPD and WormPD [Costanzo,M.C., Hogan,J.D., Cusick,M.E., Davis,B.P., Fancher,A.M., Hodges,P.E., Kondu,P., Lengieza,C., Lew-Smith,J.E., Lingner,C. et al. (2000) Nucleic Acids Res., 28, 73–76], Unigene [Wheeler,D.L., Chappey,C., Lash,A.E., Leipe,D.D., Madden,T.L., Schuler,G.D., Tatusova,T.A. and Rapp,B.A. (2000) Nucleic Acids Res., 28, 10–14], dbEST [Boguski,M.S., Lowe,T.M. and Tolstoshev,C.M. (1993) Nature Genet., 4, 332–333] and SWISS-PROT [Bairoch,A. and Apweiler,R. (2000) Nucleic Acids Res., 28, 45–48] and can be accessed at http://genome-www.stanford.edu/microarray. PMID:11125075

  20. Robust Microarray Image Processing

    OpenAIRE

    Novikov, Eugene; Barillot, Emmanuel

    2007-01-01

    In this work we have presented a complete solution for robust, high-throughput, two-color microarray image processing comprising procedures for automatic spot localization, spot quantification and spot quality control. The spot localization algorithm is fully automatic and robust with respect to deviations from perfect spot alignment and contamination. As an input, it requires only the common array design parameters: number of blocks and number of spots in the x and y directions of the array....

  1. Microfluidic Methods for Protein Microarrays

    OpenAIRE

    Hartmann, Michael

    2010-01-01

    Protein microarray technology has an enormous potential for in vitro diagnostics (IVD)1. Miniaturized and parallelized immunoassays are powerful tools to measure dozens of parameters from minute amounts of sample, whilst only requiring small amounts of reagent. Protein microarrays have become well-established research tools in basic and applied research and the first diagnostic products are already released on the market. However, in order for protein microarrays to become broadly accepted to...

  2. Compressive Sensing DNA Microarrays

    Directory of Open Access Journals (Sweden)

    Sheikh Mona A

    2009-01-01

    Full Text Available Compressive sensing microarrays (CSMs are DNA-based sensors that operate using group testing and compressive sensing (CS principles. In contrast to conventional DNA microarrays, in which each genetic sensor is designed to respond to a single target, in a CSM, each sensor responds to a set of targets. We study the problem of designing CSMs that simultaneously account for both the constraints from CS theory and the biochemistry of probe-target DNA hybridization. An appropriate cross-hybridization model is proposed for CSMs, and several methods are developed for probe design and CS signal recovery based on the new model. Lab experiments suggest that in order to achieve accurate hybridization profiling, consensus probe sequences are required to have sequence homology of at least 80% with all targets to be detected. Furthermore, out-of-equilibrium datasets are usually as accurate as those obtained from equilibrium conditions. Consequently, one can use CSMs in applications in which only short hybridization times are allowed.

  3. DNA Microarray-Based Diagnostics.

    Science.gov (United States)

    Marzancola, Mahsa Gharibi; Sedighi, Abootaleb; Li, Paul C H

    2016-01-01

    The DNA microarray technology is currently a useful biomedical tool which has been developed for a variety of diagnostic applications. However, the development pathway has not been smooth and the technology has faced some challenges. The reliability of the microarray data and also the clinical utility of the results in the early days were criticized. These criticisms added to the severe competition from other techniques, such as next-generation sequencing (NGS), impacting the growth of microarray-based tests in the molecular diagnostic market.Thanks to the advances in the underlying technologies as well as the tremendous effort offered by the research community and commercial vendors, these challenges have mostly been addressed. Nowadays, the microarray platform has achieved sufficient standardization and method validation as well as efficient probe printing, liquid handling and signal visualization. Integration of various steps of the microarray assay into a harmonized and miniaturized handheld lab-on-a-chip (LOC) device has been a goal for the microarray community. In this respect, notable progress has been achieved in coupling the DNA microarray with the liquid manipulation microsystem as well as the supporting subsystem that will generate the stand-alone LOC device.In this chapter, we discuss the major challenges that microarray technology has faced in its almost two decades of development and also describe the solutions to overcome the challenges. In addition, we review the advancements of the technology, especially the progress toward developing the LOC devices for DNA diagnostic applications.

  4. DNA microarrays : a molecular cloning manual

    National Research Council Canada - National Science Library

    Sambrook, Joseph; Bowtell, David

    2002-01-01

    .... DNA Microarrays provides authoritative, detailed instruction on the design, construction, and applications of microarrays, as well as comprehensive descriptions of the software tools and strategies...

  5. Microarray platform for omics analysis

    Science.gov (United States)

    Mecklenburg, Michael; Xie, Bin

    2001-09-01

    Microarray technology has revolutionized genetic analysis. However, limitations in genome analysis has lead to renewed interest in establishing 'omic' strategies. As we enter the post-genomic era, new microarray technologies are needed to address these new classes of 'omic' targets, such as proteins, as well as lipids and carbohydrates. We have developed a microarray platform that combines self- assembling monolayers with the biotin-streptavidin system to provide a robust, versatile immobilization scheme. A hydrophobic film is patterned on the surface creating an array of tension wells that eliminates evaporation effects thereby reducing the shear stress to which biomolecules are exposed to during immobilization. The streptavidin linker layer makes it possible to adapt and/or develop microarray based assays using virtually any class of biomolecules including: carbohydrates, peptides, antibodies, receptors, as well as them ore traditional DNA based arrays. Our microarray technology is designed to furnish seamless compatibility across the various 'omic' platforms by providing a common blueprint for fabricating and analyzing arrays. The prototype microarray uses a microscope slide footprint patterned with 2 by 96 flat wells. Data on the microarray platform will be presented.

  6. A Fisheye Viewer for microarray-based gene expression data.

    Science.gov (United States)

    Wu, Min; Thao, Cheng; Mu, Xiangming; Munson, Ethan V

    2006-10-13

    Microarray has been widely used to measure the relative amounts of every mRNA transcript from the genome in a single scan. Biologists have been accustomed to reading their experimental data directly from tables. However, microarray data are quite large and are stored in a series of files in a machine-readable format, so direct reading of the full data set is not feasible. The challenge is to design a user interface that allows biologists to usefully view large tables of raw microarray-based gene expression data. This paper presents one such interface--an electronic table (E-table) that uses fisheye distortion technology. The Fisheye Viewer for microarray-based gene expression data has been successfully developed to view MIAME data stored in the MAGE-ML format. The viewer can be downloaded from the project web site http://polaris.imt.uwm.edu:7777/fisheye/. The fisheye viewer was implemented in Java so that it could run on multiple platforms. We implemented the E-table by adapting JTable, a default table implementation in the Java Swing user interface library. Fisheye views use variable magnification to balance magnification for easy viewing and compression for maximizing the amount of data on the screen. This Fisheye Viewer is a lightweight but useful tool for biologists to quickly overview the raw microarray-based gene expression data in an E-table.

  7. A fisheye viewer for microarray-based gene expression data

    Directory of Open Access Journals (Sweden)

    Munson Ethan V

    2006-10-01

    Full Text Available Abstract Background Microarray has been widely used to measure the relative amounts of every mRNA transcript from the genome in a single scan. Biologists have been accustomed to reading their experimental data directly from tables. However, microarray data are quite large and are stored in a series of files in a machine-readable format, so direct reading of the full data set is not feasible. The challenge is to design a user interface that allows biologists to usefully view large tables of raw microarray-based gene expression data. This paper presents one such interface – an electronic table (E-table that uses fisheye distortion technology. Results The Fisheye Viewer for microarray-based gene expression data has been successfully developed to view MIAME data stored in the MAGE-ML format. The viewer can be downloaded from the project web site http://polaris.imt.uwm.edu:7777/fisheye/. The fisheye viewer was implemented in Java so that it could run on multiple platforms. We implemented the E-table by adapting JTable, a default table implementation in the Java Swing user interface library. Fisheye views use variable magnification to balance magnification for easy viewing and compression for maximizing the amount of data on the screen. Conclusion This Fisheye Viewer is a lightweight but useful tool for biologists to quickly overview the raw microarray-based gene expression data in an E-table.

  8. Microarray Developed on Plastic Substrates.

    Science.gov (United States)

    Bañuls, María-José; Morais, Sergi B; Tortajada-Genaro, Luis A; Maquieira, Ángel

    2016-01-01

    There is a huge potential interest to use synthetic polymers as versatile solid supports for analytical microarraying. Chemical modification of polycarbonate (PC) for covalent immobilization of probes, micro-printing of protein or nucleic acid probes, development of indirect immunoassay, and development of hybridization protocols are described and discussed.

  9. Direct calibration of PICKY-designed microarrays

    Directory of Open Access Journals (Sweden)

    Ronald Pamela C

    2009-10-01

    Full Text Available Abstract Background Few microarrays have been quantitatively calibrated to identify optimal hybridization conditions because it is difficult to precisely determine the hybridization characteristics of a microarray using biologically variable cDNA samples. Results Using synthesized samples with known concentrations of specific oligonucleotides, a series of microarray experiments was conducted to evaluate microarrays designed by PICKY, an oligo microarray design software tool, and to test a direct microarray calibration method based on the PICKY-predicted, thermodynamically closest nontarget information. The complete set of microarray experiment results is archived in the GEO database with series accession number GSE14717. Additional data files and Perl programs described in this paper can be obtained from the website http://www.complex.iastate.edu under the PICKY Download area. Conclusion PICKY-designed microarray probes are highly reliable over a wide range of hybridization temperatures and sample concentrations. The microarray calibration method reported here allows researchers to experimentally optimize their hybridization conditions. Because this method is straightforward, uses existing microarrays and relatively inexpensive synthesized samples, it can be used by any lab that uses microarrays designed by PICKY. In addition, other microarrays can be reanalyzed by PICKY to obtain the thermodynamically closest nontarget information for calibration.

  10. Diagnostic and analytical applications of protein microarrays

    DEFF Research Database (Denmark)

    Dufva, Hans Martin; Christensen, C.B.V.

    2005-01-01

    DNA microarrays have changed the field of biomedical sciences over the past 10 years. For several reasons, antibody and other protein microarrays have not developed at the same rate. However, protein and antibody arrays have emerged as a powerful tool to complement DNA microarrays during the post...

  11. The EADGENE Microarray Data Analysis Workshop

    DEFF Research Database (Denmark)

    de Koning, Dirk-Jan; Jaffrézic, Florence; Lund, Mogens Sandø

    2007-01-01

    Microarray analyses have become an important tool in animal genomics. While their use is becoming widespread, there is still a lot of ongoing research regarding the analysis of microarray data. In the context of a European Network of Excellence, 31 researchers representing 14 research groups from...... 10 countries performed and discussed the statistical analyses of real and simulated 2-colour microarray data that were distributed among participants. The real data consisted of 48 microarrays from a disease challenge experiment in dairy cattle, while the simulated data consisted of 10 microarrays...... from a direct comparison of two treatments (dye-balanced). While there was broader agreement with regards to methods of microarray normalisation and significance testing, there were major differences with regards to quality control. The quality control approaches varied from none, through using...

  12. The EADGENE Microarray Data Analysis Workshop

    OpenAIRE

    de Koning, Dirk-Jan; Jaffrézic, Florence; Lund, Mogens Sandø; Watson, Michael; Channing, Caroline; Hulsegge, Ina; Pool, Marco; Buitenhuis, Bart; Hedegaard, Jakob; Hornshøj, Henrik; Jiang, Li; Sørensen, Peter; Marot, Guillemette; Delmas, Céline; Lê Cao, Kim-Anh

    2007-01-01

    Abstract Microarray analyses have become an important tool in animal genomics. While their use is becoming widespread, there is still a lot of ongoing research regarding the analysis of microarray data. In the context of a European Network of Excellence, 31 researchers representing 14 research groups from 10 countries performed and discussed the statistical analyses of real and simulated 2-colour microarray data that were distributed among participants. The real data consisted of 48 microarra...

  13. "Harshlighting" small blemishes on microarrays

    Directory of Open Access Journals (Sweden)

    Wittkowski Knut M

    2005-03-01

    Full Text Available Abstract Background Microscopists are familiar with many blemishes that fluorescence images can have due to dust and debris, glass flaws, uneven distribution of fluids or surface coatings, etc. Microarray scans show similar artefacts, which affect the analysis, particularly when one tries to detect subtle changes. However, most blemishes are hard to find by the unaided eye, particularly in high-density oligonucleotide arrays (HDONAs. Results We present a method that harnesses the statistical power provided by having several HDONAs available, which are obtained under similar conditions except for the experimental factor. This method "harshlights" blemishes and renders them evident. We find empirically that about 25% of our chips are blemished, and we analyze the impact of masking them on screening for differentially expressed genes. Conclusion Experiments attempting to assess subtle expression changes should be carefully screened for blemishes on the chips. The proposed method provides investigators with a novel robust approach to improve the sensitivity of microarray analyses. By utilizing topological information to identify and mask blemishes prior to model based analyses, the method prevents artefacts from confounding the process of background correction, normalization, and summarization.

  14. LNA-modified isothermal oligonucleotide microarray for ...

    Indian Academy of Sciences (India)

    2014-10-20

    Oct 20, 2014 ... To achieve high detection specificity, we fabricated an isothermal microarray ... diagnosis, drug screening, food inspection, agricultural prod- uct monitoring ..... printed with probes B1, B2 and B3 for Bacillus licheniformis (image 1), and microarray analysis of Bacillus licheniformis PCR products amplified ...

  15. Diagnostic and analytical applications of protein microarrays

    DEFF Research Database (Denmark)

    Dufva, Hans Martin; Christensen, C.B.V.

    2005-01-01

    years. A genome-scale protein microarray has been demonstrated for identifying protein-protein interactions as well as for rapid identification of protein binding to a particular drug. Furthermore, protein microarrays have been shown as an efficient tool in cancer profiling, detection of bacteria...

  16. Microarray-integrated optoelectrofluidic immunoassay system.

    Science.gov (United States)

    Han, Dongsik; Park, Je-Kyun

    2016-05-01

    A microarray-based analytical platform has been utilized as a powerful tool in biological assay fields. However, an analyte depletion problem due to the slow mass transport based on molecular diffusion causes low reaction efficiency, resulting in a limitation for practical applications. This paper presents a novel method to improve the efficiency of microarray-based immunoassay via an optically induced electrokinetic phenomenon by integrating an optoelectrofluidic device with a conventional glass slide-based microarray format. A sample droplet was loaded between the microarray slide and the optoelectrofluidic device on which a photoconductive layer was deposited. Under the application of an AC voltage, optically induced AC electroosmotic flows caused by a microarray-patterned light actively enhanced the mass transport of target molecules at the multiple assay spots of the microarray simultaneously, which reduced tedious reaction time from more than 30 min to 10 min. Based on this enhancing effect, a heterogeneous immunoassay with a tiny volume of sample (5 μl) was successfully performed in the microarray-integrated optoelectrofluidic system using immunoglobulin G (IgG) and anti-IgG, resulting in improved efficiency compared to the static environment. Furthermore, the application of multiplex assays was also demonstrated by multiple protein detection.

  17. MARS: Microarray analysis, retrieval, and storage system

    Directory of Open Access Journals (Sweden)

    Scheideler Marcel

    2005-04-01

    Full Text Available Abstract Background Microarray analysis has become a widely used technique for the study of gene-expression patterns on a genomic scale. As more and more laboratories are adopting microarray technology, there is a need for powerful and easy to use microarray databases facilitating array fabrication, labeling, hybridization, and data analysis. The wealth of data generated by this high throughput approach renders adequate database and analysis tools crucial for the pursuit of insights into the transcriptomic behavior of cells. Results MARS (Microarray Analysis and Retrieval System provides a comprehensive MIAME supportive suite for storing, retrieving, and analyzing multi color microarray data. The system comprises a laboratory information management system (LIMS, a quality control management, as well as a sophisticated user management system. MARS is fully integrated into an analytical pipeline of microarray image analysis, normalization, gene expression clustering, and mapping of gene expression data onto biological pathways. The incorporation of ontologies and the use of MAGE-ML enables an export of studies stored in MARS to public repositories and other databases accepting these documents. Conclusion We have developed an integrated system tailored to serve the specific needs of microarray based research projects using a unique fusion of Web based and standalone applications connected to the latest J2EE application server technology. The presented system is freely available for academic and non-profit institutions. More information can be found at http://genome.tugraz.at.

  18. Annotating breast cancer microarray samples using ontologies

    Science.gov (United States)

    Liu, Hongfang; Li, Xin; Yoon, Victoria; Clarke, Robert

    2008-01-01

    As the most common cancer among women, breast cancer results from the accumulation of mutations in essential genes. Recent advance in high-throughput gene expression microarray technology has inspired researchers to use the technology to assist breast cancer diagnosis, prognosis, and treatment prediction. However, the high dimensionality of microarray experiments and public access of data from many experiments have caused inconsistencies which initiated the development of controlled terminologies and ontologies for annotating microarray experiments, such as the standard microarray Gene Expression Data (MGED) ontology (MO). In this paper, we developed BCM-CO, an ontology tailored specifically for indexing clinical annotations of breast cancer microarray samples from the NCI Thesaurus. Our research showed that the coverage of NCI Thesaurus is very limited with respect to i) terms used by researchers to describe breast cancer histology (covering 22 out of 48 histology terms); ii) breast cancer cell lines (covering one out of 12 cell lines); and iii) classes corresponding to the breast cancer grading and staging. By incorporating a wider range of those terms into BCM-CO, we were able to indexed breast cancer microarray samples from GEO using BCM-CO and MGED ontology and developed a prototype system with web interface that allows the retrieval of microarray data based on the ontology annotations. PMID:18999108

  19. Applications of heparin and heparan sulfate microarrays.

    Science.gov (United States)

    Yin, Jian; Seeberger, Peter H

    2010-01-01

    Carbohydrate microarrays have become crucial tools for revealing the biological interactions and functions of glycans, primarily because the microarray format enables the investigation of large numbers of carbohydrates at a time. Heparan sulfate (HS) and heparin are the most structurally complex glycosaminoglycans (GAGs). In this chapter, we describe the preparation of a small library of HS/heparin oligosaccharides, and the fabrication of HS/heparin microarrays that have been used to establish HS/heparin-binding profiles. Fibroblast growth factors (FGFs), natural cytotoxicity receptors (NCRs), and chemokines were screened to illuminate the very important biological functions of these glycans. Copyright (c) 2010 Elsevier Inc. All rights reserved.

  20. Fuzzy clustering analysis of microarray data.

    Science.gov (United States)

    Han, Lixin; Zeng, Xiaoqin; Yan, Hong

    2008-10-01

    Fuzzy clustering is a useful tool for identifying relevant subsets of microarray data. This paper proposes a fuzzy clustering method for microarray data analysis. An advantage of the method is that it used a combination of the fuzzy c-means and the principal component analysis to identify the groups of genes that show similar expression patterns. It allows a gene to belong to more than a gene expression pattern with different membership grades. The method is suitable for the analysis of large amounts of noisy microarray data.

  1. Metric learning for DNA microarray data analysis

    International Nuclear Information System (INIS)

    Takeuchi, Ichiro; Nakagawa, Masao; Seto, Masao

    2009-01-01

    In many microarray studies, gene set selection is an important preliminary step for subsequent main task such as tumor classification, cancer subtype identification, etc. In this paper, we investigate the possibility of using metric learning as an alternative to gene set selection. We develop a simple metric learning algorithm aiming to use it for microarray data analysis. Exploiting a property of the algorithm, we introduce a novel approach for extending the metric learning to be adaptive. We apply the algorithm to previously studied microarray data on malignant lymphoma subtype identification.

  2. Pineal function: impact of microarray analysis

    DEFF Research Database (Denmark)

    Klein, David C; Bailey, Michael J; Carter, David A

    2009-01-01

    Microarray analysis has provided a new understanding of pineal function by identifying genes that are highly expressed in this tissue relative to other tissues and also by identifying over 600 genes that are expressed on a 24-h schedule. This effort has highlighted surprising similarity to the re......Microarray analysis has provided a new understanding of pineal function by identifying genes that are highly expressed in this tissue relative to other tissues and also by identifying over 600 genes that are expressed on a 24-h schedule. This effort has highlighted surprising similarity...... foundation that microarray analysis has provided will broadly support future research on pineal function....

  3. 3D Biomaterial Microarrays for Regenerative Medicine

    DEFF Research Database (Denmark)

    Gaharwar, Akhilesh K.; Arpanaei, Ayyoob; Andresen, Thomas Lars

    2015-01-01

    Three dimensional (3D) biomaterial microarrays hold enormous promise for regenerative medicine because of their ability to accelerate the design and fabrication of biomimetic materials. Such tissue-like biomaterials can provide an appropriate microenvironment for stimulating and controlling stem...

  4. PATMA: parser of archival tissue microarray

    Directory of Open Access Journals (Sweden)

    Lukasz Roszkowiak

    2016-12-01

    Full Text Available Tissue microarrays are commonly used in modern pathology for cancer tissue evaluation, as it is a very potent technique. Tissue microarray slides are often scanned to perform computer-aided histopathological analysis of the tissue cores. For processing the image, splitting the whole virtual slide into images of individual cores is required. The only way to distinguish cores corresponding to specimens in the tissue microarray is through their arrangement. Unfortunately, distinguishing the correct order of cores is not a trivial task as they are not labelled directly on the slide. The main aim of this study was to create a procedure capable of automatically finding and extracting cores from archival images of the tissue microarrays. This software supports the work of scientists who want to perform further image processing on single cores. The proposed method is an efficient and fast procedure, working in fully automatic or semi-automatic mode. A total of 89% of punches were correctly extracted with automatic selection. With an addition of manual correction, it is possible to fully prepare the whole slide image for extraction in 2 min per tissue microarray. The proposed technique requires minimum skill and time to parse big array of cores from tissue microarray whole slide image into individual core images.

  5. Diagnostic and analytical applications of protein microarrays.

    Science.gov (United States)

    Dufva, Martin; Christensen, Claus B V

    2005-01-01

    DNA microarrays have changed the field of biomedical sciences over the past 10 years. For several reasons, antibody and other protein microarrays have not developed at the same rate. However, protein and antibody arrays have emerged as a powerful tool to complement DNA microarrays during the past 5 years. A genome-scale protein microarray has been demonstrated for identifying protein-protein interactions as well as for rapid identification of protein binding to a particular drug. Furthermore, protein microarrays have been shown as an efficient tool in cancer profiling, detection of bacteria and toxins, identification of allergen reactivity and autoantibodies. They have also demonstrated the ability to measure the absolute concentration of small molecules. Besides their capacity for parallel diagnostics, microarrays can be more sensitive than traditional methods such as enzyme-linked immunosorbent assay, mass spectrometry or high-performance liquid chromatography-based assays. However, for protein and antibody arrays to be successfully introduced into diagnostics, the biochemistry of immunomicroarrays must be better characterized and simplified, they must be validated in a clinical setting and be amenable to automation or integrated into easy-to-use systems, such as micrototal analysis systems or point-of-care devices.

  6. Contributions to Statistical Problems Related to Microarray Data

    Science.gov (United States)

    Hong, Feng

    2009-01-01

    Microarray is a high throughput technology to measure the gene expression. Analysis of microarray data brings many interesting and challenging problems. This thesis consists three studies related to microarray data. First, we propose a Bayesian model for microarray data and use Bayes Factors to identify differentially expressed genes. Second, we…

  7. Advancing microarray assembly with acoustic dispensing technology.

    Science.gov (United States)

    Wong, E Y; Diamond, S L

    2009-01-01

    In the assembly of microarrays and microarray-based chemical assays and enzymatic bioassays, most approaches use pins for contact spotting. Acoustic dispensing is a technology capable of nanoliter transfers by using acoustic energy to eject liquid sample from an open source well. Although typically used for well plate transfers, when applied to microarraying, it avoids the drawbacks of undesired physical contact with the sample; difficulty in assembling multicomponent reactions on a chip by readdressing, a rigid mode of printing that lacks patterning capabilities; and time-consuming wash steps. We demonstrated the utility of acoustic dispensing by delivering human cathepsin L in a drop-on-drop fashion into individual 50-nanoliter, prespotted reaction volumes to activate enzyme reactions at targeted positions on a microarray. We generated variable-sized spots ranging from 200 to 750 microm (and higher) and handled the transfer of fluorescent bead suspensions with increasing source well concentrations of 0.1 to 10 x 10(8) beads/mL in a linear fashion. There are no tips that can clog, and liquid dispensing CVs are generally below 5%. This platform expands the toolbox for generating analytical arrays and meets needs associated with spatially addressed assembly of multicomponent microarrays on the nanoliter scale.

  8. Discovering biological progression underlying microarray samples.

    Directory of Open Access Journals (Sweden)

    Peng Qiu

    2011-04-01

    Full Text Available In biological systems that undergo processes such as differentiation, a clear concept of progression exists. We present a novel computational approach, called Sample Progression Discovery (SPD, to discover patterns of biological progression underlying microarray gene expression data. SPD assumes that individual samples of a microarray dataset are related by an unknown biological process (i.e., differentiation, development, cell cycle, disease progression, and that each sample represents one unknown point along the progression of that process. SPD aims to organize the samples in a manner that reveals the underlying progression and to simultaneously identify subsets of genes that are responsible for that progression. We demonstrate the performance of SPD on a variety of microarray datasets that were generated by sampling a biological process at different points along its progression, without providing SPD any information of the underlying process. When applied to a cell cycle time series microarray dataset, SPD was not provided any prior knowledge of samples' time order or of which genes are cell-cycle regulated, yet SPD recovered the correct time order and identified many genes that have been associated with the cell cycle. When applied to B-cell differentiation data, SPD recovered the correct order of stages of normal B-cell differentiation and the linkage between preB-ALL tumor cells with their cell origin preB. When applied to mouse embryonic stem cell differentiation data, SPD uncovered a landscape of ESC differentiation into various lineages and genes that represent both generic and lineage specific processes. When applied to a prostate cancer microarray dataset, SPD identified gene modules that reflect a progression consistent with disease stages. SPD may be best viewed as a novel tool for synthesizing biological hypotheses because it provides a likely biological progression underlying a microarray dataset and, perhaps more importantly, the

  9. Hybridization and Selective Release of DNA Microarrays

    Energy Technology Data Exchange (ETDEWEB)

    Beer, N R; Baker, B; Piggott, T; Maberry, S; Hara, C M; DeOtte, J; Benett, W; Mukerjee, E; Dzenitis, J; Wheeler, E K

    2011-11-29

    DNA microarrays contain sequence specific probes arrayed in distinct spots numbering from 10,000 to over 1,000,000, depending on the platform. This tremendous degree of multiplexing gives microarrays great potential for environmental background sampling, broad-spectrum clinical monitoring, and continuous biological threat detection. In practice, their use in these applications is not common due to limited information content, long processing times, and high cost. The work focused on characterizing the phenomena of microarray hybridization and selective release that will allow these limitations to be addressed. This will revolutionize the ways that microarrays can be used for LLNL's Global Security missions. The goals of this project were two-fold: automated faster hybridizations and selective release of hybridized features. The first study area involves hybridization kinetics and mass-transfer effects. the standard hybridization protocol uses an overnight incubation to achieve the best possible signal for any sample type, as well as for convenience in manual processing. There is potential to significantly shorten this time based on better understanding and control of the rate-limiting processes and knowledge of the progress of the hybridization. In the hybridization work, a custom microarray flow cell was used to manipulate the chemical and thermal environment of the array and autonomously image the changes over time during hybridization. The second study area is selective release. Microarrays easily generate hybridization patterns and signatures, but there is still an unmet need for methodologies enabling rapid and selective analysis of these patterns and signatures. Detailed analysis of individual spots by subsequent sequencing could potentially yield significant information for rapidly mutating and emerging (or deliberately engineered) pathogens. In the selective release work, optical energy deposition with coherent light quickly provides the thermal energy

  10. The use of microarrays in microbial ecology

    Energy Technology Data Exchange (ETDEWEB)

    Andersen, G.L.; He, Z.; DeSantis, T.Z.; Brodie, E.L.; Zhou, J.

    2009-09-15

    Microarrays have proven to be a useful and high-throughput method to provide targeted DNA sequence information for up to many thousands of specific genetic regions in a single test. A microarray consists of multiple DNA oligonucleotide probes that, under high stringency conditions, hybridize only to specific complementary nucleic acid sequences (targets). A fluorescent signal indicates the presence and, in many cases, the abundance of genetic regions of interest. In this chapter we will look at how microarrays are used in microbial ecology, especially with the recent increase in microbial community DNA sequence data. Of particular interest to microbial ecologists, phylogenetic microarrays are used for the analysis of phylotypes in a community and functional gene arrays are used for the analysis of functional genes, and, by inference, phylotypes in environmental samples. A phylogenetic microarray that has been developed by the Andersen laboratory, the PhyloChip, will be discussed as an example of a microarray that targets the known diversity within the 16S rRNA gene to determine microbial community composition. Using multiple, confirmatory probes to increase the confidence of detection and a mismatch probe for every perfect match probe to minimize the effect of cross-hybridization by non-target regions, the PhyloChip is able to simultaneously identify any of thousands of taxa present in an environmental sample. The PhyloChip is shown to reveal greater diversity within a community than rRNA gene sequencing due to the placement of the entire gene product on the microarray compared with the analysis of up to thousands of individual molecules by traditional sequencing methods. A functional gene array that has been developed by the Zhou laboratory, the GeoChip, will be discussed as an example of a microarray that dynamically identifies functional activities of multiple members within a community. The recent version of GeoChip contains more than 24,000 50mer

  11. Microarray Я US: a user-friendly graphical interface to Bioconductor tools that enables accurate microarray data analysis and expedites comprehensive functional analysis of microarray results

    Directory of Open Access Journals (Sweden)

    Dai Yilin

    2012-06-01

    Full Text Available Abstract Background Microarray data analysis presents a significant challenge to researchers who are unable to use the powerful Bioconductor and its numerous tools due to their lack of knowledge of R language. Among the few existing software programs that offer a graphic user interface to Bioconductor packages, none have implemented a comprehensive strategy to address the accuracy and reliability issue of microarray data analysis due to the well known probe design problems associated with many widely used microarray chips. There is also a lack of tools that would expedite the functional analysis of microarray results. Findings We present Microarray Я US, an R-based graphical user interface that implements over a dozen popular Bioconductor packages to offer researchers a streamlined workflow for routine differential microarray expression data analysis without the need to learn R language. In order to enable a more accurate analysis and interpretation of microarray data, we incorporated the latest custom probe re-definition and re-annotation for Affymetrix and Illumina chips. A versatile microarray results output utility tool was also implemented for easy and fast generation of input files for over 20 of the most widely used functional analysis software programs. Conclusion Coupled with a well-designed user interface, Microarray Я US leverages cutting edge Bioconductor packages for researchers with no knowledge in R language. It also enables a more reliable and accurate microarray data analysis and expedites downstream functional analysis of microarray results.

  12. Biological microarray interpretation : The rules of engagement

    NARCIS (Netherlands)

    Breitling, Rainer

    2006-01-01

    Gene expression microarrays are now established as a standard tool in biological and biochemical laboratories. Interpreting the masses of data generated by this technology poses a number of unusual new challenges. Over the past few years a consensus has begun to emerge concerning the most important

  13. Single-species microarrays and comparative transcriptomics.

    Directory of Open Access Journals (Sweden)

    Frédéric J J Chain

    Full Text Available BACKGROUND: Prefabricated expression microarrays are currently available for only a few species but methods have been proposed to extend their application to comparisons between divergent genomes. METHODOLOGY/PRINCIPAL FINDINGS: Here we demonstrate that the hybridization intensity of genomic DNA is a poor basis on which to select unbiased probes on Affymetrix expression arrays for studies of comparative transcriptomics, and that doing so produces spurious results. We used the Affymetrix Xenopus laevis microarray to evaluate expression divergence between X. laevis, X. borealis, and their F1 hybrids. When data are analyzed with probes that interrogate only sequences with confirmed identity in both species, we recover results that differ substantially analyses that use genomic DNA hybridizations to select probes. CONCLUSIONS/SIGNIFICANCE: Our findings have implications for the experimental design of comparative expression studies that use single-species microarrays, and for our understanding of divergent expression in hybrid clawed frogs. These findings also highlight important limitations of single-species microarrays for studies of comparative transcriptomics of polyploid species.

  14. Microarray technology: a promising tool in nutrigenomics.

    Science.gov (United States)

    Masotti, Andrea; Da Sacco, Letizia; Bottazzo, Gian Franco; Alisi, Anna

    2010-08-01

    Microarray technology is a powerful tool for the global evaluation of gene expression profiles in tissues and for understanding many of the factors controlling the regulation of gene transcription. This technique not only provides a considerable amount of information on markers and predictive factors that may potentially characterize a specific clinical picture, but also promises new applications for therapy. One of the most recent applications of microarrays concerns nutritional genomics. Nutritional genomics, known as nutrigenomics, aims to identify and understand mechanisms of molecular interaction between nutrients and/or other dietary bioactive compounds and the genome. Actually, many nutrigenomic studies utilize new approaches such as microarrays, genomics, and bioinformatics to understand how nutrients influence gene expression. The coupling of these new technologies with nutrigenomics promises to lead to improvements in diet and health. In fact, it may provide new information which can be used to ameliorate dietary regimens and to discover novel natural agents for the treatment of important diseases such as diabetes and cancer. This critical review gives an overview of the clinical relevance of a nutritional approach to several important diseases, and proposes the use of microarray for nutrigenomic studies.

  15. Comparing transformation methods for DNA microarray data

    NARCIS (Netherlands)

    Thygesen, Helene H.; Zwinderman, Aeilko H.

    2004-01-01

    Background: When DNA microarray data are used for gene clustering, genotype/phenotype correlation studies, or tissue classification the signal intensities are usually transformed and normalized in several steps in order to improve comparability and signal/noise ratio. These steps may include

  16. Shrinkage covariance matrix approach for microarray data

    Science.gov (United States)

    Karjanto, Suryaefiza; Aripin, Rasimah

    2013-04-01

    Microarray technology was developed for the purpose of monitoring the expression levels of thousands of genes. A microarray data set typically consists of tens of thousands of genes (variables) from just dozens of samples due to various constraints including the high cost of producing microarray chips. As a result, the widely used standard covariance estimator is not appropriate for this purpose. One such technique is the Hotelling's T2 statistic which is a multivariate test statistic for comparing means between two groups. It requires that the number of observations (n) exceeds the number of genes (p) in the set but in microarray studies it is common that n Hotelling's T2 statistic with the shrinkage approach is proposed to estimate the covariance matrix for testing differential gene expression. The performance of this approach is then compared with other commonly used multivariate tests using a widely analysed diabetes data set as illustrations. The results across the methods are consistent, implying that this approach provides an alternative to existing techniques.

  17. Evaluating different methods of microarray data normalization

    Directory of Open Access Journals (Sweden)

    Ferreira Carlos

    2006-10-01

    Full Text Available Abstract Background With the development of DNA hybridization microarray technologies, nowadays it is possible to simultaneously assess the expression levels of thousands to tens of thousands of genes. Quantitative comparison of microarrays uncovers distinct patterns of gene expression, which define different cellular phenotypes or cellular responses to drugs. Due to technical biases, normalization of the intensity levels is a pre-requisite to performing further statistical analyses. Therefore, choosing a suitable approach for normalization can be critical, deserving judicious consideration. Results Here, we considered three commonly used normalization approaches, namely: Loess, Splines and Wavelets, and two non-parametric regression methods, which have yet to be used for normalization, namely, the Kernel smoothing and Support Vector Regression. The results obtained were compared using artificial microarray data and benchmark studies. The results indicate that the Support Vector Regression is the most robust to outliers and that Kernel is the worst normalization technique, while no practical differences were observed between Loess, Splines and Wavelets. Conclusion In face of our results, the Support Vector Regression is favored for microarray normalization due to its superiority when compared to the other methods for its robustness in estimating the normalization curve.

  18. Ecologically relevant stress resistance: from microarrays and ...

    Indian Academy of Sciences (India)

    2004-10-15

    Oct 15, 2004 ... Home; Journals; Journal of Biosciences; Volume 29; Issue 4. Ecologically relevant stress resistance: from microarrays and quantitative trait loci to candidate genes – A research plan and preliminary results using Drosophila as a model organism and climatic and genetic stress as model stresses.

  19. Design of a covalently bonded glycosphingolipid microarray

    DEFF Research Database (Denmark)

    Arigi, Emma; Blixt, Klas Ola; Buschard, Karsten

    2012-01-01

    Glycosphingolipids (GSLs) are well known ubiquitous constituents of all eukaryotic cell membranes, yet their normal biological functions are not fully understood. As with other glycoconjugates and saccharides, solid phase display on microarrays potentially provides an effective platform for in vi......Glycosphingolipids (GSLs) are well known ubiquitous constituents of all eukaryotic cell membranes, yet their normal biological functions are not fully understood. As with other glycoconjugates and saccharides, solid phase display on microarrays potentially provides an effective platform......, the major classes of plant and fungal GSLs. In this work, a prototype "universal" GSL-based covalent microarray has been designed, and preliminary evaluation of its potential utility in assaying protein-GSL binding interactions investigated. An essential step in development involved the enzymatic release......-mercaptoethylamine, was also tested. Underivatized or linker-derivatized lyso-GSL were then immobilized on N-hydroxysuccinimide- or epoxide-activated glass microarray slides and probed with carbohydrate binding proteins of known or partially known specificities (i.e., cholera toxin B-chain; peanut agglutinin...

  20. Gene Expression Analysis Using Agilent DNA Microarrays

    DEFF Research Database (Denmark)

    Stangegaard, Michael

    2009-01-01

    Hybridization of labeled cDNA to microarrays is an intuitively simple and a vastly underestimated process. If it is not performed, optimized, and standardized with the same attention to detail as e.g., RNA amplification, information may be overlooked or even lost. Careful balancing of the amount...

  1. A method of microarray data storage using array data type.

    Science.gov (United States)

    Tsoi, Lam C; Zheng, W Jim

    2007-04-01

    A well-designed microarray database can provide valuable information on gene expression levels. However, designing an efficient microarray database with minimum space usage is not an easy task since designers need to integrate the microarray data with the information of genes, probe annotation, and the descriptions of each microarray experiment. Developing better methods to store microarray data can greatly improve the efficiency and usefulness of such data. A new schema is proposed to store microarray data by using array data type in an object-relational database management system--PostgreSQL. The implemented database can store all the microarray data from the same chip in an array data structure. The variable-length array data type in PostgreSQL can store microarray data from same chip. The implementation of our schema can help to increase the data retrieval and space efficiency.

  2. Microarray Analysis of Space-flown Murine Thymus Tissue

    Data.gov (United States)

    National Aeronautics and Space Administration — Microarray Analysis of Space-flown Murine Thymus Tissue Reveals Changes in Gene Expression Regulating Stress and Glucocorticoid Receptors. We used microarrays to...

  3. Temperature Gradient Effect on Gas Discrimination Power of a Metal-Oxide Thin-Film Sensor Microarray

    Directory of Open Access Journals (Sweden)

    Joachim Goschnick

    2004-05-01

    Full Text Available Abstract: The paper presents results concerning the effect of spatial inhomogeneous operating temperature on the gas discrimination power of a gas-sensor microarray, with the latter based on a thin SnO2 film employed in the KAMINA electronic nose. Three different temperature distributions over the substrate are discussed: a nearly homogeneous one and two temperature gradients, equal to approx. 3.3 oC/mm and 6.7 oC/mm, applied across the sensor elements (segments of the array. The gas discrimination power of the microarray is judged by using the Mahalanobis distance in the LDA (Linear Discrimination Analysis coordinate system between the data clusters obtained by the response of the microarray to four target vapors: ethanol, acetone, propanol and ammonia. It is shown that the application of a temperature gradient increases the gas discrimination power of the microarray by up to 35 %.

  4. Identifying Fishes through DNA Barcodes and Microarrays.

    Science.gov (United States)

    Kochzius, Marc; Seidel, Christian; Antoniou, Aglaia; Botla, Sandeep Kumar; Campo, Daniel; Cariani, Alessia; Vazquez, Eva Garcia; Hauschild, Janet; Hervet, Caroline; Hjörleifsdottir, Sigridur; Hreggvidsson, Gudmundur; Kappel, Kristina; Landi, Monica; Magoulas, Antonios; Marteinsson, Viggo; Nölte, Manfred; Planes, Serge; Tinti, Fausto; Turan, Cemal; Venugopal, Moleyur N; Weber, Hannes; Blohm, Dietmar

    2010-09-07

    International fish trade reached an import value of 62.8 billion Euro in 2006, of which 44.6% are covered by the European Union. Species identification is a key problem throughout the life cycle of fishes: from eggs and larvae to adults in fisheries research and control, as well as processed fish products in consumer protection. This study aims to evaluate the applicability of the three mitochondrial genes 16S rRNA (16S), cytochrome b (cyt b), and cytochrome oxidase subunit I (COI) for the identification of 50 European marine fish species by combining techniques of "DNA barcoding" and microarrays. In a DNA barcoding approach, neighbour Joining (NJ) phylogenetic trees of 369 16S, 212 cyt b, and 447 COI sequences indicated that cyt b and COI are suitable for unambiguous identification, whereas 16S failed to discriminate closely related flatfish and gurnard species. In course of probe design for DNA microarray development, each of the markers yielded a high number of potentially species-specific probes in silico, although many of them were rejected based on microarray hybridisation experiments. None of the markers provided probes to discriminate the sibling flatfish and gurnard species. However, since 16S-probes were less negatively influenced by the "position of label" effect and showed the lowest rejection rate and the highest mean signal intensity, 16S is more suitable for DNA microarray probe design than cty b and COI. The large portion of rejected COI-probes after hybridisation experiments (>90%) renders the DNA barcoding marker as rather unsuitable for this high-throughput technology. Based on these data, a DNA microarray containing 64 functional oligonucleotide probes for the identification of 30 out of the 50 fish species investigated was developed. It represents the next step towards an automated and easy-to-handle method to identify fish, ichthyoplankton, and fish products.

  5. Identifying Fishes through DNA Barcodes and Microarrays.

    Directory of Open Access Journals (Sweden)

    Marc Kochzius

    Full Text Available BACKGROUND: International fish trade reached an import value of 62.8 billion Euro in 2006, of which 44.6% are covered by the European Union. Species identification is a key problem throughout the life cycle of fishes: from eggs and larvae to adults in fisheries research and control, as well as processed fish products in consumer protection. METHODOLOGY/PRINCIPAL FINDINGS: This study aims to evaluate the applicability of the three mitochondrial genes 16S rRNA (16S, cytochrome b (cyt b, and cytochrome oxidase subunit I (COI for the identification of 50 European marine fish species by combining techniques of "DNA barcoding" and microarrays. In a DNA barcoding approach, neighbour Joining (NJ phylogenetic trees of 369 16S, 212 cyt b, and 447 COI sequences indicated that cyt b and COI are suitable for unambiguous identification, whereas 16S failed to discriminate closely related flatfish and gurnard species. In course of probe design for DNA microarray development, each of the markers yielded a high number of potentially species-specific probes in silico, although many of them were rejected based on microarray hybridisation experiments. None of the markers provided probes to discriminate the sibling flatfish and gurnard species. However, since 16S-probes were less negatively influenced by the "position of label" effect and showed the lowest rejection rate and the highest mean signal intensity, 16S is more suitable for DNA microarray probe design than cty b and COI. The large portion of rejected COI-probes after hybridisation experiments (>90% renders the DNA barcoding marker as rather unsuitable for this high-throughput technology. CONCLUSIONS/SIGNIFICANCE: Based on these data, a DNA microarray containing 64 functional oligonucleotide probes for the identification of 30 out of the 50 fish species investigated was developed. It represents the next step towards an automated and easy-to-handle method to identify fish, ichthyoplankton, and fish products.

  6. Facilitating functional annotation of chicken microarray data

    Directory of Open Access Journals (Sweden)

    Gresham Cathy R

    2009-10-01

    Full Text Available Abstract Background Modeling results from chicken microarray studies is challenging for researchers due to little functional annotation associated with these arrays. The Affymetrix GenChip chicken genome array, one of the biggest arrays that serve as a key research tool for the study of chicken functional genomics, is among the few arrays that link gene products to Gene Ontology (GO. However the GO annotation data presented by Affymetrix is incomplete, for example, they do not show references linked to manually annotated functions. In addition, there is no tool that facilitates microarray researchers to directly retrieve functional annotations for their datasets from the annotated arrays. This costs researchers amount of time in searching multiple GO databases for functional information. Results We have improved the breadth of functional annotations of the gene products associated with probesets on the Affymetrix chicken genome array by 45% and the quality of annotation by 14%. We have also identified the most significant diseases and disorders, different types of genes, and known drug targets represented on Affymetrix chicken genome array. To facilitate functional annotation of other arrays and microarray experimental datasets we developed an Array GO Mapper (AGOM tool to help researchers to quickly retrieve corresponding functional information for their dataset. Conclusion Results from this study will directly facilitate annotation of other chicken arrays and microarray experimental datasets. Researchers will be able to quickly model their microarray dataset into more reliable biological functional information by using AGOM tool. The disease, disorders, gene types and drug targets revealed in the study will allow researchers to learn more about how genes function in complex biological systems and may lead to new drug discovery and development of therapies. The GO annotation data generated will be available for public use via AgBase website and

  7. Comparison of gene expression microarray data with count-based RNA measurements informs microarray interpretation.

    Science.gov (United States)

    Richard, Arianne C; Lyons, Paul A; Peters, James E; Biasci, Daniele; Flint, Shaun M; Lee, James C; McKinney, Eoin F; Siegel, Richard M; Smith, Kenneth G C

    2014-08-04

    Although numerous investigations have compared gene expression microarray platforms, preprocessing methods and batch correction algorithms using constructed spike-in or dilution datasets, there remains a paucity of studies examining the properties of microarray data using diverse biological samples. Most microarray experiments seek to identify subtle differences between samples with variable background noise, a scenario poorly represented by constructed datasets. Thus, microarray users lack important information regarding the complexities introduced in real-world experimental settings. The recent development of a multiplexed, digital technology for nucleic acid measurement enables counting of individual RNA molecules without amplification and, for the first time, permits such a study. Using a set of human leukocyte subset RNA samples, we compared previously acquired microarray expression values with RNA molecule counts determined by the nCounter Analysis System (NanoString Technologies) in selected genes. We found that gene measurements across samples correlated well between the two platforms, particularly for high-variance genes, while genes deemed unexpressed by the nCounter generally had both low expression and low variance on the microarray. Confirming previous findings from spike-in and dilution datasets, this "gold-standard" comparison demonstrated signal compression that varied dramatically by expression level and, to a lesser extent, by dataset. Most importantly, examination of three different cell types revealed that noise levels differed across tissues. Microarray measurements generally correlate with relative RNA molecule counts within optimal ranges but suffer from expression-dependent accuracy bias and precision that varies across datasets. We urge microarray users to consider expression-level effects in signal interpretation and to evaluate noise properties in each dataset independently.

  8. Viral diagnosis in Indian livestock using customized microarray chips.

    Science.gov (United States)

    Yadav, Brijesh S; Pokhriyal, Mayank; Ratta, Barkha; Kumar, Ajay; Saxena, Meeta; Sharma, Bhaskar

    2015-01-01

    Viral diagnosis in Indian livestock using customized microarray chips is gaining momentum in recent years. Hence, it is possible to design customized microarray chip for viruses infecting livestock in India. Customized microarray chips identified Bovine herpes virus-1 (BHV-1), Canine Adeno Virus-1 (CAV-1), and Canine Parvo Virus-2 (CPV-2) in clinical samples. Microarray identified specific probes were further confirmed using RT-PCR in all clinical and known samples. Therefore, the application of microarray chips during viral disease outbreaks in Indian livestock is possible where conventional methods are unsuitable. It should be noted that customized application requires a detailed cost efficiency calculation.

  9. Facilitating RNA structure prediction with microarrays.

    Science.gov (United States)

    Kierzek, Elzbieta; Kierzek, Ryszard; Turner, Douglas H; Catrina, Irina E

    2006-01-17

    Determining RNA secondary structure is important for understanding structure-function relationships and identifying potential drug targets. This paper reports the use of microarrays with heptamer 2'-O-methyl oligoribonucleotides to probe the secondary structure of an RNA and thereby improve the prediction of that secondary structure. When experimental constraints from hybridization results are added to a free-energy minimization algorithm, the prediction of the secondary structure of Escherichia coli 5S rRNA improves from 27 to 92% of the known canonical base pairs. Optimization of buffer conditions for hybridization and application of 2'-O-methyl-2-thiouridine to enhance binding and improve discrimination between AU and GU pairs are also described. The results suggest that probing RNA with oligonucleotide microarrays can facilitate determination of secondary structure.

  10. Respiratory Tularemia:Francisella Tularensisand Microarray Probe Designing.

    Science.gov (United States)

    Ranjbar, Reza; Behzadi, Payam; Mammina, Caterina

    2016-01-01

    Francisella tularensis ( F. tularensis ) is the etiological microorganism for tularemia. There are different forms of tularemia such as respiratory tularemia. Respiratory tularemia is the most severe form of tularemia with a high rate of mortality; if not treated. Therefore, traditional microbiological tools and Polymerase Chain Reaction (PCR) are not useful for a rapid, reliable, accurate, sensitive and specific diagnosis. But, DNA microarray technology does. DNA microarray technology needs to appropriate microarray probe designing. The main goal of this original article was to design suitable long oligo microarray probes for detection and identification of F. tularensis . For performing this research, the complete genomes of F. tularensis subsp. tularensis FSC198, F. tularensis subsp. holarctica LVS, F. tularensis subsp. mediasiatica , F. tularensis subsp. novicida ( F. novicida U112), and F. philomiragia subsp. philomiragia ATCC 25017 were studied via NCBI BLAST tool, GView and PanSeq Servers and finally the microarray probes were produced and processed via AlleleID 7.7 software and Oligoanalyzer tool, respectively. In this in silico investigation, a number of long oligo microarray probes were designed for detecting and identifying F. tularensis . Among these probes, 15 probes were recognized as the best candidates for microarray chip designing. Calibrated microarray probes reduce the biasis of DNA microarray technology as an advanced, rapid, accurate and cost-effective molecular diagnostic tool with high specificity and sensitivity. Professional microarray probe designing provides us with much more facility and flexibility regarding preparation of a microarray diagnostic chip.

  11. PMD: A Resource for Archiving and Analyzing Protein Microarray data.

    Science.gov (United States)

    Xu, Zhaowei; Huang, Likun; Zhang, Hainan; Li, Yang; Guo, Shujuan; Wang, Nan; Wang, Shi-Hua; Chen, Ziqing; Wang, Jingfang; Tao, Sheng-Ce

    2016-01-27

    Protein microarray is a powerful technology for both basic research and clinical study. However, because there is no database specifically tailored for protein microarray, the majority of the valuable original protein microarray data is still not publically accessible. To address this issue, we constructed Protein Microarray Database (PMD), which is specifically designed for archiving and analyzing protein microarray data. In PMD, users can easily browse and search the entire database by experimental name, protein microarray type, and sample information. Additionally, PMD integrates several data analysis tools and provides an automated data analysis pipeline for users. With just one click, users can obtain a comprehensive analysis report for their protein microarray data. The report includes preliminary data analysis, such as data normalization, candidate identification, and an in-depth bioinformatics analysis of the candidates, which include functional annotation, pathway analysis, and protein-protein interaction network analysis. PMD is now freely available at www.proteinmicroarray.cn.

  12. Weighted analysis of general microarray experiments

    Directory of Open Access Journals (Sweden)

    Kristiansson Erik

    2007-10-01

    Full Text Available Abstract Background In DNA microarray experiments, measurements from different biological samples are often assumed to be independent and to have identical variance. For many datasets these assumptions have been shown to be invalid and typically lead to too optimistic p-values. A method called WAME has been proposed where a variance is estimated for each sample and a covariance is estimated for each pair of samples. The current version of WAME is, however, limited to experiments with paired design, e.g. two-channel microarrays. Results The WAME procedure is extended to general microarray experiments, making it capable of handling both one- and two-channel datasets. Two public one-channel datasets are analysed and WAME detects both unequal variances and correlations. WAME is compared to other common methods: fold-change ranking, ordinary linear model with t-tests, LIMMA and weighted LIMMA. The p-value distributions are shown to differ greatly between the examined methods. In a resampling-based simulation study, the p-values generated by WAME are found to be substantially more correct than the alternatives when a relatively small proportion of the genes is regulated. WAME is also shown to have higher power than the other methods. WAME is available as an R-package. Conclusion The WAME procedure is generalized and the limitation to paired-design microarray datasets is removed. The examined other methods produce invalid p-values in many cases, while WAME is shown to produce essentially valid p-values when a relatively small proportion of genes is regulated. WAME is also shown to have higher power than the examined alternative methods.

  13. Tissue Microarray Analysis Applied to Bone Diagenesis

    OpenAIRE

    Barrios Mello, Rafael; Regis Silva, Maria Regina; Seixas Alves, Maria Teresa; Evison, Martin; Guimarães, Marco Aurélio; Francisco, Rafaella Arrabaça; Dias Astolphi, Rafael; Miazato Iwamura, Edna Sadayo

    2017-01-01

    Taphonomic processes affecting bone post mortem are important in forensic, archaeological and palaeontological investigations. In this study, the application of tissue microarray (TMA) analysis to a sample of femoral bone specimens from 20 exhumed individuals of known period of burial and age at death is described. TMA allows multiplexing of subsamples, permitting standardized comparative analysis of adjacent sections in 3-D and of representative cross-sections of a large number of specimens....

  14. Analyzing microarray data using quantitative association rules.

    Science.gov (United States)

    Georgii, Elisabeth; Richter, Lothar; Rückert, Ulrich; Kramer, Stefan

    2005-09-01

    We tackle the problem of finding regularities in microarray data. Various data mining tools, such as clustering, classification, Bayesian networks and association rules, have been applied so far to gain insight into gene-expression data. Association rule mining techniques used so far work on discretizations of the data and cannot account for cumulative effects. In this paper, we investigate the use of quantitative association rules that can operate directly on numeric data and represent cumulative effects of variables. Technically speaking, this type of quantitative association rules based on half-spaces can find non-axis-parallel regularities. We performed a variety of experiments testing the utility of quantitative association rules for microarray data. First of all, the results should be statistically significant and robust against fluctuations in the data. Next, the approach should be scalable in the number of variables, which is important for such high-dimensional data. Finally, the rules should make sense biologically and be sufficiently different from rules found in regular association rule mining working with discretizations. In all of these dimensions, the proposed approach performed satisfactorily. Therefore, quantitative association rules based on half-spaces should be considered as a tool for the analysis of microarray gene-expression data. The code is available from the authors on request.

  15. Metadata management and semantics in microarray repositories.

    Science.gov (United States)

    Kocabaş, F; Can, T; Baykal, N

    2011-12-01

    The number of microarray and other high-throughput experiments on primary repositories keeps increasing as do the size and complexity of the results in response to biomedical investigations. Initiatives have been started on standardization of content, object model, exchange format and ontology. However, there are backlogs and inability to exchange data between microarray repositories, which indicate that there is a great need for a standard format and data management. We have introduced a metadata framework that includes a metadata card and semantic nets that make experimental results visible, understandable and usable. These are encoded in syntax encoding schemes and represented in RDF (Resource Description Frame-word), can be integrated with other metadata cards and semantic nets, and can be exchanged, shared and queried. We demonstrated the performance and potential benefits through a case study on a selected microarray repository. We concluded that the backlogs can be reduced and that exchange of information and asking of knowledge discovery questions can become possible with the use of this metadata framework.

  16. A New Distribution Family for Microarray Data

    Directory of Open Access Journals (Sweden)

    Diana Mabel Kelmansky

    2017-02-01

    Full Text Available The traditional approach with microarray data has been to apply transformations that approximately normalize them, with the drawback of losing the original scale. The alternative stand point taken here is to search for models that fit the data, characterized by the presence of negative values, preserving their scale; one advantage of this strategy is that it facilitates a direct interpretation of the results. A new family of distributions named gpower-normal indexed by p∈R is introduced and it is proven that these variables become normal or truncated normal when a suitable gpower transformation is applied. Expressions are given for moments and quantiles, in terms of the truncated normal density. This new family can be used to model asymmetric data that include non-positive values, as required for microarray analysis. Moreover, it has been proven that the gpower-normal family is a special case of pseudo-dispersion models, inheriting all the good properties of these models, such as asymptotic normality for small variances. A combined maximum likelihood method is proposed to estimate the model parameters, and it is applied to microarray and contamination data. Rcodes are available from the authors upon request.

  17. MicroarrayDesigner: an online search tool and repository for near-optimal microarray experimental designs.

    Science.gov (United States)

    Sacan, Ahmet; Ferhatosmanoglu, Nilgun; Ferhatosmanoglu, Hakan

    2009-09-22

    Dual-channel microarray experiments are commonly employed for inference of differential gene expressions across varying organisms and experimental conditions. The design of dual-channel microarray experiments that can help minimize the errors in the resulting inferences has recently received increasing attention. However, a general and scalable search tool and a corresponding database of optimal designs were still missing. An efficient and scalable search method for finding near-optimal dual-channel microarray designs, based on a greedy hill-climbing optimization strategy, has been developed. It is empirically shown that this method can successfully and efficiently find near-optimal designs. Additionally, an improved interwoven loop design construction algorithm has been developed to provide an easily computable general class of near-optimal designs. Finally, in order to make the best results readily available to biologists, a continuously evolving catalog of near-optimal designs is provided. A new search algorithm and database for near-optimal microarray designs have been developed. The search tool and the database are accessible via the World Wide Web at http://db.cse.ohio-state.edu/MicroarrayDesigner. Source code and binary distributions are available for academic use upon request.

  18. MicroarrayDesigner: an online search tool and repository for near-optimal microarray experimental designs

    Directory of Open Access Journals (Sweden)

    Ferhatosmanoglu Nilgun

    2009-09-01

    Full Text Available Abstract Background Dual-channel microarray experiments are commonly employed for inference of differential gene expressions across varying organisms and experimental conditions. The design of dual-channel microarray experiments that can help minimize the errors in the resulting inferences has recently received increasing attention. However, a general and scalable search tool and a corresponding database of optimal designs were still missing. Description An efficient and scalable search method for finding near-optimal dual-channel microarray designs, based on a greedy hill-climbing optimization strategy, has been developed. It is empirically shown that this method can successfully and efficiently find near-optimal designs. Additionally, an improved interwoven loop design construction algorithm has been developed to provide an easily computable general class of near-optimal designs. Finally, in order to make the best results readily available to biologists, a continuously evolving catalog of near-optimal designs is provided. Conclusion A new search algorithm and database for near-optimal microarray designs have been developed. The search tool and the database are accessible via the World Wide Web at http://db.cse.ohio-state.edu/MicroarrayDesigner. Source code and binary distributions are available for academic use upon request.

  19. DNA Microarray for Detection of Gastrointestinal Viruses

    Science.gov (United States)

    Martínez, Miguel A.; Soto-del Río, María de los Dolores; Gutiérrez, Rosa María; Chiu, Charles Y.; Greninger, Alexander L.; Contreras, Juan Francisco; López, Susana; Arias, Carlos F.

    2014-01-01

    Gastroenteritis is a clinical illness of humans and other animals that is characterized by vomiting and diarrhea and caused by a variety of pathogens, including viruses. An increasing number of viral species have been associated with gastroenteritis or have been found in stool samples as new molecular tools have been developed. In this work, a DNA microarray capable in theory of parallel detection of more than 100 viral species was developed and tested. Initial validation was done with 10 different virus species, and an additional 5 species were validated using clinical samples. Detection limits of 1 × 103 virus particles of Human adenovirus C (HAdV), Human astrovirus (HAstV), and group A Rotavirus (RV-A) were established. Furthermore, when exogenous RNA was added, the limit for RV-A detection decreased by one log. In a small group of clinical samples from children with gastroenteritis (n = 76), the microarray detected at least one viral species in 92% of the samples. Single infection was identified in 63 samples (83%), and coinfection with more than one virus was identified in 7 samples (9%). The most abundant virus species were RV-A (58%), followed by Anellovirus (15.8%), HAstV (6.6%), HAdV (5.3%), Norwalk virus (6.6%), Human enterovirus (HEV) (9.2%), Human parechovirus (1.3%), Sapporo virus (1.3%), and Human bocavirus (1.3%). To further test the specificity and sensitivity of the microarray, the results were verified by reverse transcription-PCR (RT-PCR) detection of 5 gastrointestinal viruses. The RT-PCR assay detected a virus in 59 samples (78%). The microarray showed good performance for detection of RV-A, HAstV, and calicivirus, while the sensitivity for HAdV and HEV was low. Furthermore, some discrepancies in detection of mixed infections were observed and were addressed by reverse transcription-quantitative PCR (RT-qPCR) of the viruses involved. It was observed that differences in the amount of genetic material favored the detection of the most abundant

  20. Classification across gene expression microarray studies

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    Kuner Ruprecht

    2009-12-01

    Full Text Available Abstract Background The increasing number of gene expression microarray studies represents an important resource in biomedical research. As a result, gene expression based diagnosis has entered clinical practice for patient stratification in breast cancer. However, the integration and combined analysis of microarray studies remains still a challenge. We assessed the potential benefit of data integration on the classification accuracy and systematically evaluated the generalization performance of selected methods on four breast cancer studies comprising almost 1000 independent samples. To this end, we introduced an evaluation framework which aims to establish good statistical practice and a graphical way to monitor differences. The classification goal was to correctly predict estrogen receptor status (negative/positive and histological grade (low/high of each tumor sample in an independent study which was not used for the training. For the classification we chose support vector machines (SVM, predictive analysis of microarrays (PAM, random forest (RF and k-top scoring pairs (kTSP. Guided by considerations relevant for classification across studies we developed a generalization of kTSP which we evaluated in addition. Our derived version (DV aims to improve the robustness of the intrinsic invariance of kTSP with respect to technologies and preprocessing. Results For each individual study the generalization error was benchmarked via complete cross-validation and was found to be similar for all classification methods. The misclassification rates were substantially higher in classification across studies, when each single study was used as an independent test set while all remaining studies were combined for the training of the classifier. However, with increasing number of independent microarray studies used in the training, the overall classification performance improved. DV performed better than the average and showed slightly less variance. In

  1. Evaluation of toxicity of the mycotoxin citrinin using yeast ORF DNA microarray and Oligo DNA microarray

    Directory of Open Access Journals (Sweden)

    Nobumasa Hitoshi

    2007-04-01

    Full Text Available Abstract Background Mycotoxins are fungal secondary metabolites commonly present in feed and food, and are widely regarded as hazardous contaminants. Citrinin, one of the very well known mycotoxins that was first isolated from Penicillium citrinum, is produced by more than 10 kinds of fungi, and is possibly spread all over the world. However, the information on the action mechanism of the toxin is limited. Thus, we investigated the citrinin-induced genomic response for evaluating its toxicity. Results Citrinin inhibited growth of yeast cells at a concentration higher than 100 ppm. We monitored the citrinin-induced mRNA expression profiles in yeast using the ORF DNA microarray and Oligo DNA microarray, and the expression profiles were compared with those of the other stress-inducing agents. Results obtained from both microarray experiments clustered together, but were different from those of the mycotoxin patulin. The oxidative stress response genes – AADs, FLR1, OYE3, GRE2, and MET17 – were significantly induced. In the functional category, expression of genes involved in "metabolism", "cell rescue, defense and virulence", and "energy" were significantly activated. In the category of "metabolism", genes involved in the glutathione synthesis pathway were activated, and in the category of "cell rescue, defense and virulence", the ABC transporter genes were induced. To alleviate the induced stress, these cells might pump out the citrinin after modification with glutathione. While, the citrinin treatment did not induce the genes involved in the DNA repair. Conclusion Results from both microarray studies suggest that citrinin treatment induced oxidative stress in yeast cells. The genotoxicity was less severe than the patulin, suggesting that citrinin is less toxic than patulin. The reproducibility of the expression profiles was much better with the Oligo DNA microarray. However, the Oligo DNA microarray did not completely overcome cross

  2. Normalization for triple-target microarray experiments

    Directory of Open Access Journals (Sweden)

    Magniette Frederic

    2008-04-01

    Full Text Available Abstract Background Most microarray studies are made using labelling with one or two dyes which allows the hybridization of one or two samples on the same slide. In such experiments, the most frequently used dyes are Cy3 and Cy5. Recent improvements in the technology (dye-labelling, scanner and, image analysis allow hybridization up to four samples simultaneously. The two additional dyes are Alexa488 and Alexa494. The triple-target or four-target technology is very promising, since it allows more flexibility in the design of experiments, an increase in the statistical power when comparing gene expressions induced by different conditions and a scaled down number of slides. However, there have been few methods proposed for statistical analysis of such data. Moreover the lowess correction of the global dye effect is available for only two-color experiments, and even if its application can be derived, it does not allow simultaneous correction of the raw data. Results We propose a two-step normalization procedure for triple-target experiments. First the dye bleeding is evaluated and corrected if necessary. Then the signal in each channel is normalized using a generalized lowess procedure to correct a global dye bias. The normalization procedure is validated using triple-self experiments and by comparing the results of triple-target and two-color experiments. Although the focus is on triple-target microarrays, the proposed method can be used to normalize p differently labelled targets co-hybridized on a same array, for any value of p greater than 2. Conclusion The proposed normalization procedure is effective: the technical biases are reduced, the number of false positives is under control in the analysis of differentially expressed genes, and the triple-target experiments are more powerful than the corresponding two-color experiments. There is room for improving the microarray experiments by simultaneously hybridizing more than two samples.

  3. Antigen microarrays: descriptive chemistry or functional immunomics?

    Science.gov (United States)

    Prechl, József; Papp, Krisztián; Erdei, Anna

    2010-04-01

    Advances in protein microarray technology allow the generation of high content, reliable information about complex, multilevel protein interaction networks. Yet antigen arrays are used mostly only as devices for parallel immune assays describing multitudes of individual binding events. We propose here that the huge amount of immunological information hidden in the plasma of an individual could be better revealed by combining the characterization of antibody binding to target epitopes with improved estimation of effector functions triggered by these binding events. Furthermore, we could generate functional immune profiles characterizing general immune responsiveness of the individual by designing arrays incorporating epitope collections from diverse subsets of antibody targets. Copyright 2010 Elsevier Ltd. All rights reserved.

  4. Tumor classification ranking from microarray data

    Directory of Open Access Journals (Sweden)

    Kijsanayothin Phongphun

    2008-09-01

    Full Text Available Abstract Background Gene expression profiles based on microarray data are recognized as potential diagnostic indices of cancer. Molecular tumor classifications resulted from these data and learning algorithms have advanced our understanding of genetic changes associated with cancer etiology and development. However, classifications are not always perfect and in such cases the classification rankings (likelihoods of correct class predictions can be useful for directing further research (e.g., by deriving inferences about predictive indicators or prioritizing future experiments. Classification ranking is a challenging problem, particularly for microarray data, where there is a huge number of possible regulated genes with no known rating function. This study investigates the possibility of making tumor classification more informative by using a method for classification ranking that requires no additional ranking analysis and maintains relatively good classification accuracy. Results Microarray data of 11 different types and subtypes of cancer were analyzed using MDR (Multi-Dimensional Ranker, a recently developed boosting-based ranking algorithm. The number of predictor genes in all of the resulting classification models was at most nine, a huge reduction from the more than 12 thousands genes in the majority of the expression samples. Compared to several other learning algorithms, MDR gives the greatest AUC (area under the ROC curve for the classifications of prostate cancer, acute lymphoblastic leukemia (ALL and four ALL subtypes: BCR-ABL, E2A-PBX1, MALL and TALL. SVM (Support Vector Machine gives the highest AUC for the classifications of lung, lymphoma, and breast cancers, and two ALL subtypes: Hyperdiploid > 50 and TEL-AML1. MDR gives highly competitive results, producing the highest average AUC, 91.01%, and an average overall accuracy of 90.01% for cancer expression analysis. Conclusion Using the classification rankings from MDR is a simple

  5. Linking probe thermodynamics to microarray quantification

    International Nuclear Information System (INIS)

    Li, Shuzhao; Pozhitkov, Alexander; Brouwer, Marius

    2010-01-01

    Understanding the difference in probe properties holds the key to absolute quantification of DNA microarrays. So far, Langmuir-like models have failed to link sequence-specific properties to hybridization signals in the presence of a complex hybridization background. Data from washing experiments indicate that the post-hybridization washing has no major effect on the specifically bound targets, which give the final signals. Thus, the amount of specific targets bound to probes is likely determined before washing, by the competition against nonspecific binding. Our competitive hybridization model is a viable alternative to Langmuir-like models. (comment)

  6. Microarray technology applied to the complex disorder of preeclampsia.

    Science.gov (United States)

    Founds, Sandra A; Dorman, Janice S; Conley, Yvette P

    2008-01-01

    Preeclampsia is a life-threatening perinatal complication with unknown etiology. Microarray technology has characterized global gene expression in complex disorders such as preeclampsia. Nursing research and future practice may incorporate findings from microarray analyses to identify susceptibility to and prevent disease, to diagnose early, and to design and monitor personalized therapies. This overview of microarray technology, with emphasis on how it can inform genomics of preeclampsia, may provide concepts to improve future maternal-neonatal nursing care.

  7. Chemiluminescence microarrays in analytical chemistry: a critical review.

    Science.gov (United States)

    Seidel, Michael; Niessner, Reinhard

    2014-09-01

    Multi-analyte immunoassays on microarrays and on multiplex DNA microarrays have been described for quantitative analysis of small organic molecules (e.g., antibiotics, drugs of abuse, small molecule toxins), proteins (e.g., antibodies or protein toxins), and microorganisms, viruses, and eukaryotic cells. In analytical chemistry, multi-analyte detection by use of analytical microarrays has become an innovative research topic because of the possibility of generating several sets of quantitative data for different analyte classes in a short time. Chemiluminescence (CL) microarrays are powerful tools for rapid multiplex analysis of complex matrices. A wide range of applications for CL microarrays is described in the literature dealing with analytical microarrays. The motivation for this review is to summarize the current state of CL-based analytical microarrays. Combining analysis of different compound classes on CL microarrays reduces analysis time, cost of reagents, and use of laboratory space. Applications are discussed, with examples from food safety, water safety, environmental monitoring, diagnostics, forensics, toxicology, and biosecurity. The potential and limitations of research on multiplex analysis by use of CL microarrays are discussed in this review.

  8. Microarray time course experiments: finding profiles.

    Science.gov (United States)

    Irigoien, Itziar; Vives, Sergi; Arenas, Concepción

    2011-01-01

    Time course studies with microarray techniques and experimental replicates are very useful in biomedical research. We present, in replicate experiments, an alternative approach to select and cluster genes according to a new measure for association between genes. First, the procedure normalizes and standardizes the expression profile of each gene, and then, identifies scaling parameters that will further minimize the distance between replicates of the same gene. Then, the procedure filters out genes with a flat profile, detects differences between replicates, and separates genes without significant differences from the rest. For this last group of genes, we define a mean profile for each gene and use it to compute the distance between two genes. Next, a hierarchical clustering procedure is proposed, a statistic is computed for each cluster to determine its compactness, and the total number of classes is determined. For the rest of the genes, those with significant differences between replicates, the procedure detects where the differences between replicates lie, and assigns each gene to the best fitting previously identified profile or defines a new profile. We illustrate this new procedure using simulated data and a representative data set arising from a microarray experiment with replication, and report interesting results.

  9. Enzyme microarrays assembled by acoustic dispensing technology.

    Science.gov (United States)

    Wong, E Y; Diamond, S L

    2008-10-01

    Miniaturizing bioassays to the nanoliter scale for high-throughput screening reduces the consumption of reagents that are expensive or difficult to handle. Through the use of acoustic dispensing technology, nanodroplets containing 10 microM ATP (3 microCi/microL (32)P) and reaction buffer in 10% glycerol were positionally dispensed to the surface of glass slides to form 40-nL compartments (100 droplets/slide) for Pim1 (proviral integration site 1) kinase reactions. The reactions were activated by dispensing 4 nL of various levels of a pyridocarbazolo-cyclopentadienyl ruthenium complex Pim1 inhibitor, followed by dispensing 4 nL of a Pim1 kinase and peptide substrate solution to achieve final concentrations of 150 nM enzyme and 10 microM substrate. The microarray was incubated at 30 degrees C (97% R(h)) for 1.5 h. The spots were then blotted to phosphocellulose membranes to capture phosphorylated substrate. With phosphor imaging to quantify the washed membranes, the assay showed that, for doses of inhibitor from 0.75 to 3 microM, Pim1 was increasingly inhibited. Signal-to-background ratios were as high as 165, and average coefficients of variation for the assay were approximately 20%. Coefficients of variation for dispensing typical working buffers were under 5%. Thus, microarrays assembled by acoustic dispensing are promising as cost-effective tools that can be used in protein assay development.

  10. Laser direct writing of biomolecule microarrays

    Science.gov (United States)

    Serra, P.; Fernández-Pradas, J. M.; Berthet, F. X.; Colina, M.; Elvira, J.; Morenza, J. L.

    Protein-based biosensors are highly efficient tools for protein detection and identification. The production of these devices requires the manipulation of tiny amounts of protein solutions in conditions preserving their biological properties. In this work, laser induced forward transfer (LIFT) was used for spotting an array of a purified bacterial antigen in order to check the viability of this technique for the production of protein microarrays. A pulsed Nd:YAG laser beam (355 nm wavelength, 10 ns pulse duration) was used to transfer droplets of a solution containing the Treponema pallidum 17 kDa protein antigen on a glass slide. Optical microscopy showed that a regular array of micrometric droplets could be precisely and uniformly spotted onto a solid substrate. Subsequently, it was proved that LIFT deposition of a T. pallidum 17 kDa antigen onto nylon-coated glass slides preserves its antigenic reactivity and diagnostic properties. These results support that LIFT is suitable for the production of protein microarrays and pave the way for future diagnostics applications.

  11. Additive risk survival model with microarray data

    Directory of Open Access Journals (Sweden)

    Huang Jian

    2007-06-01

    Full Text Available Abstract Background Microarray techniques survey gene expressions on a global scale. Extensive biomedical studies have been designed to discover subsets of genes that are associated with survival risks for diseases such as lymphoma and construct predictive models using those selected genes. In this article, we investigate simultaneous estimation and gene selection with right censored survival data and high dimensional gene expression measurements. Results We model the survival time using the additive risk model, which provides a useful alternative to the proportional hazards model and is adopted when the absolute effects, instead of the relative effects, of multiple predictors on the hazard function are of interest. A Lasso (least absolute shrinkage and selection operator type estimate is proposed for simultaneous estimation and gene selection. Tuning parameter is selected using the V-fold cross validation. We propose Leave-One-Out cross validation based methods for evaluating the relative stability of individual genes and overall prediction significance. Conclusion We analyze the MCL and DLBCL data using the proposed approach. A small number of probes represented on the microarrays are identified, most of which have sound biological implications in lymphoma development. The selected probes are relatively stable and the proposed approach has overall satisfactory prediction power.

  12. Near-optimal designs for dual channel microarray studies

    NARCIS (Netherlands)

    Wit, Ernst; Nobile, Agostino; Khanin, Raya

    2005-01-01

    Much biological and medical research employs microarray studies to monitor gene expression levels across a wide range of organisms and under many experimental conditions. Dual channel microarrays are a common platform and allow two samples to be measured simultaneously. A frequently used design uses

  13. Design of an Enterobacteriaceae Pan-genome Microarray Chip

    DEFF Research Database (Denmark)

    Lukjancenko, Oksana; Ussery, David

    2010-01-01

    -density microarray chip has been designed, using 116 Enterobacteriaceae genome sequences, taking into account the enteric pan-genome. Probes for the microarray were checked in silico and performance of the chip, based on experimental strains from four different genera, demonstrate a relatively high ability...

  14. Microarray-based Detection of Antibiotic Resisteance Genes in Salmonella

    NARCIS (Netherlands)

    Hoek, van A.H.A.M.; Aarts, H.J.M.

    2008-01-01

    In the presented study, 143 Salmonella isolates belonging to 26 different serovars were screened for the presence of antibiotic resistance genes by microarray analysis. The microarray contained a total of 223 oligonucleotides representing genes encoding for resistance to the following antibiotic

  15. A Critical Perspective On Microarray Breast Cancer Gene Expression Profiling

    NARCIS (Netherlands)

    Sontrop, H.M.J.

    2015-01-01

    Microarrays offer biologists an exciting tool that allows the simultaneous assessment of gene expression levels for thousands of genes at once. At the time of their inception, microarrays were hailed as the new dawn in cancer biology and oncology practice with the hope that within a decade diseases

  16. Shared probe design and existing microarray reanalysis using PICKY

    Directory of Open Access Journals (Sweden)

    Chou Hui-Hsien

    2010-04-01

    Full Text Available Abstract Background Large genomes contain families of highly similar genes that cannot be individually identified by microarray probes. This limitation is due to thermodynamic restrictions and cannot be resolved by any computational method. Since gene annotations are updated more frequently than microarrays, another common issue facing microarray users is that existing microarrays must be routinely reanalyzed to determine probes that are still useful with respect to the updated annotations. Results PICKY 2.0 can design shared probes for sets of genes that cannot be individually identified using unique probes. PICKY 2.0 uses novel algorithms to track sharable regions among genes and to strictly distinguish them from other highly similar but nontarget regions during thermodynamic comparisons. Therefore, PICKY does not sacrifice the quality of shared probes when choosing them. The latest PICKY 2.1 includes the new capability to reanalyze existing microarray probes against updated gene sets to determine probes that are still valid to use. In addition, more precise nonlinear salt effect estimates and other improvements are added, making PICKY 2.1 more versatile to microarray users. Conclusions Shared probes allow expressed gene family members to be detected; this capability is generally more desirable than not knowing anything about these genes. Shared probes also enable the design of cross-genome microarrays, which facilitate multiple species identification in environmental samples. The new nonlinear salt effect calculation significantly increases the precision of probes at a lower buffer salt concentration, and the probe reanalysis function improves existing microarray result interpretations.

  17. Microarray Assisted Gene Discovery in Ulcerative Colitis

    DEFF Research Database (Denmark)

    Brusgaard, Klaus

    ), and microarray based expression studies. In IBD the increased production of chemo attractants from the inflamed microenvironment results in recruitment of activated CD4+ T lymphocytes which results in tissue damage. Where Th1 cell-derived cytokines has been reported to be essential mediators in CD with high (IFN...... on the activation of different downstream pathways. Thus it seems that different genetic backgrounds can lead to similar clinical manifestations, and as well determines the susceptibility to IBD. In the previous micro array based expression studies on UC the main target has been to point to new candidate genes...... based on analysis of the main up or down regulated genes in the dataset. The majority of the studies are hampered by a relatively shortcoming of the numbers of genes analysed on the particular array. In this study the main target has been to point to clusters of genes involved in biochemical pathways...

  18. Uses of Dendrimers for DNA Microarrays

    Directory of Open Access Journals (Sweden)

    Jean-Pierre Majoral

    2006-08-01

    Full Text Available Biosensors such as DNA microarrays and microchips are gaining an increasingimportance in medicinal, forensic, and environmental analyses. Such devices are based onthe detection of supramolecular interactions called hybridizations that occur betweencomplementary oligonucleotides, one linked to a solid surface (the probe, and the other oneto be analyzed (the target. This paper focuses on the improvements that hyperbranched andperfectly defined nanomolecules called dendrimers can provide to this methodology. Twomain uses of dendrimers for such purpose have been described up to now; either thedendrimer is used as linker between the solid surface and the probe oligonucleotide, or thedendrimer is used as a multilabeled entity linked to the target oligonucleotide. In the firstcase the dendrimer generally induces a higher loading of probes and an easier hybridization,due to moving away the solid phase. In the second case the high number of localized labels(generally fluorescent induces an increased sensitivity, allowing the detection of smallquantities of biological entities.

  19. Bystander effect: Biological endpoints and microarray analysis

    Energy Technology Data Exchange (ETDEWEB)

    Chaudhry, M. Ahmad [Department of Medical Laboratory and Radiation Sciences, College of Nursing and Health Sciences, University of Vermont, 302 Rowell Building, Burlington, VT 05405 (United States) and DNA Microarray Facility, University of Vermont, Burlington, VT 05405 (United States)]. E-mail: mchaudhr@uvm.edu

    2006-05-11

    In cell populations exposed to ionizing radiation, the biological effects occur in a much larger proportion of cells than are estimated to be traversed by radiation. It has been suggested that irradiated cells are capable of providing signals to the neighboring unirradiated cells resulting in damage to these cells. This phenomenon is termed the bystander effect. The bystander effect induces persistent, long-term, transmissible changes that result in delayed death and neoplastic transformation. Because the bystander effect is relevant to carcinogenesis, it could have significant implications for risk estimation for radiation exposure. The nature of the bystander effect signal and how it impacts the unirradiated cells remains to be elucidated. Examination of the changes in gene expression could provide clues to understanding the bystander effect and could define the signaling pathways involved in sustaining damage to these cells. The microarray technology serves as a tool to gain insight into the molecular pathways leading to bystander effect. Using medium from irradiated normal human diploid lung fibroblasts as a model system we examined gene expression alterations in bystander cells. The microarray data revealed that the radiation-induced gene expression profile in irradiated cells is different from unirradiated bystander cells suggesting that the pathways leading to biological effects in the bystander cells are different from the directly irradiated cells. The genes known to be responsive to ionizing radiation were observed in irradiated cells. Several genes were upregulated in cells receiving media from irradiated cells. Surprisingly no genes were found to be downregulated in these cells. A number of genes belonging to extracellular signaling, growth factors and several receptors were identified in bystander cells. Interestingly 15 genes involved in the cell communication processes were found to be upregulated. The induction of receptors and the cell

  20. Bystander effect: Biological endpoints and microarray analysis

    International Nuclear Information System (INIS)

    Chaudhry, M. Ahmad

    2006-01-01

    In cell populations exposed to ionizing radiation, the biological effects occur in a much larger proportion of cells than are estimated to be traversed by radiation. It has been suggested that irradiated cells are capable of providing signals to the neighboring unirradiated cells resulting in damage to these cells. This phenomenon is termed the bystander effect. The bystander effect induces persistent, long-term, transmissible changes that result in delayed death and neoplastic transformation. Because the bystander effect is relevant to carcinogenesis, it could have significant implications for risk estimation for radiation exposure. The nature of the bystander effect signal and how it impacts the unirradiated cells remains to be elucidated. Examination of the changes in gene expression could provide clues to understanding the bystander effect and could define the signaling pathways involved in sustaining damage to these cells. The microarray technology serves as a tool to gain insight into the molecular pathways leading to bystander effect. Using medium from irradiated normal human diploid lung fibroblasts as a model system we examined gene expression alterations in bystander cells. The microarray data revealed that the radiation-induced gene expression profile in irradiated cells is different from unirradiated bystander cells suggesting that the pathways leading to biological effects in the bystander cells are different from the directly irradiated cells. The genes known to be responsive to ionizing radiation were observed in irradiated cells. Several genes were upregulated in cells receiving media from irradiated cells. Surprisingly no genes were found to be downregulated in these cells. A number of genes belonging to extracellular signaling, growth factors and several receptors were identified in bystander cells. Interestingly 15 genes involved in the cell communication processes were found to be upregulated. The induction of receptors and the cell

  1. Lipid Microarray Biosensor for Biotoxin Detection.

    Energy Technology Data Exchange (ETDEWEB)

    Singh, Anup K.; Throckmorton, Daniel J.; Moran-Mirabal, Jose C.; Edel, Joshua B.; Meyer, Grant D.; Craighead, Harold G.

    2006-05-01

    We present the use of micron-sized lipid domains, patterned onto planar substrates and within microfluidic channels, to assay the binding of bacterial toxins via total internal reflection fluorescence microscopy (TIRFM). The lipid domains were patterned using a polymer lift-off technique and consisted of ganglioside-populated DSPC:cholesterol supported lipid bilayers (SLBs). Lipid patterns were formed on the substrates by vesicle fusion followed by polymer lift-off, which revealed micron-sized SLBs containing either ganglioside GT1b or GM1. The ganglioside-populated SLB arrays were then exposed to either Cholera toxin subunit B (CTB) or Tetanus toxin fragment C (TTC). Binding was assayed on planar substrates by TIRFM down to 1 nM concentration for CTB and 100 nM for TTC. Apparent binding constants extracted from three different models applied to the binding curves suggest that binding of a protein to a lipid-based receptor is strongly affected by the lipid composition of the SLB and by the substrate on which the bilayer is formed. Patterning of SLBs inside microfluidic channels also allowed the preparation of lipid domains with different compositions on a single device. Arrays within microfluidic channels were used to achieve segregation and selective binding from a binary mixture of the toxin fragments in one device. The binding and segregation within the microfluidic channels was assayed with epifluorescence as proof of concept. We propose that the method used for patterning the lipid microarrays on planar substrates and within microfluidic channels can be easily adapted to proteins or nucleic acids and can be used for biosensor applications and cell stimulation assays under different flow conditions. KEYWORDS. Microarray, ganglioside, polymer lift-off, cholera toxin, tetanus toxin, TIRFM, binding constant.4

  2. A cell spot microarray method for production of high density siRNA transfection microarrays

    Directory of Open Access Journals (Sweden)

    Mpindi John-Patrick

    2011-03-01

    Full Text Available Abstract Background High-throughput RNAi screening is widely applied in biological research, but remains expensive, infrastructure-intensive and conversion of many assays to HTS applications in microplate format is not feasible. Results Here, we describe the optimization of a miniaturized cell spot microarray (CSMA method, which facilitates utilization of the transfection microarray technique for disparate RNAi analyses. To promote rapid adaptation of the method, the concept has been tested with a panel of 92 adherent cell types, including primary human cells. We demonstrate the method in the systematic screening of 492 GPCR coding genes for impact on growth and survival of cultured human prostate cancer cells. Conclusions The CSMA method facilitates reproducible preparation of highly parallel cell microarrays for large-scale gene knockdown analyses. This will be critical towards expanding the cell based functional genetic screens to include more RNAi constructs, allow combinatorial RNAi analyses, multi-parametric phenotypic readouts or comparative analysis of many different cell types.

  3. Development of a Digital Microarray with Interferometric Reflectance Imaging

    Science.gov (United States)

    Sevenler, Derin

    This dissertation describes a new type of molecular assay for nucleic acids and proteins. We call this technique a digital microarray since it is conceptually similar to conventional fluorescence microarrays, yet it performs enumerative ('digital') counting of the number captured molecules. Digital microarrays are approximately 10,000-fold more sensitive than fluorescence microarrays, yet maintain all of the strengths of the platform including low cost and high multiplexing (i.e., many different tests on the same sample simultaneously). Digital microarrays use gold nanorods to label the captured target molecules. Each gold nanorod on the array is individually detected based on its light scattering, with an interferometric microscopy technique called SP-IRIS. Our optimized high-throughput version of SP-IRIS is able to scan a typical array of 500 spots in less than 10 minutes. Digital DNA microarrays may have utility in applications where sequencing is prohibitively expensive or slow. As an example, we describe a digital microarray assay for gene expression markers of bacterial drug resistance.

  4. Protein microarray-mediated detection of antienterovirus antibodies in serum.

    Science.gov (United States)

    Zhang, Aiying; Xiu, Bingshui; Zhang, Heqiu; Li, Ning

    2016-04-01

    To utilize prokaryotic gene expression and protein microarray to develop and evaluate a sensitive, accurate protein microarray assay for detecting antienterovirus antibodies in serum samples from patients with hand, foot and mouth disease (HFMD). Enterovirus 71 (EV71) and coxsackievirus A16 (CA16), two common causative agents for HFMD, were used for assay development. Serum was collected from patients with HFMD and healthy controls. EV71 and CA16 VP1 and VP3 genes were expressed in transfected Escherichia coli; the resultant VP1 and 3 proteins were used in a microarray assay for human serum EV71 and CA16 immunoglobulin (Ig) M and IgG. To validate the microarray assay, serum samples were tested for EV71 IgM using enzyme-linked immunosorbent assay (ELISA). Out of 50 patients with HFMD, EV71 IgM and CA16 IgM was detected in 80% and 44% of serum samples, respectively, using protein microarray, and EV71 IgM was detected in 78% of samples using ELISA. Protein microarray and ELISA showed 100% specificity for EV71-IgM detection. The protein microarray assay developed in the present study shows potential as a sensitive technique for detecting EV71 IgM in serum samples from patients with HFMD. © The Author(s) 2016.

  5. A Human Lectin Microarray for Sperm Surface Glycosylation Analysis *

    Science.gov (United States)

    Sun, Yangyang; Cheng, Li; Gu, Yihua; Xin, Aijie; Wu, Bin; Zhou, Shumin; Guo, Shujuan; Liu, Yin; Diao, Hua; Shi, Huijuan; Wang, Guangyu; Tao, Sheng-ce

    2016-01-01

    Glycosylation is one of the most abundant and functionally important protein post-translational modifications. As such, technology for efficient glycosylation analysis is in high demand. Lectin microarrays are a powerful tool for such investigations and have been successfully applied for a variety of glycobiological studies. However, most of the current lectin microarrays are primarily constructed from plant lectins, which are not well suited for studies of human glycosylation because of the extreme complexity of human glycans. Herein, we constructed a human lectin microarray with 60 human lectin and lectin-like proteins. All of the lectins and lectin-like proteins were purified from yeast, and most showed binding to human glycans. To demonstrate the applicability of the human lectin microarray, human sperm were probed on the microarray and strong bindings were observed for several lectins, including galectin-1, 7, 8, GalNAc-T6, and ERGIC-53 (LMAN1). These bindings were validated by flow cytometry and fluorescence immunostaining. Further, mass spectrometry analysis showed that galectin-1 binds several membrane-associated proteins including heat shock protein 90. Finally, functional assays showed that binding of galectin-8 could significantly enhance the acrosome reaction within human sperms. To our knowledge, this is the first construction of a human lectin microarray, and we anticipate it will find wide use for a range of human or mammalian studies, alone or in combination with plant lectin microarrays. PMID:27364157

  6. Highly Sensitive Flexible Pressure Sensor Based on Silver Nanowires-Embedded Polydimethylsiloxane Electrode with Microarray Structure.

    Science.gov (United States)

    Shuai, Xingtian; Zhu, Pengli; Zeng, Wenjin; Hu, Yougen; Liang, Xianwen; Zhang, Yu; Sun, Rong; Wong, Ching-Ping

    2017-08-09

    Flexible pressure sensors have attracted increasing research interest because of their potential applications for wearable sensing devices. Herein, a highly sensitive flexible pressure sensor is exhibited based on the elastomeric electrodes and a microarray architecture. Polydimethylsiloxane (PDMS) substrate, coated with silver nanowires (AgNWs), is used as the top electrode, while polyvinylidene fluoride (PVDF) as the dielectric layer. Several transfer processes are applied on seeking facile strategy for the preparation of the bottom electrode via embedding AgNWs into the PDMS film of microarray structure. The flexible pressure sensor integrates the top electrode, dielectric layer, and microarray electrode in a sandwich structure. It is demonstrated that such sensors possess the superiorities of high sensitivity (2.94 kPa -1 ), low detection limit (flexible pressure sensor exhibits good performance even in a noncontact way, such as detecting voice vibrations and air flow. Due to its superior performance, this designed flexible pressure sensor demonstrates promising potential in the application of electronic skins, as well as wearable healthcare monitors.

  7. Towards standardization of microarray-based genotyping of Salmonella

    DEFF Research Database (Denmark)

    Löfström, Charlotta; Grønlund, Hugo Ahlm; Riber, Leise

    2010-01-01

    Genotyping is becoming an increasingly important tool to improve risk assessments of Salmonella. DNA microarray technology is a promising diagnostic tool that can provide high resolution genomic profile of many genes simultaneously. However, standardization of DNA microarray analysis is needed...... of Salmonella at two different laboratories. The low-density array contained 281 of 57-60-mer oligonucleotide probes for detecting a wide range of specific genomic markers associated with antibiotic resistance, cell envelope structures, mobile genetic elements and pathogenicity. Several test parameters...... for a decentralized and simple-to-implement DNA microarray as part of a pan-European source-attribution model for risk assessment of Salmonella....

  8. AFM 4.0: a toolbox for DNA microarray analysis.

    Science.gov (United States)

    Breitkreutz, B J; Jorgensen, P; Breitkreutz, A; Tyers, M

    2001-01-01

    We have developed a series of programs, collectively packaged as Array File Maker 4.0 (AFM), that manipulate and manage DNA microarray data. AFM 4.0 is simple to use, applicable to any organism or microarray, and operates within the familiar confines of Microsoft Excel. Given a database of expression ratios, AFM 4.0 generates input files for clustering, helps prepare colored figures and Venn diagrams, and can uncover aneuploidy in yeast microarray data. AFM 4.0 should be especially useful to laboratories that do not have access to specialized commercial or in-house software.

  9. Tissue Microarray Analysis Applied to Bone Diagenesis.

    Science.gov (United States)

    Mello, Rafael Barrios; Silva, Maria Regina Regis; Alves, Maria Teresa Seixas; Evison, Martin Paul; Guimarães, Marco Aurelio; Francisco, Rafaella Arrabaca; Astolphi, Rafael Dias; Iwamura, Edna Sadayo Miazato

    2017-01-04

    Taphonomic processes affecting bone post mortem are important in forensic, archaeological and palaeontological investigations. In this study, the application of tissue microarray (TMA) analysis to a sample of femoral bone specimens from 20 exhumed individuals of known period of burial and age at death is described. TMA allows multiplexing of subsamples, permitting standardized comparative analysis of adjacent sections in 3-D and of representative cross-sections of a large number of specimens. Standard hematoxylin and eosin, periodic acid-Schiff and silver methenamine, and picrosirius red staining, and CD31 and CD34 immunohistochemistry were applied to TMA sections. Osteocyte and osteocyte lacuna counts, percent bone matrix loss, and fungal spheroid element counts could be measured and collagen fibre bundles observed in all specimens. Decalcification with 7% nitric acid proceeded more rapidly than with 0.5 M EDTA and may offer better preservation of histological and cellular structure. No endothelial cells could be detected using CD31 and CD34 immunohistochemistry. Correlation between osteocytes per lacuna and age at death may reflect reported age-related responses to microdamage. Methodological limitations and caveats, and results of the TMA analysis of post mortem diagenesis in bone are discussed, and implications for DNA survival and recovery considered.

  10. Tissue microarray profiling in human heart failure.

    Science.gov (United States)

    Lal, Sean; Nguyen, Lisa; Tezone, Rhenan; Ponten, Fredrik; Odeberg, Jacob; Li, Amy; Dos Remedios, Cristobal

    2016-09-01

    Tissue MicroArrays (TMAs) are a versatile tool for high-throughput protein screening, allowing qualitative analysis of a large number of samples on a single slide. We have developed a customizable TMA system that uniquely utilizes cryopreserved human cardiac samples from both heart failure and donor patients to produce formalin-fixed paraffin-embedded sections. Confirmatory upstream or downstream molecular studies can then be performed on the same (biobanked) cryopreserved tissue. In a pilot study, we applied our TMAs to screen for the expression of four-and-a-half LIM-domain 2 (FHL2), a member of the four-and-a-half LIM family. This protein has been implicated in the pathogenesis of heart failure in a variety of animal models. While FHL2 is abundant in the heart, not much is known about its expression in human heart failure. For this purpose, we generated an affinity-purified rabbit polyclonal anti-human FHL2 antibody. Our TMAs allowed high-throughput profiling of FHL2 protein using qualitative and semiquantitative immunohistochemistry that proved complementary to Western blot analysis. We demonstrated a significant relative reduction in FHL2 protein expression across different forms of human heart failure. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. Transcriptome analysis of zebrafish embryogenesis using microarrays.

    Directory of Open Access Journals (Sweden)

    Sinnakaruppan Mathavan

    2005-08-01

    Full Text Available Zebrafish (Danio rerio is a well-recognized model for the study of vertebrate developmental genetics, yet at the same time little is known about the transcriptional events that underlie zebrafish embryogenesis. Here we have employed microarray analysis to study the temporal activity of developmentally regulated genes during zebrafish embryogenesis. Transcriptome analysis at 12 different embryonic time points covering five different developmental stages (maternal, blastula, gastrula, segmentation, and pharyngula revealed a highly dynamic transcriptional profile. Hierarchical clustering, stage-specific clustering, and algorithms to detect onset and peak of gene expression revealed clearly demarcated transcript clusters with maximum gene activity at distinct developmental stages as well as co-regulated expression of gene groups involved in dedicated functions such as organogenesis. Our study also revealed a previously unidentified cohort of genes that are transcribed prior to the mid-blastula transition, a time point earlier than when the zygotic genome was traditionally thought to become active. Here we provide, for the first time to our knowledge, a comprehensive list of developmentally regulated zebrafish genes and their expression profiles during embryogenesis, including novel information on the temporal expression of several thousand previously uncharacterized genes. The expression data generated from this study are accessible to all interested scientists from our institute resource database (http://giscompute.gis.a-star.edu.sg/~govind/zebrafish/data_download.html.

  12. Rapid Diagnosis of Bacterial Meningitis Using a Microarray

    Directory of Open Access Journals (Sweden)

    Ren-Jy Ben

    2008-06-01

    Conclusion: The microarray method provides a more accurate and rapid diagnostic tool for bacterial meningitis compared to traditional culture methods. Clinical application of this new technique may reduce the potential risk of delay in treatment.

  13. Identification of mycotoxigenic fungi using an oligonucleotide microarray

    CSIR Research Space (South Africa)

    Barros, E

    2013-01-01

    Full Text Available the development of an oligonucleotide microarray specific for eleven mycotoxigenic fungi isolated from different food commodities in South Africa. This array is suitable for the detection and identification of cultures of potential mycotoxigenic fungi in both...

  14. Novel Protein Microarray Technology to Examine Men with Prostate Cancer

    National Research Council Canada - National Science Library

    Lilja, Hans

    2005-01-01

    The authors developed a novel macro and nanoporous silicon surface for protein microarrays to facilitate high-throughput biomarker discovery, and high-density protein-chip array analyses of complex biological samples...

  15. Kernel Based Nonlinear Dimensionality Reduction and Classification for Genomic Microarray

    Science.gov (United States)

    Li, Xuehua; Shu, Lan

    2008-01-01

    Genomic microarrays are powerful research tools in bioinformatics and modern medicinal research because they enable massively-parallel assays and simultaneous monitoring of thousands of gene expression of biological samples. However, a simple microarray experiment often leads to very high-dimensional data and a huge amount of information, the vast amount of data challenges researchers into extracting the important features and reducing the high dimensionality. In this paper, a nonlinear dimensionality reduction kernel method based locally linear embedding(LLE) is proposed, and fuzzy K-nearest neighbors algorithm which denoises datasets will be introduced as a replacement to the classical LLE's KNN algorithm. In addition, kernel method based support vector machine (SVM) will be used to classify genomic microarray data sets in this paper. We demonstrate the application of the techniques to two published DNA microarray data sets. The experimental results confirm the superiority and high success rates of the presented method. PMID:27879930

  16. Kernel Based Nonlinear Dimensionality Reduction and Classification for Genomic Microarray.

    Science.gov (United States)

    Li, Xuehua; Shu, Lan

    2008-07-15

    Genomic microarrays are powerful research tools in bioinformatics and modern medicinal research because they enable massively-parallel assays and simultaneous monitoring of thousands of gene expression of biological samples. However, a simple microarray experiment often leads to very high-dimensional data and a huge amount of information, the vast amount of data challenges researchers into extracting the important features and reducing the high dimensionality. In this paper, a nonlinear dimensionality reduction kernel method based locally linear embedding(LLE) is proposed, and fuzzy K-nearest neighbors algorithm which denoises datasets will be introduced as a replacement to the classical LLE's KNN algorithm. In addition, kernel method based support vector machine (SVM) will be used to classify genomic microarray data sets in this paper. We demonstrate the application of the techniques to two published DNA microarray data sets. The experimental results confirm the superiority and high success rates of the presented method.

  17. Profiling In Situ Microbial Community Structure with an Amplification Microarray

    Science.gov (United States)

    Knickerbocker, Christopher; Bryant, Lexi; Golova, Julia; Wiles, Cory; Williams, Kenneth H.; Peacock, Aaron D.; Long, Philip E.

    2013-01-01

    The objectives of this study were to unify amplification, labeling, and microarray hybridization chemistries within a single, closed microfluidic chamber (an amplification microarray) and verify technology performance on a series of groundwater samples from an in situ field experiment designed to compare U(VI) mobility under conditions of various alkalinities (as HCO3−) during stimulated microbial activity accompanying acetate amendment. Analytical limits of detection were between 2 and 200 cell equivalents of purified DNA. Amplification microarray signatures were well correlated with 16S rRNA-targeted quantitative PCR results and hybridization microarray signatures. The succession of the microbial community was evident with and consistent between the two microarray platforms. Amplification microarray analysis of acetate-treated groundwater showed elevated levels of iron-reducing bacteria (Flexibacter, Geobacter, Rhodoferax, and Shewanella) relative to the average background profile, as expected. Identical molecular signatures were evident in the transect treated with acetate plus NaHCO3, but at much lower signal intensities and with a much more rapid decline (to nondetection). Azoarcus, Thaurea, and Methylobacterium were responsive in the acetate-only transect but not in the presence of bicarbonate. Observed differences in microbial community composition or response to bicarbonate amendment likely had an effect on measured rates of U reduction, with higher rates probable in the part of the field experiment that was amended with bicarbonate. The simplification in microarray-based work flow is a significant technological advance toward entirely closed-amplicon microarray-based tests and is generally extensible to any number of environmental monitoring applications. PMID:23160129

  18. Emerging use of gene expression microarrays in plant physiology.

    Science.gov (United States)

    Wullschleger, Stan D; Difazio, Stephen P

    2003-01-01

    Microarrays have become an important technology for the global analysis of gene expression in humans, animals, plants, and microbes. Implemented in the context of a well-designed experiment, cDNA and oligonucleotide arrays can provide highthroughput, simultaneous analysis of transcript abundance for hundreds, if not thousands, of genes. However, despite widespread acceptance, the use of microarrays as a tool to better understand processes of interest to the plant physiologist is still being explored. To help illustrate current uses of microarrays in the plant sciences, several case studies that we believe demonstrate the emerging application of gene expression arrays in plant physiology were selected from among the many posters and presentations at the 2003 Plant and Animal Genome XI Conference. Based on this survey, microarrays are being used to assess gene expression in plants exposed to the experimental manipulation of air temperature, soil water content and aluminium concentration in the root zone. Analysis often includes characterizing transcript profiles for multiple post-treatment sampling periods and categorizing genes with common patterns of response using hierarchical clustering techniques. In addition, microarrays are also providing insights into developmental changes in gene expression associated with fibre and root elongation in cotton and maize, respectively. Technical and analytical limitations of microarrays are discussed and projects attempting to advance areas of microarray design and data analysis are highlighted. Finally, although much work remains, we conclude that microarrays are a valuable tool for the plant physiologist interested in the characterization and identification of individual genes and gene families with potential application in the fields of agriculture, horticulture and forestry.

  19. Microarray analysis of gene expression during bacteriophage T4 infection.

    Science.gov (United States)

    Luke, Kimberly; Radek, Agnes; Liu, XiuPing; Campbell, John; Uzan, Marc; Haselkorn, Robert; Kogan, Yakov

    2002-08-01

    Genomic microarrays were used to examine the complex temporal program of gene expression exhibited by bacteriophage T4 during the course of development. The microarray data confirm the existence of distinct early, middle, and late transcriptional classes during the bacteriophage replicative cycle. This approach allows assignment of previously uncharacterized genes to specific temporal classes. The genomic expression data verify many promoter assignments and predict the existence of previously unidentified promoters.

  20. Universal Reference RNA as a standard for microarray experiments

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    Fero Michael

    2004-03-01

    Full Text Available Abstract Background Obtaining reliable and reproducible two-color microarray gene expression data is critically important for understanding the biological significance of perturbations made on a cellular system. Microarray design, RNA preparation and labeling, hybridization conditions and data acquisition and analysis are variables difficult to simultaneously control. A useful tool for monitoring and controlling intra- and inter-experimental variation is Universal Reference RNA (URR, developed with the goal of providing hybridization signal at each microarray probe location (spot. Measuring signal at each spot as the ratio of experimental RNA to reference RNA targets, rather than relying on absolute signal intensity, decreases variability by normalizing signal output in any two-color hybridization experiment. Results Human, mouse and rat URR (UHRR, UMRR and URRR, respectively were prepared from pools of RNA derived from individual cell lines representing different tissues. A variety of microarrays were used to determine percentage of spots hybridizing with URR and producing signal above a user defined threshold (microarray coverage. Microarray coverage was consistently greater than 80% for all arrays tested. We confirmed that individual cell lines contribute their own unique set of genes to URR, arguing for a pool of RNA from several cell lines as a better configuration for URR as opposed to a single cell line source for URR. Microarray coverage comparing two separately prepared batches each of UHRR, UMRR and URRR were highly correlated (Pearson's correlation coefficients of 0.97. Conclusion Results of this study demonstrate that large quantities of pooled RNA from individual cell lines are reproducibly prepared and possess diverse gene representation. This type of reference provides a standard for reducing variation in microarray experiments and allows more reliable comparison of gene expression data within and between experiments and

  1. Design and analysis of mismatch probes for long oligonucleotide microarrays

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    Deng, Ye; He, Zhili; Van Nostrand, Joy D.; Zhou, Jizhong

    2008-08-15

    Nonspecific hybridization is currently a major concern with microarray technology. One of most effective approaches to estimating nonspecific hybridizations in oligonucleotide microarrays is the utilization of mismatch probes; however, this approach has not been used for longer oligonucleotide probes. Here, an oligonucleotide microarray was constructed to evaluate and optimize parameters for 50-mer mismatch probe design. A perfect match (PM) and 28 mismatch (MM) probes were designed for each of ten target genes selected from three microorganisms. The microarrays were hybridized with synthesized complementary oligonucleotide targets at different temperatures (e.g., 42, 45 and 50 C). In general, the probes with evenly distributed mismatches were more distinguishable than those with randomly distributed mismatches. MM probes with 3, 4 and 5 mismatched nucleotides were differentiated for 50-mer oligonucleotide probes hybridized at 50, 45 and 42 C, respectively. Based on the experimental data generated from this study, a modified positional dependent nearest neighbor (MPDNN) model was constructed to adjust the thermodynamic parameters of matched and mismatched dimer nucleotides in the microarray environment. The MM probes with four flexible positional mismatches were designed using the newly established MPDNN model and the experimental results demonstrated that the redesigned MM probes could yield more consistent hybridizations. Conclusions: This study provides guidance on the design of MM probes for long oligonucleotides (e.g., 50 mers). The novel MPDNN model has improved the consistency for long MM probes, and this modeling method can potentially be used for the prediction of oligonucleotide microarray hybridizations.

  2. Assessing Bacterial Interactions Using Carbohydrate-Based Microarrays

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    Andrea Flannery

    2015-12-01

    Full Text Available Carbohydrates play a crucial role in host-microorganism interactions and many host glycoconjugates are receptors or co-receptors for microbial binding. Host glycosylation varies with species and location in the body, and this contributes to species specificity and tropism of commensal and pathogenic bacteria. Additionally, bacterial glycosylation is often the first bacterial molecular species encountered and responded to by the host system. Accordingly, characterising and identifying the exact structures involved in these critical interactions is an important priority in deciphering microbial pathogenesis. Carbohydrate-based microarray platforms have been an underused tool for screening bacterial interactions with specific carbohydrate structures, but they are growing in popularity in recent years. In this review, we discuss carbohydrate-based microarrays that have been profiled with whole bacteria, recombinantly expressed adhesins or serum antibodies. Three main types of carbohydrate-based microarray platform are considered; (i conventional carbohydrate or glycan microarrays; (ii whole mucin microarrays; and (iii microarrays constructed from bacterial polysaccharides or their components. Determining the nature of the interactions between bacteria and host can help clarify the molecular mechanisms of carbohydrate-mediated interactions in microbial pathogenesis, infectious disease and host immune response and may lead to new strategies to boost therapeutic treatments.

  3. Protein microarray: sensitive and effective immunodetection for drug residues

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    Zer Cindy

    2010-02-01

    Full Text Available Abstract Background Veterinary drugs such as clenbuterol (CL and sulfamethazine (SM2 are low molecular weight ( Results The artificial antigens were spotted on microarray slides. Standard concentrations of the compounds were added to compete with the spotted antigens for binding to the antisera to determine the IC50. Our microarray assay showed the IC50 were 39.6 ng/ml for CL and 48.8 ng/ml for SM2, while the traditional competitive indirect-ELISA (ci-ELISA showed the IC50 were 190.7 ng/ml for CL and 156.7 ng/ml for SM2. We further validated the two methods with CL fortified chicken muscle tissues, and the protein microarray assay showed 90% recovery while the ci-ELISA had 76% recovery rate. When tested with CL-fed chicken muscle tissues, the protein microarray assay had higher sensitivity (0.9 ng/g than the ci-ELISA (0.1 ng/g for detection of CL residues. Conclusions The protein microarrays showed 4.5 and 3.5 times lower IC50 than the ci-ELISA detection for CL and SM2, respectively, suggesting that immunodetection of small molecules with protein microarray is a better approach than the traditional ELISA technique.

  4. A fluorometric microarray with ZnO substrate-enhanced fluorescence and suppressed ``coffee-ring'' effects for fluorescence immunoassays

    Science.gov (United States)

    Li, Shuying; Dong, Minmin; Li, Rui; Zhang, Liyan; Qiao, Yuchun; Jiang, Yao; Qi, Wei; Wang, Hua

    2015-11-01

    immunoassays of human IgG, showing a linear detection range from 0.010 to 10.0 ng mL-1. Such a throughput-improved fluorometric microarray could be tailored for probing multiple biomarkers in complicated media like serum or blood. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr06070b

  5. New oligonucleotide microarray for rapid diagnosis of avian viral diseases.

    Science.gov (United States)

    Sultankulova, Kulyaisan T; Kozhabergenov, Nurlan S; Strochkov, Vitaliy M; Burashev, Yerbol D; Shorayeva, Kamshat A; Chervyakova, Olga V; Rametov, Nurkuisa M; Sandybayev, Nurlan T; Sansyzbay, Abylay R; Orynbayev, Mukhit B

    2017-04-05

    We developed a new oligonucleotide microarray comprising 16 identical subarrays for simultaneous rapid detection of avian viruses: avian influenza virus (AIV), Newcastle disease virus (NDV), infection bronchitis virus (IBV), and infectious bursal disease virus (IBDV) in single- and mixed-virus infections. The objective of the study was to develop an oligonucleotide microarray for rapid diagnosis of avian diseases that would be used in the course of mass analysis for routine epidemiological surveillance owing to its ability to test one specimen for several infections. The paper describes the technique for rapid and simultaneous diagnosis of avian diseases such as avian influenza, Newcastle disease, infectious bronchitis and infectious bursal disease with use of oligonucleotide microarray, conditions for hybridization of fluorescent-labelled viral cDNA on the microarray and its specificity tested with use of AIV, NDV, IBV, IBDV strains as well as biomaterials from poultry. Sensitivity and specificity of the developed microarray was evaluated with use of 122 specimens of biological material: 44 cloacal swabs from sick birds and 78 tissue specimens from dead wild and domestic birds, as well as with use of 15 AIV, NDV, IBV and IBDV strains, different in their origin, epidemiological and biological characteristics (RIBSP Microbial Collection). This microarray demonstrates high diagnostic sensitivity (99.16% within 95% CI limits 97.36-100%) and specificity (100%). Specificity of the developed technique was confirmed by direct sequencing of NP and M (AIV), VP2 (IBDV), S1 (IBV), NP (NDV) gene fragments. Diagnostic effectiveness of the developed DNA microarray is 99.18% and therefore it can be used in mass survey for specific detection of AIV, NDV, IBV and IBDV circulating in the region in the course of epidemiological surveillance. Rather simple method for rapid diagnosis of avian viral diseases that several times shortens duration of assay versus classical diagnostic

  6. DNA Microarray Detection of 18 Important Human Blood Protozoan Species.

    Science.gov (United States)

    Chen, Mu-Xin; Ai, Lin; Chen, Jun-Hu; Feng, Xin-Yu; Chen, Shao-Hong; Cai, Yu-Chun; Lu, Yan; Zhou, Xiao-Nong; Chen, Jia-Xu; Hu, Wei

    2016-12-01

    Accurate detection of blood protozoa from clinical samples is important for diagnosis, treatment and control of related diseases. In this preliminary study, a novel DNA microarray system was assessed for the detection of Plasmodium, Leishmania, Trypanosoma, Toxoplasma gondii and Babesia in humans, animals, and vectors, in comparison with microscopy and PCR data. Developing a rapid, simple, and convenient detection method for protozoan detection is an urgent need. The microarray assay simultaneously identified 18 species of common blood protozoa based on the differences in respective target genes. A total of 20 specific primer pairs and 107 microarray probes were selected according to conserved regions which were designed to identify 18 species in 5 blood protozoan genera. The positive detection rate of the microarray assay was 91.78% (402/438). Sensitivity and specificity for blood protozoan detection ranged from 82.4% (95%CI: 65.9% ~ 98.8%) to 100.0% and 95.1% (95%CI: 93.2% ~ 97.0%) to 100.0%, respectively. Positive predictive value (PPV) and negative predictive value (NPV) ranged from 20.0% (95%CI: 2.5% ~ 37.5%) to 100.0% and 96.8% (95%CI: 95.0% ~ 98.6%) to 100.0%, respectively. Youden index varied from 0.82 to 0.98. The detection limit of the DNA microarrays ranged from 200 to 500 copies/reaction, similar to PCR findings. The concordance rate between microarray data and DNA sequencing results was 100%. Overall, the newly developed microarray platform provides a convenient, highly accurate, and reliable clinical assay for the determination of blood protozoan species.

  7. Advanced spot quality analysis in two-colour microarray experiments

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    Vetter Guillaume

    2008-09-01

    Full Text Available Abstract Background Image analysis of microarrays and, in particular, spot quantification and spot quality control, is one of the most important steps in statistical analysis of microarray data. Recent methods of spot quality control are still in early age of development, often leading to underestimation of true positive microarray features and, consequently, to loss of important biological information. Therefore, improving and standardizing the statistical approaches of spot quality control are essential to facilitate the overall analysis of microarray data and subsequent extraction of biological information. Findings We evaluated the performance of two image analysis packages MAIA and GenePix (GP using two complementary experimental approaches with a focus on the statistical analysis of spot quality factors. First, we developed control microarrays with a priori known fluorescence ratios to verify the accuracy and precision of the ratio estimation of signal intensities. Next, we developed advanced semi-automatic protocols of spot quality evaluation in MAIA and GP and compared their performance with available facilities of spot quantitative filtering in GP. We evaluated these algorithms for standardised spot quality analysis in a whole-genome microarray experiment assessing well-characterised transcriptional modifications induced by the transcription regulator SNAI1. Using a set of RT-PCR or qRT-PCR validated microarray data, we found that the semi-automatic protocol of spot quality control we developed with MAIA allowed recovering approximately 13% more spots and 38% more differentially expressed genes (at FDR = 5% than GP with default spot filtering conditions. Conclusion Careful control of spot quality characteristics with advanced spot quality evaluation can significantly increase the amount of confident and accurate data resulting in more meaningful biological conclusions.

  8. Development of an ordered microarray of electrochemiluminescent nanosensors

    Science.gov (United States)

    Chovin, Arnaud; Garrigue, Patrick; Pecastaings, Gilles; Saadaoui, Hassan; Sojic, Neso

    2006-05-01

    A microarray of electrochemiluminescent (ECL) nanosensors for remote detection is reported. Such nanosensor arrays were created on the distal face of coherent optical fibre bundles by adapting near-field optical probe and nanoelectrode methodologies. The fabrication process allows the production of high-density microarrays of nanosensors where each optical aperture is surrounded by a gold nanoring electrode. The initial architecture of the optical fibre bundle is retained and thus the microarray keeps its imaging properties. The electrochemical response of the array displays a steady-state current. This feature indicates that the nanoelectrodes forming the array can be considered as diffusively independent. In other words, each ring-shaped electrode of the array probes electrochemically a different micro-environment. We also show that this microdevice can be used as an ECL nanosensor microarray. Indeed, ECL light is initiated by the gold nanoring electrode in the presence of a co-reactant biospecies, NADH. A fraction of the isotropically electrochemically generated light is collected by the same aperture, transmitted by the corresponding fibre core and eventually imaged by a CCD camera. The gold coating therefore acts as an electrode material and also to confine the ECL light in each etched core. Such nanostructured microdevice integrates ECL-light generation, collection and imaging in a microarray format.

  9. Oligonucleotide microarrays: immobilization of phosphorylated oligonucleotides on epoxylated surface.

    Science.gov (United States)

    Mahajan, S; Kumar, P; Gupta, K C

    2006-01-01

    A facile and efficient method for direct immobilization of phosphorylated oligonucleotides on an epoxy-activated glass surface is described. The new immobilization strategy has been analyzed for its performance in DNA microarray under both microwave and thermal conditions. It reflects high immobilization efficiency ( approximately 23%), and signal-to-noise ratio ( approximately 98) and resulted in high hybridization efficiency ( approximately 36%) in comparison to those obtained with standard methods, viz., NTMTA ( approximately 9.76%) and epoxide-amine ( approximately 9.82%). The probes immobilized through the new strategy were found to be heat-stable, since the performance of microarray decreased by only approximately 7% after subjecting it to 20 PCR-like heat cycles, suggesting that the chemistry could be used in integrated PCR/microarray devices. The immobilization of probes following the proposed chemistry resulted in spots of superior quality in terms of spot morphology, spot homogeneity, and signal reproducibility. The constructed microarrays have been successfully used for the discrimination of nucleotide mismatches. In conclusion, these features make the new immobilization strategy ideal for facile, efficient, and cost-effective manufacturing of DNA microarrays.

  10. Automated multidimensional phenotypic profiling using large public microarray repositories

    Science.gov (United States)

    Xu, Min; Li, Wenyuan; James, Gareth M.; Mehan, Michael R.; Zhou, Xianghong Jasmine

    2009-01-01

    Phenotypes are complex, and difficult to quantify in a high-throughput fashion. The lack of comprehensive phenotype data can prevent or distort genotype–phenotype mapping. Here, we describe “PhenoProfiler,” a computational method that enables in silico phenotype profiling. Drawing on the principle that similar gene expression patterns are likely to be associated with similar phenotype patterns, PhenoProfiler supplements the missing quantitative phenotype information for a given microarray dataset based on other well-characterized microarray datasets. We applied our method to 587 human microarray datasets covering >14,000 samples, and confirmed that the predicted phenotype profiles are highly consistent with true phenotype descriptions. PhenoProfiler offers several unique capabilities: (i) automated, multidimensional phenotype profiling, facilitating the analysis and treatment design of complex diseases; (ii) the extrapolation of phenotype profiles beyond provided classes; and (iii) the detection of confounding phenotype factors that could otherwise bias biological inferences. Finally, because no direct comparisons are made between gene expression values from different datasets, the method can use the entire body of cross-platform microarray data. This work has produced a compendium of phenotype profiles for the National Center for Biotechnology Information GEO datasets, which can facilitate an unbiased understanding of the transcriptome-phenome mapping. The continued accumulation of microarray data will further increase the power of PhenoProfiler, by increasing the variety and the quality of phenotypes to be profiled. PMID:19590007

  11. Statistical implications of pooling RNA samples for microarray experiments

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    Landfield Philip W

    2003-06-01

    Full Text Available Abstract Background Microarray technology has become a very important tool for studying gene expression profiles under various conditions. Biologists often pool RNA samples extracted from different subjects onto a single microarray chip to help defray the cost of microarray experiments as well as to correct for the technical difficulty in getting sufficient RNA from a single subject. However, the statistical, technical and financial implications of pooling have not been explicitly investigated. Results Modeling the resulting gene expression from sample pooling as a mixture of individual responses, we derived expressions for the experimental error and provided both upper and lower bounds for its value in terms of the variability among individuals and the number of RNA samples pooled. Using "virtual" pooling of data from real experiments and computer simulations, we investigated the statistical properties of RNA sample pooling. Our study reveals that pooling biological samples appropriately is statistically valid and efficient for microarray experiments. Furthermore, optimal pooling design(s can be found to meet statistical requirements while minimizing total cost. Conclusions Appropriate RNA pooling can provide equivalent power and improve efficiency and cost-effectiveness for microarray experiments with a modest increase in total number of subjects. Pooling schemes in terms of replicates of subjects and arrays can be compared before experiments are conducted.

  12. Evaluating melanocytic lesions with single nucleotide polymorphism (SNP) chromosomal microarray.

    Science.gov (United States)

    Hedayat, Amin A; Linos, Konstantinos; Jung, Hou-Sung; Tafe, Laura J; Yan, Shaofeng; LeBlanc, Robert E; Lefferts, Joel A

    2017-12-01

    Histopathology is the gold standard for diagnosing melanocytic lesions; however, distinguishing benign versus malignant is not always clear histologically. Single nucleotide polymorphism (SNP) microarray analysis may help in making a definitive diagnosis. Here, we share our experience with the Oncoscan FFPE Assay and demonstrate its diagnostic utility in the context of ambiguous melanocytic lesions. Eleven archival melanocytic lesions, including three benign nevi, four melanomas, three BAP1-deficient Spitzoid nevi and one nevoid melanoma were selected for validation. SNP-array was performed according to the manufacturer's protocol, using the recommended 80ng of DNA; however, as little as 15ng was used if the extraction yield was lower. Concordance was assessed with H&E and various combinations of BAP1 and p16 immunohistochemical stains (IHC) and external reference laboratory chromosomal microarray results. After validation, the SNP array was utilized to make definitive diagnoses in four challenging cases. Oncoscan SNP array findings were in concordance with H&E, IHC, and reference laboratory chromosomal microarray testing. The SNP-based microarray can accurately detect copy number changes and aid in making a more definitive diagnosis of challenging melanocytic lesions. This can be accomplished using significantly less DNA than is required by other microarray technologies. Copyright © 2017. Published by Elsevier Inc.

  13. Can Zipf's law be adapted to normalize microarrays?

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    Häsler Robert

    2005-02-01

    Full Text Available Abstract Background Normalization is the process of removing non-biological sources of variation between array experiments. Recent investigations of data in gene expression databases for varying organisms and tissues have shown that the majority of expressed genes exhibit a power-law distribution with an exponent close to -1 (i.e. obey Zipf's law. Based on the observation that our single channel and two channel microarray data sets also followed a power-law distribution, we were motivated to develop a normalization method based on this law, and examine how it compares with existing published techniques. A computationally simple and intuitively appealing technique based on this observation is presented. Results Using pairwise comparisons using MA plots (log ratio vs. log intensity, we compared this novel method to previously published normalization techniques, namely global normalization to the mean, the quantile method, and a variation on the loess normalization method designed specifically for boutique microarrays. Results indicated that, for single channel microarrays, the quantile method was superior with regard to eliminating intensity-dependent effects (banana curves, but Zipf's law normalization does minimize this effect by rotating the data distribution such that the maximal number of data points lie on the zero of the log ratio axis. For two channel boutique microarrays, the Zipf's law normalizations performed as well as, or better than existing techniques. Conclusion Zipf's law normalization is a useful tool where the Quantile method cannot be applied, as is the case with microarrays containing functionally specific gene sets (boutique arrays.

  14. Advanced Data Mining of Leukemia Cells Micro-Arrays

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    Ryan M. Pierce

    2009-12-01

    Full Text Available This paper provides continuation and extensions of previous research by Segall and Pierce (2009a that discussed data mining for micro-array databases of Leukemia cells for primarily self-organized maps (SOM. As Segall and Pierce (2009a and Segall and Pierce (2009b the results of applying data mining are shown and discussed for the data categories of microarray databases of HL60, Jurkat, NB4 and U937 Leukemia cells that are also described in this article. First, a background section is provided on the work of others pertaining to the applications of data mining to micro-array databases of Leukemia cells and micro-array databases in general. As noted in predecessor article by Segall and Pierce (2009a, micro-array databases are one of the most popular functional genomics tools in use today. This research in this paper is intended to use advanced data mining technologies for better interpretations and knowledge discovery as generated by the patterns of gene expressions of HL60, Jurkat, NB4 and U937 Leukemia cells. The advanced data mining performed entailed using other data mining tools such as cubic clustering criterion, variable importance rankings, decision trees, and more detailed examinations of data mining statistics and study of other self-organized maps (SOM clustering regions of workspace as generated by SAS Enterprise Miner version 4. Conclusions and future directions of the research are also presented.

  15. Tissue Microarray: A rapidly evolving diagnostic and research tool

    Science.gov (United States)

    Jawhar, Nazar M.T.

    2009-01-01

    Tissue microarray is a recent innovation in the field of pathology. A microarray contains many small representative tissue samples from hundreds of different cases assembled on a single histologic slide, and therefore allows high throughput analysis of multiple specimens at the same time. Tissue microarrays are paraffin blocks produced by extracting cylindrical tissue cores from different paraffin donor blocks and re-embedding these into a single recipient (microarray) block at defined array coordinates. Using this technique, up to 1000 or more tissue samples can be arrayed into a single paraffin block. It can permit simultaneous analysis of molecular targets at the DNA, mRNA, and protein levels under identical, standardized conditions on a single glass slide, and also provide maximal preservation and use of limited and irreplaceable archival tissue samples. This versatile technique, in which data analysis is automated facilitates retrospective and prospective human tissue studies. It is a practical and effective tool for high-throughput molecular analysis of tissues that is helping to identify new diagnostic and prognostic markers and targets in human cancers, and has a range of potential applications in basic research, prognostic oncology and drug discovery. This article summarizes the technical aspects of tissue microarray construction and sectioning, advantages, application, and limitations. PMID:19318744

  16. Significance analysis of lexical bias in microarray data

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    Falkow Stanley

    2003-04-01

    Full Text Available Abstract Background Genes that are determined to be significantly differentially regulated in microarray analyses often appear to have functional commonalities, such as being components of the same biochemical pathway. This results in certain words being under- or overrepresented in the list of genes. Distinguishing between biologically meaningful trends and artifacts of annotation and analysis procedures is of the utmost importance, as only true biological trends are of interest for further experimentation. A number of sophisticated methods for identification of significant lexical trends are currently available, but these methods are generally too cumbersome for practical use by most microarray users. Results We have developed a tool, LACK, for calculating the statistical significance of apparent lexical bias in microarray datasets. The frequency of a user-specified list of search terms in a list of genes which are differentially regulated is assessed for statistical significance by comparison to randomly generated datasets. The simplicity of the input files and user interface targets the average microarray user who wishes to have a statistical measure of apparent lexical trends in analyzed datasets without the need for bioinformatics skills. The software is available as Perl source or a Windows executable. Conclusion We have used LACK in our laboratory to generate biological hypotheses based on our microarray data. We demonstrate the program's utility using an example in which we confirm significant upregulation of SPI-2 pathogenicity island of Salmonella enterica serovar Typhimurium by the cation chelator dipyridyl.

  17. AN IMPROVED FUZZY CLUSTERING ALGORITHM FOR MICROARRAY IMAGE SPOTS SEGMENTATION

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    V.G. Biju

    2015-11-01

    Full Text Available An automatic cDNA microarray image processing using an improved fuzzy clustering algorithm is presented in this paper. The spot segmentation algorithm proposed uses the gridding technique developed by the authors earlier, for finding the co-ordinates of each spot in an image. Automatic cropping of spots from microarray image is done using these co-ordinates. The present paper proposes an improved fuzzy clustering algorithm Possibility fuzzy local information c means (PFLICM to segment the spot foreground (FG from background (BG. The PFLICM improves fuzzy local information c means (FLICM algorithm by incorporating typicality of a pixel along with gray level information and local spatial information. The performance of the algorithm is validated using a set of simulated cDNA microarray images added with different levels of AWGN noise. The strength of the algorithm is tested by computing the parameters such as the Segmentation matching factor (SMF, Probability of error (pe, Discrepancy distance (D and Normal mean square error (NMSE. SMF value obtained for PFLICM algorithm shows an improvement of 0.9 % and 0.7 % for high noise and low noise microarray images respectively compared to FLICM algorithm. The PFLICM algorithm is also applied on real microarray images and gene expression values are computed.

  18. Probe Selection for DNA Microarrays using OligoWiz

    DEFF Research Database (Denmark)

    Wernersson, Rasmus; Juncker, Agnieszka; Nielsen, Henrik Bjørn

    2007-01-01

    Nucleotide abundance measurements using DNA microarray technology are possible only if appropriate probes complementary to the target nucleotides can be identified. Here we present a protocol for selecting DNA probes for microarrays using the OligoWiz application. OligoWiz is a client-server appl......Nucleotide abundance measurements using DNA microarray technology are possible only if appropriate probes complementary to the target nucleotides can be identified. Here we present a protocol for selecting DNA probes for microarrays using the OligoWiz application. OligoWiz is a client......-server application that offers a detailed graphical interface and real-time user interaction on the client side, and massive computer power and a large collection of species databases (400, summer 2007) on the server side. Probes are selected according to five weighted scores: cross-hybridization, deltaT(m), folding...... computer skills and can be executed from any Internet-connected computer. The probe selection procedure for a standard microarray design targeting all yeast transcripts can be completed in 1 h....

  19. Plastic protein microarray to investigate the molecular pathways of magnetic nanoparticle-induced nanotoxicity

    International Nuclear Information System (INIS)

    Liu Yingshuai; Li Xuelian; Bao Shujuan; Lu Zhisong; Li Changming; Li Qing

    2013-01-01

    Superparamagnetic iron oxide nanoparticles (SPIONs) (about 15 nm) were synthesized via a hydrothermal method and characterized by field emission scanning electron microscopy, transmission electron microscopy, dynamic light scattering, x-ray diffraction, and vibrating sample magnetometer. The molecular pathways of SPIONs-induced nanotoxicity was further investigated by protein microarrays on a plastic substrate from evaluation of cell viability, reactive oxygen species (ROS) generation and cell apoptosis. The experimental results reveal that 50 μg ml −1 or higher levels of SPIONs cause significant loss of cell viability, considerable generation of ROS and cell apoptosis. It is proposed that high level SPIONs could induce cell apoptosis via a mitochondria-mediated intrinsic pathway by activation of caspase 9 and caspase 3, an increase of the Bax/Bcl-2 ratio, and down-regulation of HSP70 and HSP90 survivor factors. (paper)

  20. Plastic protein microarray to investigate the molecular pathways of magnetic nanoparticle-induced nanotoxicity

    Science.gov (United States)

    Liu, Yingshuai; Li, Xuelian; Bao, Shujuan; Lu, Zhisong; Li, Qing; Li, Chang Ming

    2013-05-01

    Superparamagnetic iron oxide nanoparticles (SPIONs) (about 15 nm) were synthesized via a hydrothermal method and characterized by field emission scanning electron microscopy, transmission electron microscopy, dynamic light scattering, x-ray diffraction, and vibrating sample magnetometer. The molecular pathways of SPIONs-induced nanotoxicity was further investigated by protein microarrays on a plastic substrate from evaluation of cell viability, reactive oxygen species (ROS) generation and cell apoptosis. The experimental results reveal that 50 μg ml-1 or higher levels of SPIONs cause significant loss of cell viability, considerable generation of ROS and cell apoptosis. It is proposed that high level SPIONs could induce cell apoptosis via a mitochondria-mediated intrinsic pathway by activation of caspase 9 and caspase 3, an increase of the Bax/Bcl-2 ratio, and down-regulation of HSP70 and HSP90 survivor factors.

  1. MICROARRAY IMAGE GRIDDING USING GRID LINE REFINEMENT TECHNIQUE

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    V.G. Biju

    2015-05-01

    Full Text Available An important stage in microarray image analysis is gridding. Microarray image gridding is done to locate sub arrays in a microarray image and find co-ordinates of spots within each sub array. For accurate identification of spots, most of the proposed gridding methods require human intervention. In this paper a fully automatic gridding method which enhances spot intensity in the preprocessing step as per a histogram based threshold method is used. The gridding step finds co-ordinates of spots from horizontal and vertical profile of the image. To correct errors due to the grid line placement, a grid line refinement technique is proposed. The algorithm is applied on different image databases and results are compared based on spot detection accuracy and time. An average spot detection accuracy of 95.06% depicts the proposed method’s flexibility and accuracy in finding the spot co-ordinates for different database images.

  2. Comparative analysis of genomic signal processing for microarray data clustering.

    Science.gov (United States)

    Istepanian, Robert S H; Sungoor, Ala; Nebel, Jean-Christophe

    2011-12-01

    Genomic signal processing is a new area of research that combines advanced digital signal processing methodologies for enhanced genetic data analysis. It has many promising applications in bioinformatics and next generation of healthcare systems, in particular, in the field of microarray data clustering. In this paper we present a comparative performance analysis of enhanced digital spectral analysis methods for robust clustering of gene expression across multiple microarray data samples. Three digital signal processing methods: linear predictive coding, wavelet decomposition, and fractal dimension are studied to provide a comparative evaluation of the clustering performance of these methods on several microarray datasets. The results of this study show that the fractal approach provides the best clustering accuracy compared to other digital signal processing and well known statistical methods.

  3. DNA microarray data and contextual analysis of correlation graphs

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    Hingamp Pascal

    2003-04-01

    Full Text Available Abstract Background DNA microarrays are used to produce large sets of expression measurements from which specific biological information is sought. Their analysis requires efficient and reliable algorithms for dimensional reduction, classification and annotation. Results We study networks of co-expressed genes obtained from DNA microarray experiments. The mathematical concept of curvature on graphs is used to group genes or samples into clusters to which relevant gene or sample annotations are automatically assigned. Application to publicly available yeast and human lymphoma data demonstrates the reliability of the method in spite of its simplicity, especially with respect to the small number of parameters involved. Conclusions We provide a method for automatically determining relevant gene clusters among the many genes monitored with microarrays. The automatic annotations and the graphical interface improve the readability of the data. A C++ implementation, called Trixy, is available from http://tagc.univ-mrs.fr/bioinformatics/trixy.html.

  4. Screening of cDNA libraries on glass slide microarrays.

    Science.gov (United States)

    Berger, Dave K; Crampton, Bridget G; Hein, Ingo; Vos, Wiesner

    2007-01-01

    A quantitative screening method was developed to evaluate the quality of cDNA libraries constructed by suppression subtraction hybridization (SSH) or other enrichment techniques. The SSH technique was adapted to facilitate screening of the resultant library on a small number of glass slide microarrays. A simple data analysis pipeline named SSHscreen using "linear models for microarray data" (limma) functions in the R computing environment was developed to identify clones in the cDNA libraries that are significantly differentially expressed, and to determine if they were rare or abundant in the original treated sample. This approach facilitates the choice of clones from the cDNA library for further analysis, such as DNA sequencing, Northern blotting, RT-PCR, or detailed expression profiling using a custom cDNA microarray. Furthermore, this strategy is particularly useful for studies of nonmodel organisms for which there is little genome sequence information.

  5. D-MaPs - DNA-microarray projects: Web-based software for multi-platform microarray analysis.

    Science.gov (United States)

    Carazzolle, Marcelo F; Herig, Taís S; Deckmann, Ana C; Pereira, Gonçalo A G

    2009-07-01

    The web application D-Maps provides a user-friendly interface to researchers performing studies based on microarrays. The program was developed to manage and process one- or two-color microarray data obtained from several platforms (currently, GeneTAC, ScanArray, CodeLink, NimbleGen and Affymetrix). Despite the availability of many algorithms and many software programs designed to perform microarray analysis on the internet, these usually require sophisticated knowledge of mathematics, statistics and computation. D-maps was developed to overcome the requirement of high performance computers or programming experience. D-Maps performs raw data processing, normalization and statistical analysis, allowing access to the analyzed data in text or graphical format. An original feature presented by D-Maps is GEO (Gene Expression Omnibus) submission format service. The D-MaPs application was already used for analysis of oligonucleotide microarrays and PCR-spotted arrays (one- and two-color, laser and light scanner). In conclusion, D-Maps is a valuable tool for microarray research community, especially in the case of groups without a bioinformatic core.

  6. D-MaPs - DNA-microarray projects: web-based software for multi-platform microarray analysis

    Directory of Open Access Journals (Sweden)

    Marcelo F. Carazzolle

    2009-01-01

    Full Text Available The web application D-Maps provides a user-friendly interface to researchers performing studies based on microarrays. The program was developed to manage and process one- or two-color microarray data obtained from several platforms (currently, GeneTAC, ScanArray, CodeLink, NimbleGen and Affymetrix. Despite the availability of many algorithms and many software programs designed to perform microarray analysis on the internet, these usually require sophisticated knowledge of mathematics, statistics and computation. D-maps was developed to overcome the requirement of high performance computers or programming experience. D-Maps performs raw data processing, normalization and statistical analysis, allowing access to the analyzed data in text or graphical format. An original feature presented by D-Maps is GEO (Gene Expression Omnibus submission format service. The D-MaPs application was already used for analysis of oligonucleotide microarrays and PCR-spotted arrays (one- and two-color, laser and light scanner. In conclusion, D-Maps is a valuable tool for microarray research community, especially in the case of groups without a bioinformatic core.

  7. Hand-held portable microarray reader for biodetection

    Science.gov (United States)

    Thompson, Deanna Lynn; Coleman, Matthew A; Lane, Stephen M; Matthews, Dennis L; Albala, Joanna; Wachsmann-Hogiu, Sebastian

    2013-04-23

    A hand-held portable microarray reader for biodetection includes a microarray reader engineered to be small enough for portable applications. The invention includes a high-powered light-emitting diode that emits excitation light, an excitation filter positioned to receive the excitation light, a slide, a slide holder assembly for positioning the slide to receive the excitation light from the excitation filter, an emission filter positioned to receive the excitation light from the slide, a lens positioned to receive the excitation light from the emission filter, and a CCD camera positioned to receive the excitation light from the lens.

  8. Advanced Data Mining of Leukemia Cells Micro-Arrays

    OpenAIRE

    Richard S. Segall; Ryan M. Pierce

    2009-01-01

    This paper provides continuation and extensions of previous research by Segall and Pierce (2009a) that discussed data mining for micro-array databases of Leukemia cells for primarily self-organized maps (SOM). As Segall and Pierce (2009a) and Segall and Pierce (2009b) the results of applying data mining are shown and discussed for the data categories of microarray databases of HL60, Jurkat, NB4 and U937 Leukemia cells that are also described in this article. First, a background section is pro...

  9. Sensitivity and fidelity of DNA microarray improved with integration of Amplified Differential Gene Expression (ADGE

    Directory of Open Access Journals (Sweden)

    Ile Kristina E

    2003-07-01

    Full Text Available Abstract Background The ADGE technique is a method designed to magnify the ratios of gene expression before detection. It improves the detection sensitivity to small change of gene expression and requires small amount of starting material. However, the throughput of ADGE is low. We integrated ADGE with DNA microarray (ADGE microarray and compared it with regular microarray. Results When ADGE was integrated with DNA microarray, a quantitative relationship of a power function between detected and input ratios was found. Because of ratio magnification, ADGE microarray was better able to detect small changes in gene expression in a drug resistant model cell line system. The PCR amplification of templates and efficient labeling reduced the requirement of starting material to as little as 125 ng of total RNA for one slide hybridization and enhanced the signal intensity. Integration of ratio magnification, template amplification and efficient labeling in ADGE microarray reduced artifacts in microarray data and improved detection fidelity. The results of ADGE microarray were less variable and more reproducible than those of regular microarray. A gene expression profile generated with ADGE microarray characterized the drug resistant phenotype, particularly with reference to glutathione, proliferation and kinase pathways. Conclusion ADGE microarray magnified the ratios of differential gene expression in a power function, improved the detection sensitivity and fidelity and reduced the requirement for starting material while maintaining high throughput. ADGE microarray generated a more informative expression pattern than regular microarray.

  10. Spotted cotton oligonucleotide microarrays for gene expression analysis

    Directory of Open Access Journals (Sweden)

    Nettleton Dan

    2007-03-01

    Full Text Available Abstract Background Microarrays offer a powerful tool for diverse applications plant biology and crop improvement. Recently, two comprehensive assemblies of cotton ESTs were constructed based on three Gossypium species. Using these assemblies as templates, we describe the design and creation and of a publicly available oligonucleotide array for cotton, useful for all four of the cultivated species. Results Synthetic oligonucleotide probes were generated from exemplar sequences of a global assembly of 211,397 cotton ESTs derived from >50 different cDNA libraries representing many different tissue types and tissue treatments. A total of 22,787 oligonucleotide probes are included on the arrays, optimized to target the diversity of the transcriptome and previously studied cotton genes, transcription factors, and genes with homology to Arabidopsis. A small portion of the oligonucleotides target unidentified protein coding sequences, thereby providing an element of gene discovery. Because many oligonucleotides were based on ESTs from fiber-specific cDNA libraries, the microarray has direct application for analysis of the fiber transcriptome. To illustrate the utility of the microarray, we hybridized labeled bud and leaf cDNAs from G. hirsutum and demonstrate technical consistency of results. Conclusion The cotton oligonucleotide microarray provides a reproducible platform for transcription profiling in cotton, and is made publicly available through http://cottonevolution.info.

  11. Microarray-based large scale detection of single feature ...

    Indian Academy of Sciences (India)

    2015-12-08

    Dec 8, 2015 ... Hybridization and data quality. The five genotypes such as JKC703, JKC725, JKC737,. JKC777 and JKC783 were used in the present study. To assess our microarray intensity data, the raw intensity data of only PM probes/features of cotton cultivars were log2 transformed and studied by density plots, and ...

  12. Gene ordering in partitive clustering using microarray expressions

    Indian Academy of Sciences (India)

    PRAKASH KUMAR

    the new hybrid approach, finds comparable or sometimes superior biological gene order in less computation time than those obtained by optimal leaf ordering in hierarchical clustering solution. Ray S S, Bandyopadhyay S and Pal S K 2007 Gene ordering in partitive clustering using microarray expressions; J. Biosci.

  13. CONFIRMING MICROARRAY DATA--IS IT REALLY NECESSARY?

    Science.gov (United States)

    The generation of corroborative data has become a commonly used approach for ensuring the veracity of microarray data. Indeed, the need to conduct corroborative studies has now become official editorial policy for at least two journals, and several more are considering introducin...

  14. Dimension reduction methods for microarray data: a review

    Directory of Open Access Journals (Sweden)

    Rabia Aziz

    2017-03-01

    Full Text Available Dimension reduction has become inevitable for pre-processing of high dimensional data. “Gene expression microarray data” is an instance of such high dimensional data. Gene expression microarray data displays the maximum number of genes (features simultaneously at a molecular level with a very small number of samples. The copious numbers of genes are usually provided to a learning algorithm for producing a complete characterization of the classification task. However, most of the times the majority of the genes are irrelevant or redundant to the learning task. It will deteriorate the learning accuracy and training speed as well as lead to the problem of overfitting. Thus, dimension reduction of microarray data is a crucial preprocessing step for prediction and classification of disease. Various feature selection and feature extraction techniques have been proposed in the literature to identify the genes, that have direct impact on the various machine learning algorithms for classification and eliminate the remaining ones. This paper describes the taxonomy of dimension reduction methods with their characteristics, evaluation criteria, advantages and disadvantages. It also presents a review of numerous dimension reduction approaches for microarray data, mainly those methods that have been proposed over the past few years.

  15. Improving missing value estimation in microarray data with gene ontology.

    Science.gov (United States)

    Tuikkala, Johannes; Elo, Laura; Nevalainen, Olli S; Aittokallio, Tero

    2006-03-01

    Gene expression microarray experiments produce datasets with frequent missing expression values. Accurate estimation of missing values is an important prerequisite for efficient data analysis as many statistical and machine learning techniques either require a complete dataset or their results are significantly dependent on the quality of such estimates. A limitation of the existing estimation methods for microarray data is that they use no external information but the estimation is based solely on the expression data. We hypothesized that utilizing a priori information on functional similarities available from public databases facilitates the missing value estimation. We investigated whether semantic similarity originating from gene ontology (GO) annotations could improve the selection of relevant genes for missing value estimation. The relative contribution of each information source was automatically estimated from the data using an adaptive weight selection procedure. Our experimental results in yeast cDNA microarray datasets indicated that by considering GO information in the k-nearest neighbor algorithm we can enhance its performance considerably, especially when the number of experimental conditions is small and the percentage of missing values is high. The increase of performance was less evident with a more sophisticated estimation method. We conclude that even a small proportion of annotated genes can provide improvements in data quality significant for the eventual interpretation of the microarray experiments. Java and Matlab codes are available on request from the authors. Available online at http://users.utu.fi/jotatu/GOImpute.html.

  16. Broad spectrum microarray for fingerprint-based bacterial species identification

    Directory of Open Access Journals (Sweden)

    Frey Jürg E

    2010-02-01

    Full Text Available Abstract Background Microarrays are powerful tools for DNA-based molecular diagnostics and identification of pathogens. Most target a limited range of organisms and are based on only one or a very few genes for specific identification. Such microarrays are limited to organisms for which specific probes are available, and often have difficulty discriminating closely related taxa. We have developed an alternative broad-spectrum microarray that employs hybridisation fingerprints generated by high-density anonymous markers distributed over the entire genome for identification based on comparison to a reference database. Results A high-density microarray carrying 95,000 unique 13-mer probes was designed. Optimized methods were developed to deliver reproducible hybridisation patterns that enabled confident discrimination of bacteria at the species, subspecies, and strain levels. High correlation coefficients were achieved between replicates. A sub-selection of 12,071 probes, determined by ANOVA and class prediction analysis, enabled the discrimination of all samples in our panel. Mismatch probe hybridisation was observed but was found to have no effect on the discriminatory capacity of our system. Conclusions These results indicate the potential of our genome chip for reliable identification of a wide range of bacterial taxa at the subspecies level without laborious prior sequencing and probe design. With its high resolution capacity, our proof-of-principle chip demonstrates great potential as a tool for molecular diagnostics of broad taxonomic groups.

  17. Microarray-based RNA profiling of breast cancer

    DEFF Research Database (Denmark)

    Larsen, Martin J; Thomassen, Mads; Tan, Qihua

    2014-01-01

    analyzed the same 234 breast cancers on two different microarray platforms. One dataset contained known batch-effects associated with the fabrication procedure used. The aim was to assess the significance of correcting for systematic batch-effects when integrating data from different platforms. We here...

  18. DNA microarray analysis of fim mutations in Escherichia coli

    DEFF Research Database (Denmark)

    Schembri, Mark; Ussery, David; Workman, Christopher

    2002-01-01

    we have used DNA microarray analysis to examine the molecular events involved in response to fimbrial gene expression in E. coli K-12. Observed differential expression levels of the fim genes were in good agreement with our current knowledge of the stoichiometry of type I fimbriae. Changes in fim...

  19. Comparison of Comparative Genomic Hybridization Technologies across Microarray Platforms

    Science.gov (United States)

    In the 2007 Association of Biomolecular Resource Facilities (ABRF) Microarray Research Group (MARG) project, we analyzed HL-60 DNA with five platforms: Agilent, Affymetrix 500K, Affymetrix U133 Plus 2.0, Illumina, and RPCI 19K BAC arrays. Copy number variation (CNV) was analyzed ...

  20. The microarray detecting six fruit-tree viruses

    Czech Academy of Sciences Publication Activity Database

    Lenz, Ondřej; Petrzik, Karel; Špak, Josef

    2009-01-01

    Roč. 148, July (2009), s. 27 ISSN 1866-590X. [International Conference on Virus and other Graft Transmissible Diseases of Fruit Crops /21./. 05.07.2009-10.07.2009, Neustadt] R&D Projects: GA MŠk OC 853.001 Institutional research plan: CEZ:AV0Z50510513 Keywords : microarray * detection * virus Subject RIV: EE - Microbiology, Virology

  1. A Customized DNA Microarray for Microbial Source Tracking ...

    Science.gov (United States)

    It is estimated that more than 160, 000 miles of rivers and streams in the United States are impaired due to the presence of waterborne pathogens. These pathogens typically originate from human and other animal fecal pollution sources; therefore, a rapid microbial source tracking (MST) method is needed to facilitate water quality assessment and impaired water remediation. We report a novel qualitative DNA microarray technology consisting of 453 probes for the detection of general fecal and host-associated bacteria, viruses, antibiotic resistance, and other environmentally relevant genetic indicators. A novel data normalization and reduction approach is also presented to help alleviate false positives often associated with high-density microarray applications. To evaluate the performance of the approach, DNA and cDNA was isolated from swine, cattle, duck, goose and gull fecal reference samples, as well as soiled poultry liter and raw municipal sewage. Based on nonmetric multidimensional scaling analysis of results, findings suggest that the novel microarray approach may be useful for pathogen detection and identification of fecal contamination in recreational waters. The ability to simultaneously detect a large collection of environmentally important genetic indicators in a single test has the potential to provide water quality managers with a wide range of information in a short period of time. Future research is warranted to measure microarray performance i

  2. Low-density microarray technologies for rapid human norovirus genotyping

    Science.gov (United States)

    Human noroviruses cause up to 21 million cases of foodborne disease in the United States annually and are the most common cause of acute gastroenteritis in industrialized countries. To reduce the burden of foodborne disease associated with viruses, the use of low density DNA microarrays in conjuncti...

  3. Kernel Based Nonlinear Dimensionality Reduction and Classification for Genomic Microarray

    Directory of Open Access Journals (Sweden)

    Lan Shu

    2008-07-01

    Full Text Available Genomic microarrays are powerful research tools in bioinformatics and modern medicinal research because they enable massively-parallel assays and simultaneous monitoring of thousands of gene expression of biological samples. However, a simple microarray experiment often leads to very high-dimensional data and a huge amount of information, the vast amount of data challenges researchers into extracting the important features and reducing the high dimensionality. In this paper, a nonlinear dimensionality reduction kernel method based locally linear embedding(LLE is proposed, and fuzzy K-nearest neighbors algorithm which denoises datasets will be introduced as a replacement to the classical LLE’s KNN algorithm. In addition, kernel method based support vector machine (SVM will be used to classify genomic microarray data sets in this paper. We demonstrate the application of the techniques to two published DNA microarray data sets. The experimental results confirm the superiority and high success rates of the presented method.

  4. Towards a programmable magnetic bead microarray in a microfluidic channel

    DEFF Research Database (Denmark)

    Smistrup, Kristian; Bruus, Henrik; Hansen, Mikkel Fougt

    2007-01-01

    to use larger currents and obtain forces of longer range than from thin current lines at a given power limit. Guiding of magnetic beads in the hybrid magnetic separator and the construction of a programmable microarray of magnetic beads in the microfluidic channel by hydrodynamic focusing is presented....

  5. Development of DNA Microarrays for Metabolic Pathway and Bioprocess Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Gregory Stephanopoulos

    2004-07-31

    Transcriptional profiling experiments utilizing DNA microarrays to study the intracellular accumulation of PHB in Synechocystis has proved difficult in large part because strains that show significant differences in PHB which would justify global analysis of gene expression have not been isolated.

  6. Integrating Biological Perspectives:. a Quantum Leap for Microarray Expression Analysis

    Science.gov (United States)

    Wanke, Dierk; Kilian, Joachim; Bloss, Ulrich; Mangelsen, Elke; Supper, Jochen; Harter, Klaus; Berendzen, Kenneth W.

    2009-02-01

    Biologists and bioinformatic scientists cope with the analysis of transcript abundance and the extraction of meaningful information from microarray expression data. By exploiting biological information accessible in public databases, we try to extend our current knowledge over the plant model organism Arabidopsis thaliana. Here, we give two examples of increasing the quality of information gained from large scale expression experiments by the integration of microarray-unrelated biological information: First, we utilize Arabidopsis microarray data to demonstrate that expression profiles are usually conserved between orthologous genes of different organisms. In an initial step of the analysis, orthology has to be inferred unambiguously, which then allows comparison of expression profiles between orthologs. We make use of the publicly available microarray expression data of Arabidopsis and barley, Hordeum vulgare. We found a generally positive correlation in expression trajectories between true orthologs although both organisms are only distantly related in evolutionary time scale. Second, extracting clusters of co-regulated genes implies similarities in transcriptional regulation via similar cis-regulatory elements (CREs). Vice versa approaches, where co-regulated gene clusters are found by investigating on CREs were not successful in general. Nonetheless, in some cases the presence of CREs in a defined position, orientation or CRE-combinations is positively correlated with co-regulated gene clusters. Here, we make use of genes involved in the phenylpropanoid biosynthetic pathway, to give one positive example for this approach.

  7. Approximate sample size calculations with microarray data: an illustration

    NARCIS (Netherlands)

    Ferreira, José A.; Zwinderman, Aeilko

    2006-01-01

    We outline a method of sample size calculation in microarray experiments on the basis of pilot data and illustrate its practical application with both simulated and real data. The method was shown to be consistent (as the number of 'probed genes' tends to infinity) under general conditions in an

  8. Microarrays: Molecular allergology and nanotechnology for personalised medicine (II).

    Science.gov (United States)

    Lucas, J M

    2010-01-01

    Progress in nanotechnology and DNA recombination techniques have produced tools for the diagnosis and investigation of allergy at molecular level. The most advanced examples of such progress are the microarray techniques, which have been expanded not only in research in the field of proteomics but also in application to the clinical setting. Microarrays of allergic components offer results relating to hundreds of allergenic components in a single test, and using a small amount of serum which can be obtained from capillary blood. The availability of new molecules will allow the development of panels including new allergenic components and sources, which will require evaluation for clinical use. Their application opens the door to component-based diagnosis, to the holistic perception of sensitisation as represented by molecular allergy, and to patient-centred medical practice by allowing great diagnostic accuracy and the definition of individualised immunotherapy for each patient. The present article reviews the application of allergenic component microarrays to allergology for diagnosis, management in the form of specific immunotherapy, and epidemiological studies. A review is also made of the use of protein and gene microarray techniques in basic research and in allergological diseases. Lastly, an evaluation is made of the challenges we face in introducing such techniques to clinical practice, and of the future perspectives of this new technology. Copyright 2010 SEICAP. Published by Elsevier Espana. All rights reserved.

  9. Review Article: Current Knowledge on Microarray Technology - An ...

    African Journals Online (AJOL)

    The completion of whole genome sequencing projects has led to a rapid increase in the availability of genetic information. In the field of transcriptomics, the emergence of microarray-based technologies and the design of DNA biochips allow high-throughput studies of RNA expression in cell and tissue at a given moment.

  10. Microarray analysis of adipose tissue gene expression profiles ...

    Indian Academy of Sciences (India)

    Excessive accumulation of lipids in the adipose tissue is one of the main problems faced by the broiler industry nowadays. In order to visualize the mechanisms involved in the gene expression and regulation of lipid metabolism in adipose tissue, cDNA microarray containing 9 024 cDNA was used to construct gene ...

  11. Employing image processing techniques for cancer detection using microarray images.

    Science.gov (United States)

    Dehghan Khalilabad, Nastaran; Hassanpour, Hamid

    2017-02-01

    Microarray technology is a powerful genomic tool for simultaneously studying and analyzing the behavior of thousands of genes. The analysis of images obtained from this technology plays a critical role in the detection and treatment of diseases. The aim of the current study is to develop an automated system for analyzing data from microarray images in order to detect cancerous cases. The proposed system consists of three main phases, namely image processing, data mining, and the detection of the disease. The image processing phase performs operations such as refining image rotation, gridding (locating genes) and extracting raw data from images the data mining includes normalizing the extracted data and selecting the more effective genes. Finally, via the extracted data, cancerous cell is recognized. To evaluate the performance of the proposed system, microarray database is employed which includes Breast cancer, Myeloid Leukemia and Lymphomas from the Stanford Microarray Database. The results indicate that the proposed system is able to identify the type of cancer from the data set with an accuracy of 95.45%, 94.11%, and 100%, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. DNA microarray analysis of genes differentially expressed in ...

    Indian Academy of Sciences (India)

    These genes may play a major role in promoting excessive proliferation and accumulation of lipid droplets, which contribute to the development of obesity. By using microarray-based technology, we examined differential gene expression in early differentiated adipocytes and late differentiated adipocytes. Validated genes ...

  13. See what you eat--broad GMO screening with microarrays.

    Science.gov (United States)

    von Götz, Franz

    2010-03-01

    Despite the controversy of whether genetically modified organisms (GMOs) are beneficial or harmful for humans, animals, and/or ecosystems, the number of cultivated GMOs is increasing every year. Many countries and federations have implemented safety and surveillance systems for GMOs. Potent testing technologies need to be developed and implemented to monitor the increasing number of GMOs. First, these GMO tests need to be comprehensive, i.e., should detect all, or at least the most important, GMOs on the market. This type of GMO screening requires a high degree of parallel tests or multiplexing. To date, DNA microarrays have the highest number of multiplexing capabilities when nucleic acids are analyzed. This trend article focuses on the evolution of DNA microarrays for GMO testing. Over the last 7 years, combinations of multiplex PCR detection and microarray detection have been developed to qualitatively assess the presence of GMOs. One example is the commercially available DualChip GMO (Eppendorf, Germany; http://www.eppendorf-biochip.com), which is the only GMO screening system successfully validated in a multicenter study. With use of innovative amplification techniques, promising steps have recently been taken to make GMO detection with microarrays quantitative.

  14. Application of Microarray technology in research and diagnostics

    DEFF Research Database (Denmark)

    Helweg-Larsen, Rehannah Borup

    The overall purpose of this thesis is to evaluate the use of microarray analysis to investigate the transcriptome of human cancers and human follicular cells and define the correlation between expression of human genes and specific cancer types as well as the developmental competence of the oocyte...

  15. Exploiting fluorescence for multiplex immunoassays on protein microarrays

    Science.gov (United States)

    Herbáth, Melinda; Papp, Krisztián; Balogh, Andrea; Matkó, János; Prechl, József

    2014-09-01

    Protein microarray technology is becoming the method of choice for identifying protein interaction partners, detecting specific proteins, carbohydrates and lipids, or for characterizing protein interactions and serum antibodies in a massively parallel manner. Availability of the well-established instrumentation of DNA arrays and development of new fluorescent detection instruments promoted the spread of this technique. Fluorescent detection has the advantage of high sensitivity, specificity, simplicity and wide dynamic range required by most measurements. Fluorescence through specifically designed probes and an increasing variety of detection modes offers an excellent tool for such microarray platforms. Measuring for example the level of antibodies, their isotypes and/or antigen specificity simultaneously can offer more complex and comprehensive information about the investigated biological phenomenon, especially if we take into consideration that hundreds of samples can be measured in a single assay. Not only body fluids, but also cell lysates, extracted cellular components, and intact living cells can be analyzed on protein arrays for monitoring functional responses to printed samples on the surface. As a rapidly evolving area, protein microarray technology offers a great bulk of information and new depth of knowledge. These are the features that endow protein arrays with wide applicability and robust sample analyzing capability. On the whole, protein arrays are emerging new tools not just in proteomics, but glycomics, lipidomics, and are also important for immunological research. In this review we attempt to summarize the technical aspects of planar fluorescent microarray technology along with the description of its main immunological applications.

  16. Microarray expression profiling of human dental pulp from single subject.

    Science.gov (United States)

    Tete, Stefano; Mastrangelo, Filiberto; Scioletti, Anna Paola; Tranasi, Michelangelo; Raicu, Florina; Paolantonio, Michele; Stuppia, Liborio; Vinci, Raffaele; Gherlone, Enrico; Ciampoli, Cristian; Sberna, Maria Teresa; Conti, Pio

    2008-01-01

    Microarray is a recently developed simultaneous analysis of expression patterns of thousand of genes. The aim of this research was to evaluate the expression profile of human healthy dental pulp in order to find the presence of genes activated and encoding for proteins involved in the physiological process of human dental pulp. We report data obtained by analyzing expression profiles of human tooth pulp from single subjects, using an approach based on the amplification of the total RNA. Experiments were performed on a high-density array able to analyse about 21,000 oligonucleotide sequences of about 70 bases in duplicate, using an approach based on the amplification of the total RNA from the pulp of a single tooth. Obtained data were analyzed using the S.A.M. system (Significance Analysis of Microarray) and genes were merged according to their molecular functions and biological process by the Onto-Express software. The microarray analysis revealed 362 genes with specific pulp expression. Genes showing significant high expression were classified in genes involved in tooth development, protoncogenes, genes of collagen, DNAse, Metallopeptidases and Growth factors. We report a microarray analysis, carried out by extraction of total RNA from specimens of healthy human dental pulp tissue. This approach represents a powerful tool in the study of human normal and pathological pulp, allowing minimization of the genetic variability due to the pooling of samples from different individuals.

  17. Microarray analysis of the gene expression profile in triethylene ...

    African Journals Online (AJOL)

    Microarray analysis of the gene expression profile in triethylene glycol dimethacrylate-treated human dental pulp cells. ... Conclusions: Our results suggest that TEGDMA can change the many functions of hDPCs through large changes in gene expression levels and complex interactions with different signaling pathways.

  18. Evaluation of prognostic indicators using validated canine insulinoma tissue microarrays

    NARCIS (Netherlands)

    Buishand, Floryne O; Visser, Judith; Kik, Marja; Gröne, Andrea; Keesler, Rebekah I; Briaire-de Bruijn, Inge H; Kirpensteijn, Jolle

    Tissue microarray (TMA) technology allows analysis of multiple tumour samples simultaneously on a single slide. The aim of the present study was to develop and assess a TMA containing 32 primary canine insulinomas and 13 insulinoma metastases. The results of histopathological and immunohistochemical

  19. Microarrays for Universal Detection and Identification of Phytoplasmas

    DEFF Research Database (Denmark)

    Nicolaisen, Mogens; Nyskjold, Henriette; Bertaccini, Assunta

    2013-01-01

    Detection and identification of phytoplasmas is a laborious process often involving nested PCR followed by restriction enzyme analysis and fine-resolution gel electrophoresis. To improve throughput, other methods are needed. Microarray technology offers a generic assay that can potentially detect...

  20. High quality protein microarray using in situ protein purification

    Directory of Open Access Journals (Sweden)

    Fleischmann Robert D

    2009-08-01

    Full Text Available Abstract Background In the postgenomic era, high throughput protein expression and protein microarray technologies have progressed markedly permitting screening of therapeutic reagents and discovery of novel protein functions. Hexa-histidine is one of the most commonly used fusion tags for protein expression due to its small size and convenient purification via immobilized metal ion affinity chromatography (IMAC. This purification process has been adapted to the protein microarray format, but the quality of in situ His-tagged protein purification on slides has not been systematically evaluated. We established methods to determine the level of purification of such proteins on metal chelate-modified slide surfaces. Optimized in situ purification of His-tagged recombinant proteins has the potential to become the new gold standard for cost-effective generation of high-quality and high-density protein microarrays. Results Two slide surfaces were examined, chelated Cu2+ slides suspended on a polyethylene glycol (PEG coating and chelated Ni2+ slides immobilized on a support without PEG coating. Using PEG-coated chelated Cu2+ slides, consistently higher purities of recombinant proteins were measured. An optimized wash buffer (PBST composed of 10 mM phosphate buffer, 2.7 mM KCl, 140 mM NaCl and 0.05% Tween 20, pH 7.4, further improved protein purity levels. Using Escherichia coli cell lysates expressing 90 recombinant Streptococcus pneumoniae proteins, 73 proteins were successfully immobilized, and 66 proteins were in situ purified with greater than 90% purity. We identified several antigens among the in situ-purified proteins via assays with anti-S. pneumoniae rabbit antibodies and a human patient antiserum, as a demonstration project of large scale microarray-based immunoproteomics profiling. The methodology is compatible with higher throughput formats of in vivo protein expression, eliminates the need for resin-based purification and circumvents

  1. Workflows for microarray data processing in the Kepler environment

    Science.gov (United States)

    2012-01-01

    Background Microarray data analysis has been the subject of extensive and ongoing pipeline development due to its complexity, the availability of several options at each analysis step, and the development of new analysis demands, including integration with new data sources. Bioinformatics pipelines are usually custom built for different applications, making them typically difficult to modify, extend and repurpose. Scientific workflow systems are intended to address these issues by providing general-purpose frameworks in which to develop and execute such pipelines. The Kepler workflow environment is a well-established system under continual development that is employed in several areas of scientific research. Kepler provides a flexible graphical interface, featuring clear display of parameter values, for design and modification of workflows. It has capabilities for developing novel computational components in the R, Python, and Java programming languages, all of which are widely used for bioinformatics algorithm development, along with capabilities for invoking external applications and using web services. Results We developed a series of fully functional bioinformatics pipelines addressing common tasks in microarray processing in the Kepler workflow environment. These pipelines consist of a set of tools for GFF file processing of NimbleGen chromatin immunoprecipitation on microarray (ChIP-chip) datasets and more comprehensive workflows for Affymetrix gene expression microarray bioinformatics and basic primer design for PCR experiments, which are often used to validate microarray results. Although functional in themselves, these workflows can be easily customized, extended, or repurposed to match the needs of specific projects and are designed to be a toolkit and starting point for specific applications. These workflows illustrate a workflow programming paradigm focusing on local resources (programs and data) and therefore are close to traditional shell scripting or

  2. Workflows for microarray data processing in the Kepler environment

    Directory of Open Access Journals (Sweden)

    Stropp Thomas

    2012-05-01

    Full Text Available Abstract Background Microarray data analysis has been the subject of extensive and ongoing pipeline development due to its complexity, the availability of several options at each analysis step, and the development of new analysis demands, including integration with new data sources. Bioinformatics pipelines are usually custom built for different applications, making them typically difficult to modify, extend and repurpose. Scientific workflow systems are intended to address these issues by providing general-purpose frameworks in which to develop and execute such pipelines. The Kepler workflow environment is a well-established system under continual development that is employed in several areas of scientific research. Kepler provides a flexible graphical interface, featuring clear display of parameter values, for design and modification of workflows. It has capabilities for developing novel computational components in the R, Python, and Java programming languages, all of which are widely used for bioinformatics algorithm development, along with capabilities for invoking external applications and using web services. Results We developed a series of fully functional bioinformatics pipelines addressing common tasks in microarray processing in the Kepler workflow environment. These pipelines consist of a set of tools for GFF file processing of NimbleGen chromatin immunoprecipitation on microarray (ChIP-chip datasets and more comprehensive workflows for Affymetrix gene expression microarray bioinformatics and basic primer design for PCR experiments, which are often used to validate microarray results. Although functional in themselves, these workflows can be easily customized, extended, or repurposed to match the needs of specific projects and are designed to be a toolkit and starting point for specific applications. These workflows illustrate a workflow programming paradigm focusing on local resources (programs and data and therefore are close to

  3. Independent component analysis of Alzheimer's DNA microarray gene expression data

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    Vanderburg Charles R

    2009-01-01

    Full Text Available Abstract Background Gene microarray technology is an effective tool to investigate the simultaneous activity of multiple cellular pathways from hundreds to thousands of genes. However, because data in the colossal amounts generated by DNA microarray technology are usually complex, noisy, high-dimensional, and often hindered by low statistical power, their exploitation is difficult. To overcome these problems, two kinds of unsupervised analysis methods for microarray data: principal component analysis (PCA and independent component analysis (ICA have been developed to accomplish the task. PCA projects the data into a new space spanned by the principal components that are mutually orthonormal to each other. The constraint of mutual orthogonality and second-order statistics technique within PCA algorithms, however, may not be applied to the biological systems studied. Extracting and characterizing the most informative features of the biological signals, however, require higher-order statistics. Results ICA is one of the unsupervised algorithms that can extract higher-order statistical structures from data and has been applied to DNA microarray gene expression data analysis. We performed FastICA method on DNA microarray gene expression data from Alzheimer's disease (AD hippocampal tissue samples and consequential gene clustering. Experimental results showed that the ICA method can improve the clustering results of AD samples and identify significant genes. More than 50 significant genes with high expression levels in severe AD were extracted, representing immunity-related protein, metal-related protein, membrane protein, lipoprotein, neuropeptide, cytoskeleton protein, cellular binding protein, and ribosomal protein. Within the aforementioned categories, our method also found 37 significant genes with low expression levels. Moreover, it is worth noting that some oncogenes and phosphorylation-related proteins are expressed in low levels. In

  4. Computational biology of genome expression and regulation--a review of microarray bioinformatics.

    Science.gov (United States)

    Wang, Junbai

    2008-01-01

    Microarray technology is being used widely in various biomedical research areas; the corresponding microarray data analysis is an essential step toward the best utilizing of array technologies. Here we review two components of the microarray data analysis: a low level of microarray data analysis that emphasizes the designing, the quality control, and the preprocessing of microarray experiments, then a high level of microarray data analysis that focuses on the domain-specific microarray applications such as tumor classification, biomarker prediction, analyzing array CGH experiments, and reverse engineering of gene expression networks. Additionally, we will review the recent development of building a predictive model in genome expression and regulation studies. This review may help biologists grasp a basic knowledge of microarray bioinformatics as well as its potential impact on the future evolvement of biomedical research fields.

  5. Transcriptional Profiling of Hydrogen Production Metabolism of Rhodobacter capsulatus under Temperature Stress by Microarray Analysis

    Directory of Open Access Journals (Sweden)

    Muazzez Gürgan

    2015-06-01

    Full Text Available Biohydrogen is a clean and renewable form of hydrogen, which can be produced by photosynthetic bacteria in outdoor large-scale photobioreactors using sunlight. In this study, the transcriptional response of Rhodobacter capsulatus to cold (4 °C and heat (42 °C stress was studied using microarrays. Bacteria were grown in 30/2 acetate/glutamate medium at 30 °C for 48 h under continuous illumination. Then, cold and heat stresses were applied for two and six hours. Growth and hydrogen production were impaired under both stress conditions. Microarray chips for R. capsulatus were custom designed by Affymetrix (GeneChip®. TR_RCH2a520699F. The numbers of significantly changed genes were 328 and 293 out of 3685 genes under cold and heat stress, respectively. Our results indicate that temperature stress greatly affects the hydrogen production metabolisms of R. capsulatus. Specifically, the expression of genes that participate in nitrogen metabolism, photosynthesis and the electron transport system were induced by cold stress, while decreased by heat stress. Heat stress also resulted in down regulation of genes related to cell envelope, transporter and binding proteins. Transcriptome analysis and physiological results were consistent with each other. The results presented here may aid clarification of the genetic mechanisms for hydrogen production in purple non-sulfur (PNS bacteria under temperature stress.

  6. Washing scaling of GeneChip microarray expression

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    Krohn Knut

    2010-05-01

    Full Text Available Abstract Background Post-hybridization washing is an essential part of microarray experiments. Both the quality of the experimental washing protocol and adequate consideration of washing in intensity calibration ultimately affect the quality of the expression estimates extracted from the microarray intensities. Results We conducted experiments on GeneChip microarrays with altered protocols for washing, scanning and staining to study the probe-level intensity changes as a function of the number of washing cycles. For calibration and analysis of the intensity data we make use of the 'hook' method which allows intensity contributions due to non-specific and specific hybridization of perfect match (PM and mismatch (MM probes to be disentangled in a sequence specific manner. On average, washing according to the standard protocol removes about 90% of the non-specific background and about 30-50% and less than 10% of the specific targets from the MM and PM, respectively. Analysis of the washing kinetics shows that the signal-to-noise ratio doubles roughly every ten stringent washing cycles. Washing can be characterized by time-dependent rate constants which reflect the heterogeneous character of target binding to microarray probes. We propose an empirical washing function which estimates the survival of probe bound targets. It depends on the intensity contribution due to specific and non-specific hybridization per probe which can be estimated for each probe using existing methods. The washing function allows probe intensities to be calibrated for the effect of washing. On a relative scale, proper calibration for washing markedly increases expression measures, especially in the limit of small and large values. Conclusions Washing is among the factors which potentially distort expression measures. The proposed first-order correction method allows direct implementation in existing calibration algorithms for microarray data. We provide an experimental

  7. Recommendations for the use of microarrays in prenatal diagnosis.

    Science.gov (United States)

    Suela, Javier; López-Expósito, Isabel; Querejeta, María Eugenia; Martorell, Rosa; Cuatrecasas, Esther; Armengol, Lluis; Antolín, Eugenia; Domínguez Garrido, Elena; Trujillo-Tiebas, María José; Rosell, Jordi; García Planells, Javier; Cigudosa, Juan Cruz

    2017-04-07

    Microarray technology, recently implemented in international prenatal diagnosis systems, has become one of the main techniques in this field in terms of detection rate and objectivity of the results. This guideline attempts to provide background information on this technology, including technical and diagnostic aspects to be considered. Specifically, this guideline defines: the different prenatal sample types to be used, as well as their characteristics (chorionic villi samples, amniotic fluid, fetal cord blood or miscarriage tissue material); variant reporting policies (including variants of uncertain significance) to be considered in informed consents and prenatal microarray reports; microarray limitations inherent to the technique and which must be taken into account when recommending microarray testing for diagnosis; a detailed clinical algorithm recommending the use of microarray testing and its introduction into routine clinical practice within the context of other genetic tests, including pregnancies in families with a genetic history or specific syndrome suspicion, first trimester increased nuchal translucency or second trimester heart malformation and ultrasound findings not related to a known or specific syndrome. This guideline has been coordinated by the Spanish Association for Prenatal Diagnosis (AEDP, «Asociación Española de Diagnóstico Prenatal»), the Spanish Human Genetics Association (AEGH, «Asociación Española de Genética Humana») and the Spanish Society of Clinical Genetics and Dysmorphology (SEGCyD, «Sociedad Española de Genética Clínica y Dismorfología»). Copyright © 2017 Elsevier España, S.L.U. All rights reserved.

  8. Diagnostic utility of microarray testing in pregnancy loss.

    Science.gov (United States)

    Rosenfeld, J A; Tucker, M E; Escobar, L F; Neill, N J; Torchia, B S; McDaniel, L D; Schultz, R A; Chong, K; Chitayat, D

    2015-10-01

    To determine the frequency of clinically significant chromosomal abnormalities identified by chromosomal microarray in pregnancy losses at any gestational age and to compare microarray performance with that of traditional cytogenetic analysis when testing pregnancy losses. Among 535 fetal demise specimens of any gestational age, clinical microarray-based comparative genomic hybridization (aCGH) was performed successfully on 515, and a subset of 107 specimens underwent additional single nucleotide polymorphism (SNP) analysis. Overall, clinically significant abnormalities were identified in 12.8% (64/499) of specimens referred with normal or unknown karyotypes. Detection rates were significantly higher with earlier gestational age. In the subset with normal karyotype, clinically significant abnormalities were identified in 6.9% (20/288). This detection rate did not vary significantly with gestational age, suggesting that, unlike aneuploidy, the contribution of submicroscopic chromosomal abnormalities to fetal demise does not vary with gestational age. In the 107 specimens that underwent aCGH and SNP analysis, seven cases (6.5%) had abnormalities of potential clinical significance detected by the SNP component, including female triploidy. aCGH failed to yield fetal results in 8.3%, which is an improvement over traditional cytogenetic analysis of fetal demise specimens. Both the provision of results in cases in which karyotype fails and the detection of abnormalities in the presence of a normal karyotype demonstrate the increased diagnostic utility of microarray in pregnancy loss. Thus, chromosomal microarray testing is a preferable, robust method of analyzing cases of pregnancy loss to better delineate possible genetic etiologies, regardless of gestational age. Copyright © 2015 ISUOG. Published by John Wiley & Sons Ltd.

  9. Integrated olfactory receptor and microarray gene expression databases

    Directory of Open Access Journals (Sweden)

    Crasto Chiquito J

    2007-06-01

    Full Text Available Abstract Background Gene expression patterns of olfactory receptors (ORs are an important component of the signal encoding mechanism in the olfactory system since they determine the interactions between odorant ligands and sensory neurons. We have developed the Olfactory Receptor Microarray Database (ORMD to house OR gene expression data. ORMD is integrated with the Olfactory Receptor Database (ORDB, which is a key repository of OR gene information. Both databases aim to aid experimental research related to olfaction. Description ORMD is a Web-accessible database that provides a secure data repository for OR microarray experiments. It contains both publicly available and private data; accessing the latter requires authenticated login. The ORMD is designed to allow users to not only deposit gene expression data but also manage their projects/experiments. For example, contributors can choose whether to make their datasets public. For each experiment, users can download the raw data files and view and export the gene expression data. For each OR gene being probed in a microarray experiment, a hyperlink to that gene in ORDB provides access to genomic and proteomic information related to the corresponding olfactory receptor. Individual ORs archived in ORDB are also linked to ORMD, allowing users access to the related microarray gene expression data. Conclusion ORMD serves as a data repository and project management system. It facilitates the study of microarray experiments of gene expression in the olfactory system. In conjunction with ORDB, ORMD integrates gene expression data with the genomic and functional data of ORs, and is thus a useful resource for both olfactory researchers and the public.

  10. Translating microarray data for diagnostic testing in childhood leukaemia

    International Nuclear Information System (INIS)

    Hoffmann, Katrin; Firth, Martin J; Beesley, Alex H; Klerk, Nicholas H de; Kees, Ursula R

    2006-01-01

    Recent findings from microarray studies have raised the prospect of a standardized diagnostic gene expression platform to enhance accurate diagnosis and risk stratification in paediatric acute lymphoblastic leukaemia (ALL). However, the robustness as well as the format for such a diagnostic test remains to be determined. As a step towards clinical application of these findings, we have systematically analyzed a published ALL microarray data set using Robust Multi-array Analysis (RMA) and Random Forest (RF). We examined published microarray data from 104 ALL patients specimens, that represent six different subgroups defined by cytogenetic features and immunophenotypes. Using the decision-tree based supervised learning algorithm Random Forest (RF), we determined a small set of genes for optimal subgroup distinction and subsequently validated their predictive power in an independent patient cohort. We achieved very high overall ALL subgroup prediction accuracies of about 98%, and were able to verify the robustness of these genes in an independent panel of 68 specimens obtained from a different institution and processed in a different laboratory. Our study established that the selection of discriminating genes is strongly dependent on the analysis method. This may have profound implications for clinical use, particularly when the classifier is reduced to a small set of genes. We have demonstrated that as few as 26 genes yield accurate class prediction and importantly, almost 70% of these genes have not been previously identified as essential for class distinction of the six ALL subgroups. Our finding supports the feasibility of qRT-PCR technology for standardized diagnostic testing in paediatric ALL and should, in conjunction with conventional cytogenetics lead to a more accurate classification of the disease. In addition, we have demonstrated that microarray findings from one study can be confirmed in an independent study, using an entirely independent patient cohort

  11. Seeded Bayesian Networks: Constructing genetic networks from microarray data

    Directory of Open Access Journals (Sweden)

    Quackenbush John

    2008-07-01

    Full Text Available Abstract Background DNA microarrays and other genomics-inspired technologies provide large datasets that often include hidden patterns of correlation between genes reflecting the complex processes that underlie cellular metabolism and physiology. The challenge in analyzing large-scale expression data has been to extract biologically meaningful inferences regarding these processes – often represented as networks – in an environment where the datasets are often imperfect and biological noise can obscure the actual signal. Although many techniques have been developed in an attempt to address these issues, to date their ability to extract meaningful and predictive network relationships has been limited. Here we describe a method that draws on prior information about gene-gene interactions to infer biologically relevant pathways from microarray data. Our approach consists of using preliminary networks derived from the literature and/or protein-protein interaction data as seeds for a Bayesian network analysis of microarray results. Results Through a bootstrap analysis of gene expression data derived from a number of leukemia studies, we demonstrate that seeded Bayesian Networks have the ability to identify high-confidence gene-gene interactions which can then be validated by comparison to other sources of pathway data. Conclusion The use of network seeds greatly improves the ability of Bayesian Network analysis to learn gene interaction networks from gene expression data. We demonstrate that the use of seeds derived from the biomedical literature or high-throughput protein-protein interaction data, or the combination, provides improvement over a standard Bayesian Network analysis, allowing networks involving dynamic processes to be deduced from the static snapshots of biological systems that represent the most common source of microarray data. Software implementing these methods has been included in the widely used TM4 microarray analysis package.

  12. Microarray is an efficient tool for circRNA profiling.

    Science.gov (United States)

    Li, Shasha; Teng, Shuaishuai; Xu, Junquan; Su, Guannan; Zhang, Yu; Zhao, Jianqing; Zhang, Suwei; Wang, Haiyan; Qin, Wenyan; Lu, Zhi John; Guo, Yong; Zhu, Qianyong; Wang, Dong

    2018-02-03

    Circular RNAs (circRNAs) are emerging as a new class of endogenous and regulatory noncoding RNAs in latest years. With the widespread application of RNA sequencing (RNA-seq) technology and bioinformatics prediction, large numbers of circRNAs have been identified. However, at present, we lack a comprehensive characterization of all these circRNAs in interested samples. In this study, we integrated 87 935 circRNAs sequences that cover most of circRNAs identified till now represented in circBase to design microarray probes targeting back-splice site of each circRNA to profile expression of those circRNAs. By comparing the circRNA detection efficiency of RNA-seq with this circRNA microarray, we revealed that microarray is more efficient than RNA-seq for circRNA profiling. Then, we found ∼80 000 circRNAs were expressed in cervical tumors and matched normal tissues, and ∼25 000 of them were differently expressed. Notably, many of these circRNAs detected by this microarray can be validated by quantitative reverse transcription polymerase chain reaction (RT-qPCR) or RNA-seq. Strikingly, as many as ∼18 000 circRNAs could be robustly detected in cell-free plasma samples, and the expression of ∼2700 of them differed after surgery for tumor removal. Our findings provided a comprehensive and genome-wide characterization of circRNAs in paired normal tissues and tumors and plasma samples from multiple individuals. In addition, we also provide a rich resource with 41 microarray data sets and 10 RNA-seq data sets and strong evidences for circRNA expression in cervical cancer. In conclusion, circRNAs could be efficiently profiled by circRNA microarray to target their reported back-splice sites in interested samples. © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  13. Detection of analyte binding to microarrays using gold nanoparticle labels and a desktop scanner

    DEFF Research Database (Denmark)

    Han, Anpan; Dufva, Martin; Belleville, Erik

    2003-01-01

    six attomoles of antibody-gold conjugates. This detection system was used in a competitive immunoassay to measure the concentration of the pesticide metabolite 2,6-dichlorobenzamide (BAM) in water samples. The results showed that the gold labeled antibodies functioned comparably with a fluorescent......Microarray hybridization or antibody binding can be detected by many techniques, however, only a few are suitable for widespread use since many of these detection techniques rely on bulky and expensive instruments. Here, we describe the usefulness of a simple and inexpensive detection method based...... on gold nanoparticle labeled antibodies visualized by a commercial, office desktop flatbed scanner. Scanning electron microscopy studies showed that the signal from the flatbed scanner was proportional to the surface density of the bound antibody-gold conjugates, and that the flatbed scanner could detect...

  14. Fuzzy C-means method with empirical mode decomposition for clustering microarray data.

    Science.gov (United States)

    Wang, Yan-Fei; Yu, Zu-Guo; Anh, Vo

    2013-01-01

    Microarray techniques have revolutionised genomic research by making it possible to monitor the expression of thousands of genes in parallel. The Fuzzy C-Means (FCM) method is an efficient clustering approach devised for microarray data analysis. However, microarray data contains noise, which would affect clustering results. In this paper, we propose to combine the FCM method with the Empirical Mode Decomposition (EMD) for clustering microarray data to reduce the effect of the noise. The results suggest the clustering structures of denoised microarray data are more reasonable and genes have tighter association with their clusters than those using FCM only.

  15. A microarray gene expressions with classification using extreme learning machine

    Directory of Open Access Journals (Sweden)

    Yasodha M.

    2015-01-01

    Full Text Available In the present scenario, one of the dangerous disease is cancer. It spreads through blood or lymph to other location of the body, it is a set of cells display uncontrolled growth, attack and destroy nearby tissues, and occasionally metastasis. In cancer diagnosis and molecular biology, a utilized effective tool is DNA microarrays. The dominance of this technique is recognized, so several open doubt arise regarding proper examination of microarray data. In the field of medical sciences, multicategory cancer classification plays very important role. The need for cancer classification has become essential because the number of cancer sufferers is increasing. In this research work, to overcome problems of multicategory cancer classification an improved Extreme Learning Machine (ELM classifier is used. It rectify problems faced by iterative learning methods such as local minima, improper learning rate and over fitting and the training completes with high speed.

  16. Analyses of Aloe polysaccharides using carbohydrate microarray profiling

    DEFF Research Database (Denmark)

    Isager Ahl, Louise; Grace, Olwen M; Pedersen, Henriette Lodberg

    2018-01-01

    As the popularity of Aloe vera extracts continues to rise, a desire to fully understand the individual polymer components of the leaf mesophyll, their relation to one another and the effects they have on the human body are increasing. Polysaccharides present in the leaf mesophyll have been...... identified as the components responsible for the biological activities of Aloe vera, and they have been widely studied in the past decades. However, the commonly used methods do not provide the desired platform to conduct large comparative studies of polysaccharide compositions as most of them require...... a complete or near-complete fractionation of the polymers. The objective for this study was to assess whether carbohydrate microarrays could be used for the high-throughput analysis of cell wall polysaccharides in Aloe leaf mesophyll. The method we chose is known as Comprehensive Microarray Polymer Profiling...

  17. Low-Cost Peptide Microarrays for Mapping Continuous Antibody Epitopes.

    Science.gov (United States)

    McBride, Ryan; Head, Steven R; Ordoukhanian, Phillip; Law, Mansun

    2016-01-01

    With the increasing need for understanding antibody specificity in antibody and vaccine research, pepscan assays provide a rapid method for mapping and profiling antibody responses to continuous epitopes. We have developed a relatively low-cost method to generate peptide microarray slides for studying antibody binding. Using a setup of an IntavisAG MultiPep RS peptide synthesizer, a Digilab MicroGrid II 600 microarray printer robot, and an InnoScan 1100 AL scanner, the method allows the interrogation of up to 1536 overlapping, alanine-scanning, and mutant peptides derived from the target antigens. Each peptide is tagged with a polyethylene glycol aminooxy terminus to improve peptide solubility, orientation, and conjugation efficiency to the slide surface.

  18. Segmentation and intensity estimation for microarray images with saturated pixels

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    Yang Yan

    2011-11-01

    Full Text Available Abstract Background Microarray image analysis processes scanned digital images of hybridized arrays to produce the input spot-level data for downstream analysis, so it can have a potentially large impact on those and subsequent analysis. Signal saturation is an optical effect that occurs when some pixel values for highly expressed genes or peptides exceed the upper detection threshold of the scanner software (216 - 1 = 65, 535 for 16-bit images. In practice, spots with a sizable number of saturated pixels are often flagged and discarded. Alternatively, the saturated values are used without adjustments for estimating spot intensities. The resulting expression data tend to be biased downwards and can distort high-level analysis that relies on these data. Hence, it is crucial to effectively correct for signal saturation. Results We developed a flexible mixture model-based segmentation and spot intensity estimation procedure that accounts for saturated pixels by incorporating a censored component in the mixture model. As demonstrated with biological data and simulation, our method extends the dynamic range of expression data beyond the saturation threshold and is effective in correcting saturation-induced bias when the lost information is not tremendous. We further illustrate the impact of image processing on downstream classification, showing that the proposed method can increase diagnostic accuracy using data from a lymphoma cancer diagnosis study. Conclusions The presented method adjusts for signal saturation at the segmentation stage that identifies a pixel as part of the foreground, background or other. The cluster membership of a pixel can be altered versus treating saturated values as truly observed. Thus, the resulting spot intensity estimates may be more accurate than those obtained from existing methods that correct for saturation based on already segmented data. As a model-based segmentation method, our procedure is able to identify inner

  19. DNA microarray technique for detecting food-borne pathogens

    Directory of Open Access Journals (Sweden)

    Xing GAO

    2012-08-01

    Full Text Available Objective To study the application of DNA microarray technique for screening and identifying multiple food-borne pathogens. Methods The oligonucleotide probes were designed by Clustal X and Oligo 6.0 at the conserved regions of specific genes of multiple food-borne pathogens, and then were validated by bioinformatic analyses. The 5' end of each probe was modified by amino-group and 10 Poly-T, and the optimized probes were synthesized and spotted on aldehyde-coated slides. The bacteria DNA template incubated with Klenow enzyme was amplified by arbitrarily primed PCR, and PCR products incorporated into Aminoallyl-dUTP were coupled with fluorescent dye. After hybridization of the purified PCR products with DNA microarray, the hybridization image and fluorescence intensity analysis was acquired by ScanArray and GenePix Pro 5.1 software. A series of detection conditions such as arbitrarily primed PCR and microarray hybridization were optimized. The specificity of this approach was evaluated by 16 different bacteria DNA, and the sensitivity and reproducibility were verified by 4 food-borne pathogens DNA. The samples of multiple bacteria DNA and simulated water samples of Shigella dysenteriae were detected. Results Nine different food-borne bacteria were successfully discriminated under the same condition. The sensitivity of genomic DNA was 102 -103pg/ μl, and the coefficient of variation (CV of the reproducibility of assay was less than 15%. The corresponding specific hybridization maps of the multiple bacteria DNA samples were obtained, and the detection limit of simulated water sample of Shigella dysenteriae was 3.54×105cfu/ml. Conclusions The DNA microarray detection system based on arbitrarily primed PCR can be employed for effective detection of multiple food-borne pathogens, and this assay may offer a new method for high-throughput platform for detecting bacteria.

  20. Specific serology for emerging human coronaviruses by protein microarray

    NARCIS (Netherlands)

    Reusken, C.; Mou, H.; Godeke, G. J.; van der Hoek, L.; Meyer, B.; Müller, M. A.; Haagmans, B.; de Sousa, R.; Schuurman, N.; Dittmer, U.; Rottier, P.; Osterhaus, A.; Drosten, C.; Bosch, B. J.; Koopmans, M.

    2013-01-01

    We present a serological assay for the specific detection of IgM and IgG antibodies against the emerging human coronavirus hCoV-EMC and the SARS-CoV based on protein microarray technology. The assay uses the S1 receptor-binding subunit of the spike protein of hCoV-EMC and SARS-CoV as antigens. The

  1. Fish 'n' chips: the use of microarrays for aquatic toxicology.

    Science.gov (United States)

    Denslow, Nancy D; Garcia-Reyero, Natàlia; Barber, David S

    2007-03-01

    Gene expression analysis is changing the way that we look at toxicity, allowing toxicologists to perform parallel analyses of entire transcriptomes. While this technology is not as advanced in aquatic toxicology as it is for mammalian models, it has shown promise for determining modes of action, identifying biomarkers and developing "signatures" of chemicals that can be used for field and mixture studies. A major hurdle for the use of microarrays in aquatic toxicology is the lack of sequence information for non-model species. Custom arrays based on gene libraries enriched for genes that are expressed in response to specific contaminants have been used with excellent success for some non-model species, suggesting that this approach will work well for ecotoxicology and spurring on the sequencing of cDNA libraries for species of interest. New sequencing technology and development of repositories for gene expression data will accelerate the use of microarrays in aquatic toxicology. Notwithstanding the preliminary successes that have been achieved even with partial cDNA libraries printed on arrays, ecological samples present elevated challenges for this technology due to the high degree of variation of the samples. Furthermore, recent studies that show nonlinear toxic responses for ecological species underscore the necessity of establishing time and dose dependence of effects on gene expression and comparing these results with traditional markers of toxicity. To realize the full potential of microarrays, researchers must do the experiments required to bridge the gap between the 'omics' technologies and traditional toxicology to demonstrate that microarrays have predictive value in ecotoxicology.

  2. Microarrays of near-field optical probes with adjustable dimensions

    Energy Technology Data Exchange (ETDEWEB)

    Chovin, A. [Laboratoire d' Analyse Chimique par Reconnaissance Moleculaire, Universite Bordeaux I, ENSCPB, 16 avenue Pey-Berland, 33607 Pessac (France); Garrigue, P. [Laboratoire d' Analyse Chimique par Reconnaissance Moleculaire, Universite Bordeaux I, ENSCPB, 16 avenue Pey-Berland, 33607 Pessac (France); Pecastaings, G. [Centre de Recherche Paul Pascal-CNRS, 115 avenue du Dr Schweitzer, 33600 Pessac (France); Saadaoui, H. [Centre de Recherche Paul Pascal-CNRS, 115 avenue du Dr Schweitzer, 33600 Pessac (France); Manek-Hoenninger, I. [Centre Lasers Intenses et Applications, Universite Bordeaux I, 351 Cours de la Liberation, 33405 Talence (France)]. E-mail: manek@celia.u-bordeaux1.fr; Sojic, N. [Laboratoire d' Analyse Chimique par Reconnaissance Moleculaire, Universite Bordeaux I, ENSCPB, 16 avenue Pey-Berland, 33607 Pessac (France)]. E-mail: sojic@enscpb.fr

    2006-01-15

    We present the fabrication and the characterization of high-density microarrays comprising thousands of near-field optical probes. Two types of microarrays have been prepared by adapting the SNOM methodology: arrays of uncoated fiber nanotips (i.e. apertureless probes) and arrays of apertures with adjustable subwavelength dimensions. Such arrays were fabricated by retaining the coherent structure of monomode optical fiber bundles and therefore keeping their imaging properties. The size of the apertures in a microarray was tuned at the nanometer scale by modifying the fabrication parameters. Far-field characterization of these near-field probe arrays shows completely different behavior depending both on their architecture and on their characteristic size. The angular distribution of the far-field intensity transmitted through the aperture arrays is used to determine the optical size of such diffracting apertures. Aperture radii ranging from 95 to 250 nm were found in good agreement with SEM data. Furthermore, each nanoaperture of the array is optically independent in the far-field regime. Eventually, this study demonstrates potential applications of these imaging arrays as parallel near-field optical probes in both configurations (apertureless and with apertures)

  3. Microarrays of near-field optical probes with adjustable dimensions.

    Science.gov (United States)

    Chovin, A; Garrigue, P; Pecastaings, G; Saadaoui, H; Manek-Hönninger, I; Sojic, N

    2006-01-01

    We present the fabrication and the characterization of high-density microarrays comprising thousands of near-field optical probes. Two types of microarrays have been prepared by adapting the SNOM methodology: arrays of uncoated fiber nanotips (i.e. apertureless probes) and arrays of apertures with adjustable subwavelength dimensions. Such arrays were fabricated by retaining the coherent structure of monomode optical fiber bundles and therefore keeping their imaging properties. The size of the apertures in a microarray was tuned at the nanometer scale by modifying the fabrication parameters. Far-field characterization of these near-field probe arrays shows completely different behavior depending both on their architecture and on their characteristic size. The angular distribution of the far-field intensity transmitted through the aperture arrays is used to determine the optical size of such diffracting apertures. Aperture radii ranging from 95 to 250 nm were found in good agreement with SEM data. Furthermore, each nanoaperture of the array is optically independent in the far-field regime. Eventually, this study demonstrates potential applications of these imaging arrays as parallel near-field optical probes in both configurations (apertureless and with apertures).

  4. DNA Microarray Technologies: A Novel Approach to Geonomic Research

    Energy Technology Data Exchange (ETDEWEB)

    Hinman, R.; Thrall, B.; Wong, K,

    2002-01-01

    A cDNA microarray allows biologists to examine the expression of thousands of genes simultaneously. Researchers may analyze the complete transcriptional program of an organism in response to specific physiological or developmental conditions. By design, a cDNA microarray is an experiment with many variables and few controls. One question that inevitably arises when working with a cDNA microarray is data reproducibility. How easy is it to confirm mRNA expression patterns? In this paper, a case study involving the treatment of a murine macrophage RAW 264.7 cell line with tumor necrosis factor alpha (TNF) was used to obtain a rough estimate of data reproducibility. Two trials were examined and a list of genes displaying either a > 2-fold or > 4-fold increase in gene expression was compiled. Variations in signal mean ratios between the two slides were observed. We can assume that erring in reproducibility may be compensated by greater inductive levels of similar genes. Steps taken to obtain results included serum starvation of cells before treatment, tests of mRNA for quality/consistency, and data normalization.

  5. Microarray image segmentation using additional dye--an experimental study.

    Science.gov (United States)

    Gupta, Rashi; Ruosaari, Salla; Kulathinal, Sangita; Hollmén, Jaakko; Auvinen, Petri

    2007-01-01

    The DNA microarray technique allows monitoring the expression levels of thousands of genes simultaneously. A single DNA microarray experiment involves a number of error-prone manual and automated processes, which influence the results and have an impact on the subsequent stages of analysis. Typical problems of arrays are pinning errors while probe printing and the corruption of spots by noise patches. These errors should be detected at the time of image analysis in order to prevent the erroneous intensities from ending up in the analysis and inference stages. In this paper we introduce the concept (referred to as SybrSpot) of utilizing information provided by an additional dye, SYBR green RNA II, for segmentation of gene expression microarrays. Owing to the effective binding of the SYBR green RNA II to the array probes, an image with high signal-to-noise ratio is obtained. This image is used to learn about the spot quality and to flag spots which are not reliably hybridized and corrupted by noise. Further, we compare SybrSpot with GenePix and demonstrate that SybrSpot performs better than GenePix when flagging spots with no probes or weak probes. The code is available upon request to authors.

  6. Identification of Listeria species by microarray-based assay.

    Science.gov (United States)

    Volokhov, Dmitriy; Rasooly, Avraham; Chumakov, Konstantin; Chizhikov, Vladimir

    2002-12-01

    We have developed a rapid microarray-based assay for the reliable detection and discrimination of six species of the Listeria genus: L. monocytogenes, L. ivanovii, L. innocua, L. welshimeri, L. seeligeri, and L. grayi. The approach used in this study involves one-tube multiplex PCR amplification of six target bacterial virulence factor genes (iap, hly, inlB, plcA, plcB, and clpE), synthesis of fluorescently labeled single-stranded DNA, and hybridization to the multiple individual oligonucleotide probes specific for each Listeria species and immobilized on a glass surface. Results of the microarray analysis of 53 reference and clinical isolates of Listeria spp. demonstrated that this method allowed unambiguous identification of all six Listeria species based on sequence differences in the iap gene. Another virulence factor gene, hly, was used for detection and genotyping all L. monocytogenes, all L. ivanovii, and 8 of 11 L. seeligeri isolates. Other members of the genus Listeria and three L. seeligeri isolates did not contain the hly gene. There was complete agreement between the results of genotyping based on the hly and iap gene sequences. All L. monocytogenes isolates were found to be positive for the inlB, plcA, plcB, and clpE virulence genes specific only to this species. Our data on Listeria species analysis demonstrated that this microarray technique is a simple, rapid, and robust genotyping method that is also a potentially valuable tool for identification and characterization of bacterial pathogens in general.

  7. Sequence-dependent fluorescence of cyanine dyes on microarrays.

    Directory of Open Access Journals (Sweden)

    Christy Agbavwe

    Full Text Available Cy3 and Cy5 are among the most commonly used oligonucleotide labeling molecules. Studies of nucleic acid structure and dynamics use these dyes, and they are ubiquitous in microarray experiments. They are sensitive to their environment and have higher quantum yield when bound to DNA. The fluorescent intensity of terminal cyanine dyes is also known to be significantly dependent on the base sequence of the oligonucleotide. We have developed a very precise and high-throughput method to evaluate the sequence dependence of oligonucleotide labeling dyes using microarrays and have applied the method to Cy3 and Cy5. We used light-directed in-situ synthesis of terminally-labeled microarrays to determine the fluorescence intensity of each dye on all 1024 possible 5'-labeled 5-mers. Their intensity is sensitive to all five bases. Their fluorescence is higher with 5' guanines, and adenines in subsequent positions. Cytosine suppresses fluorescence. Intensity falls by half over the range of all 5-mers for Cy3, and two-thirds for Cy5. Labeling with 5'-biotin-streptavidin-Cy3/-Cy5 gives a completely different sequence dependence and greatly reduces fluorescence compared with direct terminal labeling.

  8. Instance-based concept learning from multiclass DNA microarray data

    Directory of Open Access Journals (Sweden)

    Dubitzky Werner

    2006-02-01

    Full Text Available Abstract Background Various statistical and machine learning methods have been successfully applied to the classification of DNA microarray data. Simple instance-based classifiers such as nearest neighbor (NN approaches perform remarkably well in comparison to more complex models, and are currently experiencing a renaissance in the analysis of data sets from biology and biotechnology. While binary classification of microarray data has been extensively investigated, studies involving multiclass data are rare. The question remains open whether there exists a significant difference in performance between NN approaches and more complex multiclass methods. Comparative studies in this field commonly assess different models based on their classification accuracy only; however, this approach lacks the rigor needed to draw reliable conclusions and is inadequate for testing the null hypothesis of equal performance. Comparing novel classification models to existing approaches requires focusing on the significance of differences in performance. Results We investigated the performance of instance-based classifiers, including a NN classifier able to assign a degree of class membership to each sample. This model alleviates a major problem of conventional instance-based learners, namely the lack of confidence values for predictions. The model translates the distances to the nearest neighbors into 'confidence scores'; the higher the confidence score, the closer is the considered instance to a pre-defined class. We applied the models to three real gene expression data sets and compared them with state-of-the-art methods for classifying microarray data of multiple classes, assessing performance using a statistical significance test that took into account the data resampling strategy. Simple NN classifiers performed as well as, or significantly better than, their more intricate competitors. Conclusion Given its highly intuitive underlying principles – simplicity

  9. Micro-Analyzer: automatic preprocessing of Affymetrix microarray data.

    Science.gov (United States)

    Guzzi, Pietro Hiram; Cannataro, Mario

    2013-08-01

    A current trend in genomics is the investigation of the cell mechanism using different technologies, in order to explain the relationship among genes, molecular processes and diseases. For instance, the combined use of gene-expression arrays and genomic arrays has been demonstrated as an effective instrument in clinical practice. Consequently, in a single experiment different kind of microarrays may be used, resulting in the production of different types of binary data (images and textual raw data). The analysis of microarray data requires an initial preprocessing phase, that makes raw data suitable for use on existing analysis platforms, such as the TIGR M4 (TM4) Suite. An additional challenge to be faced by emerging data analysis platforms is the ability to treat in a combined way those different microarray formats coupled with clinical data. In fact, resulting integrated data may include both numerical and symbolic data (e.g. gene expression and SNPs regarding molecular data), as well as temporal data (e.g. the response to a drug, time to progression and survival rate), regarding clinical data. Raw data preprocessing is a crucial step in analysis but is often performed in a manual and error prone way using different software tools. Thus novel, platform independent, and possibly open source tools enabling the semi-automatic preprocessing and annotation of different microarray data are needed. The paper presents Micro-Analyzer (Microarray Analyzer), a cross-platform tool for the automatic normalization, summarization and annotation of Affymetrix gene expression and SNP binary data. It represents the evolution of the μ-CS tool, extending the preprocessing to SNP arrays that were not allowed in μ-CS. The Micro-Analyzer is provided as a Java standalone tool and enables users to read, preprocess and analyse binary microarray data (gene expression and SNPs) by invoking TM4 platform. It avoids: (i) the manual invocation of external tools (e.g. the Affymetrix Power

  10. Supervised group Lasso with applications to microarray data analysis

    Directory of Open Access Journals (Sweden)

    Huang Jian

    2007-02-01

    Full Text Available Abstract Background A tremendous amount of efforts have been devoted to identifying genes for diagnosis and prognosis of diseases using microarray gene expression data. It has been demonstrated that gene expression data have cluster structure, where the clusters consist of co-regulated genes which tend to have coordinated functions. However, most available statistical methods for gene selection do not take into consideration the cluster structure. Results We propose a supervised group Lasso approach that takes into account the cluster structure in gene expression data for gene selection and predictive model building. For gene expression data without biological cluster information, we first divide genes into clusters using the K-means approach and determine the optimal number of clusters using the Gap method. The supervised group Lasso consists of two steps. In the first step, we identify important genes within each cluster using the Lasso method. In the second step, we select important clusters using the group Lasso. Tuning parameters are determined using V-fold cross validation at both steps to allow for further flexibility. Prediction performance is evaluated using leave-one-out cross validation. We apply the proposed method to disease classification and survival analysis with microarray data. Conclusion We analyze four microarray data sets using the proposed approach: two cancer data sets with binary cancer occurrence as outcomes and two lymphoma data sets with survival outcomes. The results show that the proposed approach is capable of identifying a small number of influential gene clusters and important genes within those clusters, and has better prediction performance than existing methods.

  11. Phenotype microarray profiling of the antibacterial activity of red cabbage

    Directory of Open Access Journals (Sweden)

    Hafidh RR

    2012-06-01

    Full Text Available Background: Functional food can be a potent source of wide array of biocomonents with antimicrobial activity. We investigated the antibacterial activity of red cabbage (RC extract on Gram negative and positive ATCC strains. Most intersting, we, for the first time, explored and analysed the complete phenotypic profile of RC-treated bacteria using Omnilog Phenotype Microarray. Results: This study revealed that the phenotype microarray (PM screen was a valuable tool in the search for compounds and their antibacterial mechanisms that can inhibit bacterial growth by affecting certain metabolic pathways. It was shown that RC exerted remarkable antibacterial effect on S. aureus and E. coli bacteria, and PM showed a wide range phenotypic profile of the exerted RC antibacterial activity. RC targeted the peptide, carbon, nutriontional assembly, and sulfur metbolic pathways altogether. The peptidoglycan synthesis pathway was inferred to be targeted by RC extract at a metabolic point different from other available cell wall-targeting drugs; these could be hot targets for the discovery of new therapy for many problematic microbes.Conclusions: Taken together, the phenotype microarray for functional food and medicinal plants can be a very useful tool for profiling their antimicrobial activity. Moreover, extracts of functional food can exert antibacterial activity by hitting a wide range of metabolic pathways, at the same time leading to very difficult condition for bacteria to rapidly develop resistance. Therefore, using functional foods or medicinal plants as such, or as extracts, can be superior on mono-targeting antibiotics if the optimal concentrations and conditions of these functional foods were sought.

  12. Up-to-Date Applications of Microarrays and Their Way to Commercialization

    Directory of Open Access Journals (Sweden)

    Sarah Schumacher

    2015-04-01

    Full Text Available This review addresses up-to-date applications of Protein Microarrays. Protein Microarrays play a significant role in basic research as well as in clinical applications and are applicable in a lot of fields, e.g., DNA, proteins and small molecules. Additionally they are on the way to enter clinics in routine diagnostics. Protein Microarrays can be powerful tools to improve healthcare. An overview of basic characteristics to mediate essential knowledge of this technique is given. To reach this goal, some challenges still have to be addressed. A few applications of Protein Microarrays in a medical context are shown. Finally, an outlook, where the potential of Protein Microarrays is depicted and speculations how the future of Protein Microarrays will look like are made.

  13. Handling gene redundancy in microarray data using Grey Relational Analysis.

    Science.gov (United States)

    Zhang, Li-Juan; Li, Zhou-Jun; Chen, Huo-Wang

    2008-01-01

    Gene selection is one of the important and frequently used techniques for microarray data classification. In this paper, we introduce a new metric to measure gene-class relevance and gene-gene redundancy. The new metric is based on Grey Relational Analysis (GRA), called Grey Relational Grade (GRG), and never used in gene selection before. Based on the GRG, we develop a new gene selection method, which uses GRG to group similar genes to clusters, and then select informative genes from each cluster to avoid redundancy. Experiments on public data sets demonstrate the effectiveness of the proposed method.

  14. A microarray analysis of two distinct lymphatic endothelial cell populations

    Directory of Open Access Journals (Sweden)

    Bernhard Schweighofer

    2015-06-01

    Full Text Available We have recently identified lymphatic endothelial cells (LECs to form two morphologically different populations, exhibiting significantly different surface protein expression levels of podoplanin, a major surface marker for this cell type. In vitro shockwave treatment (IVSWT of LECs resulted in enrichment of the podoplaninhigh cell population and was accompanied by markedly increased cell proliferation, as well as 2D and 3D migration. Gene expression profiles of these distinct populations were established using Affymetrix microarray analyses. Here we provide additional details about our dataset (NCBI GEO accession number GSE62510 and describe how we analyzed the data to identify differently expressed genes in these two LEC populations.

  15. Versatile High Throughput Microarray Analysis for Marine Glycobiology

    DEFF Research Database (Denmark)

    Asunción Salmeán, Armando

    to concept proof that is possible to use the Comprehensive Microarray Polymer Profiling (CoMPP) as a tool for other extracellular matrixes such as marine animals and not only for algal or plant cell walls. Thus, we discovered fucoidan and cellulose epitopes in several tissues of various marine animals from...... in cell development. Another part of this work focused in the development of a novel methodology for the discovery of unknown algal polysaccharides and characterization of carbohydrate binding proteins. Based on the coevolution between alga and marine saprophytic microorganisms, which use the algal...

  16. Towards a programmable magnetic bead microarray in a microfluidic channel

    International Nuclear Information System (INIS)

    Smistrup, Kristian; Bruus, Henrik; Hansen, Mikkel F.

    2007-01-01

    A new hybrid magnetic bead separator that combines an external magnetic field with 175 μm thick current lines buried in the back side of a silicon wafer is presented. A microfluidic channel was etched into the front side of the wafer. The large cross-section of the current lines makes it possible to use larger currents and obtain forces of longer range than from thin current lines at a given power limit. Guiding of magnetic beads in the hybrid magnetic separator and the construction of a programmable microarray of magnetic beads in the microfluidic channel by hydrodynamic focusing is presented

  17. Sequential interim analyses of survival data in DNA microarray experiments

    Directory of Open Access Journals (Sweden)

    Jung Klaus

    2011-04-01

    Full Text Available Abstract Background Discovery of biomarkers that are correlated with therapy response and thus with survival is an important goal of medical research on severe diseases, e.g. cancer. Frequently, microarray studies are performed to identify genes of which the expression levels in pretherapeutic tissue samples are correlated to survival times of patients. Typically, such a study can take several years until the full planned sample size is available. Therefore, interim analyses are desirable, offering the possibility of stopping the study earlier, or of performing additional laboratory experiments to validate the role of the detected genes. While many methods correcting the multiple testing bias introduced by interim analyses have been proposed for studies of one single feature, there are still open questions about interim analyses of multiple features, particularly of high-dimensional microarray data, where the number of features clearly exceeds the number of samples. Therefore, we examine false discovery rates and power rates in microarray experiments performed during interim analyses of survival studies. In addition, the early stopping based on interim results of such studies is evaluated. As stop criterion we employ the achieved average power rate, i.e. the proportion of detected true positives, for which a new estimator is derived and compared to existing estimators. Results In a simulation study, pre-specified levels of the false discovery rate are maintained in each interim analysis, where reduced levels as used in classical group sequential designs of one single feature are not necessary. Average power rates increase with each interim analysis, and many studies can be stopped prior to their planned end when a certain pre-specified power rate is achieved. The new estimator for the power rate slightly deviates from the true power rate but is comparable to other estimators. Conclusions Interim analyses of microarray experiments can provide

  18. High quality epoxysilane substrate for clinical multiplex serodiagnostic proteomic microarrays

    Science.gov (United States)

    Ewart, Tom; Carmichael, Stuart; Lea, Peter

    2005-09-01

    Polylysine and aminopropylsilane treated glass comprised the majority of substrates employed in first generation genetic microarray substrates. Second generation single stranded long oligo libraries with amino termini provided for controlled terminal specific attachment, and rationally designed unique sequence libraries with normalized melting temperatures. These libraries benefit from active covalent coupling surfaces such as Epoxysilane. The latter's oxime ring shows versatile reactivity with amino-, thiol- and hydroxyl- groups thus encompassing small molecule, oligo and proteomic microarray applications. Batch-to-batch production uniformity supports entry of the Epoxysilane process into clinical diagnostics. We carried out multiple print runs of 21 clinically relevant bacterial and viral antigens at optimized concentrations, plus human IgG and IgM standards in triplicate on multiple batches of Epoxysilane substrates. A set of 45 patient sera were assayed in a 35 minute protocol using 10 microliters per array in a capillary-fill format (15 minute serum incubation, wash, 15 minute incubation with Cy3-labeled anti-hIgG plus Dy647-labeled anti-hIgM, final wash). The LOD (3 SD above background) was better than 1 microgram/ml for IgG, and standard curves were regular and monotonically increasing over the range 0 to 1000 micrograms/ml. Ninety-five percent of the CVs for the standards were under 10%, and 90% percent of CVs for antigen responses were under 10% across all batches of Epoxysilane and print runs. In addition, where SDs are larger than expected, microarray images may be readily reviewed for quality control purposes and pin misprints quickly identified. In order to determine the influence of stirring on sensitivity and speed of the microarray assay, we printed 10 common ToRCH antigens (H. pylori, T. gondii, Rubella, Rubeola, C. trachomatis, Herpes 1 and 2, CMV, C. jejuni, and EBV) in Epoxysilane-activated slide-wells. Anti-IgG-Cy3 direct binding to printed Ig

  19. GenePublisher: automated analysis of DNA microarray data

    DEFF Research Database (Denmark)

    Knudsen, Steen; Workman, Christopher; Sicheritz-Ponten, T.

    2003-01-01

    , statistical analysis and visualization of the data. The results are run against databases of signal transduction pathways, metabolic pathways and promoter sequences in order to extract more information. The results of the entire analysis are summarized in report form and returned to the user.......GenePublisher, a system for automatic analysis of data from DNA microarray experiments, has been implemented with a web interface at http://www.cbs.dtu.dk/services/GenePublisher. Raw data are uploaded to the server together with aspecification of the data. The server performs normalization...

  20. DNA microarray analysis of fim mutations in Escherichia coli

    DEFF Research Database (Denmark)

    Schembri, Mark; Ussery, David; Workman, Christopher

    2002-01-01

    Bacterial adhesion is often mediated by complex polymeric surface structures referred to as fimbriae. Type I fimbriae of Escherichia coli represent the archetypical and best characterised fimbrial system. These adhesive organelles mediate binding to D-mannose and are directly associated...... we have used DNA microarray analysis to examine the molecular events involved in response to fimbrial gene expression in E. coli K-12. Observed differential expression levels of the fim genes were in good agreement with our current knowledge of the stoichiometry of type I fimbriae. Changes in fim...

  1. Identification of Listeria Species by Microarray-Based Assay

    OpenAIRE

    Volokhov, Dmitriy; Rasooly, Avraham; Chumakov, Konstantin; Chizhikov, Vladimir

    2002-01-01

    We have developed a rapid microarray-based assay for the reliable detection and discrimination of six species of the Listeria genus: L. monocytogenes, L. ivanovii, L. innocua, L. welshimeri, L. seeligeri, and L. grayi. The approach used in this study involves one-tube multiplex PCR amplification of six target bacterial virulence factor genes (iap, hly, inlB, plcA, plcB, and clpE), synthesis of fluorescently labeled single-stranded DNA, and hybridization to the multiple individual oligonucleot...

  2. Precision Profiling and Components of Variability Analysis for Affymetrix Microarray Assays Run in a Clinical Context

    OpenAIRE

    Daly, Thomas M.; Dumaual, Carmen M.; Dotson, Crystal A.; Farmen, Mark W.; Kadam, Sunil K.; Hockett, Richard D.

    2005-01-01

    Although gene expression profiling using microarray technology is widely used in research environments, adoption of microarray testing in clinical laboratories is currently limited. In an attempt to determine how such assays would perform in a clinical laboratory, we evaluated the analytical variability of Affymetrix microarray probesets using two generations of human Affymetrix chips (U95Av2 and U133A). The study was designed to mimic potential clinical applications by using multiple operato...

  3. Specificity of DNA microarray hybridization: characterization, effectors and approaches for data correction

    OpenAIRE

    Koltai, Hinanit; Weingarten-Baror, Carmiya

    2008-01-01

    Microarray-hybridization specificity is one of the main effectors of microarray result quality. In the present review, we suggest a definition for specificity that spans four hybridization levels, from the single probe to the microarray platform. For increased hybridization specificity, it is important to quantify the extent of the specificity at each of these levels, and correct the data accordingly. We outline possible effects of low hybridization specificity on the obtained results and lis...

  4. Gene expression risk signatures maintain prognostic power in multiple myeloma despite microarray probe set translation

    DEFF Research Database (Denmark)

    Hermansen, N E U; Borup, R; Andersen, M K

    2016-01-01

    INTRODUCTION: Gene expression profiling (GEP) risk models in multiple myeloma are based on 3'-end microarrays. We hypothesized that GEP risk signatures could retain prognostic power despite being translated and applied to whole-transcript microarray data. METHODS: We studied CD138-positive bone...... signatures maintain significant prognostic power in HDT myeloma patients. We suggest probe set matching for GEP risk signature translation as part of the efforts towards a microarray-independent GEP risk standard. (ClicinalTrials.gov identifier: NCT00639054)....

  5. [Software development in data analysis and mining for cDNA microarray].

    Science.gov (United States)

    Wu, Bin; Wang, Jianguo; Wang, Miqu

    2007-12-01

    Data analysis and mining is a key issue to microarray technology and is usually implemented through software development. This paper summarizes the state-of-art software development in cDNA microarray data analysis and mining. The updated software developments are discussed in three stages: data inquisition from cDNA microarray tests, statistical treatment of cDNA data and data mining from gene network.

  6. Validation of MIMGO: a method to identify differentially expressed GO terms in a microarray dataset

    OpenAIRE

    Yamada, Yoichi; Sawada, Hiroki; Hirotani, Ken-ichi; Oshima, Masanobu; Satou, Kenji

    2012-01-01

    Abstract Background We previously proposed an algorithm for the identification of GO terms that commonly annotate genes whose expression is upregulated or downregulated in some microarray data compared with in other microarray data. We call these “differentially expressed GO terms” and have named the algorithm “matrix-assisted identification method of differentially expressed GO terms” (MIMGO). MIMGO can also identify microarray data in which genes annotated with a differentially expressed GO...

  7. Data Integration for Microarrays: Enhanced Inference for Gene Regulatory Networks

    Directory of Open Access Journals (Sweden)

    Alina Sîrbu

    2015-05-01

    Full Text Available Microarray technologies have been the basis of numerous important findings regarding gene expression in the few last decades. Studies have generated large amounts of data describing various processes, which, due to the existence of public databases, are widely available for further analysis. Given their lower cost and higher maturity compared to newer sequencing technologies, these data continue to be produced, even though data quality has been the subject of some debate. However, given the large volume of data generated, integration can help overcome some issues related, e.g., to noise or reduced time resolution, while providing additional insight on features not directly addressed by sequencing methods. Here, we present an integration test case based on public Drosophila melanogaster datasets (gene expression, binding site affinities, known interactions. Using an evolutionary computation framework, we show how integration can enhance the ability to recover transcriptional gene regulatory networks from these data, as well as indicating which data types are more important for quantitative and qualitative network inference. Our results show a clear improvement in performance when multiple datasets are integrated, indicating that microarray data will remain a valuable and viable resource for some time to come.

  8. DNA Microarray Data Analysis: A Novel Biclustering Algorithm Approach

    Directory of Open Access Journals (Sweden)

    Tewfik Ahmed H

    2006-01-01

    Full Text Available Biclustering algorithms refer to a distinct class of clustering algorithms that perform simultaneous row-column clustering. Biclustering problems arise in DNA microarray data analysis, collaborative filtering, market research, information retrieval, text mining, electoral trends, exchange analysis, and so forth. When dealing with DNA microarray experimental data for example, the goal of biclustering algorithms is to find submatrices, that is, subgroups of genes and subgroups of conditions, where the genes exhibit highly correlated activities for every condition. In this study, we develop novel biclustering algorithms using basic linear algebra and arithmetic tools. The proposed biclustering algorithms can be used to search for all biclusters with constant values, biclusters with constant values on rows, biclusters with constant values on columns, and biclusters with coherent values from a set of data in a timely manner and without solving any optimization problem. We also show how one of the proposed biclustering algorithms can be adapted to identify biclusters with coherent evolution. The algorithms developed in this study discover all valid biclusters of each type, while almost all previous biclustering approaches will miss some.

  9. Multivariate analysis of microarray data: differential expression and differential connection.

    Science.gov (United States)

    Kiiveri, Harri T

    2011-02-01

    Typical analysis of microarray data ignores the correlation between gene expression values. In this paper we present a model for microarray data which specifically allows for correlation between genes. As a result we combine gene network ideas with linear models and differential expression. We use sparse inverse covariance matrices and their associated graphical representation to capture the notion of gene networks. An important issue in using these models is the identification of the pattern of zeroes in the inverse covariance matrix. The limitations of existing methods for doing this are discussed and we provide a workable solution for determining the zero pattern. We then consider a method for estimating the parameters in the inverse covariance matrix which is suitable for very high dimensional matrices. We also show how to construct multivariate tests of hypotheses. These overall multivariate tests can be broken down into two components, the first one being similar to tests for differential expression and the second involving the connections between genes. The methods in this paper enable the extraction of a wealth of information concerning the relationships between genes which can be conveniently represented in graphical form. Differentially expressed genes can be placed in the context of the gene network and places in the gene network where unusual or interesting patterns have emerged can be identified, leading to the formulation of hypotheses for future experimentation.

  10. Multivariate analysis of microarray data: differential expression and differential connection

    Directory of Open Access Journals (Sweden)

    Kiiveri Harri T

    2011-02-01

    Full Text Available Abstract Background Typical analysis of microarray data ignores the correlation between gene expression values. In this paper we present a model for microarray data which specifically allows for correlation between genes. As a result we combine gene network ideas with linear models and differential expression. Results We use sparse inverse covariance matrices and their associated graphical representation to capture the notion of gene networks. An important issue in using these models is the identification of the pattern of zeroes in the inverse covariance matrix. The limitations of existing methods for doing this are discussed and we provide a workable solution for determining the zero pattern. We then consider a method for estimating the parameters in the inverse covariance matrix which is suitable for very high dimensional matrices. We also show how to construct multivariate tests of hypotheses. These overall multivariate tests can be broken down into two components, the first one being similar to tests for differential expression and the second involving the connections between genes. Conclusion The methods in this paper enable the extraction of a wealth of information concerning the relationships between genes which can be conveniently represented in graphical form. Differentially expressed genes can be placed in the context of the gene network and places in the gene network where unusual or interesting patterns have emerged can be identified, leading to the formulation of hypotheses for future experimentation.

  11. Systematic interpretation of microarray data using experiment annotations

    Directory of Open Access Journals (Sweden)

    Frohme Marcus

    2006-12-01

    Full Text Available Abstract Background Up to now, microarray data are mostly assessed in context with only one or few parameters characterizing the experimental conditions under study. More explicit experiment annotations, however, are highly useful for interpreting microarray data, when available in a statistically accessible format. Results We provide means to preprocess these additional data, and to extract relevant traits corresponding to the transcription patterns under study. We found correspondence analysis particularly well-suited for mapping such extracted traits. It visualizes associations both among and between the traits, the hereby annotated experiments, and the genes, revealing how they are all interrelated. Here, we apply our methods to the systematic interpretation of radioactive (single channel and two-channel data, stemming from model organisms such as yeast and drosophila up to complex human cancer samples. Inclusion of technical parameters allows for identification of artifacts and flaws in experimental design. Conclusion Biological and clinical traits can act as landmarks in transcription space, systematically mapping the variance of large datasets from the predominant changes down toward intricate details.

  12. Biocompatible Hydrogels for Microarray Cell Printing and Encapsulation

    Directory of Open Access Journals (Sweden)

    Akshata Datar

    2015-10-01

    Full Text Available Conventional drug screening processes are a time-consuming and expensive endeavor, but highly rewarding when they are successful. To identify promising lead compounds, millions of compounds are traditionally screened against therapeutic targets on human cells grown on the surface of 96-wells. These two-dimensional (2D cell monolayers are physiologically irrelevant, thus, often providing false-positive or false-negative results, when compared to cells grown in three-dimensional (3D structures such as hydrogel droplets. However, 3D cell culture systems are not easily amenable to high-throughput screening (HTS, thus inherently low throughput, and requiring relatively large volume for cell-based assays. In addition, it is difficult to control cellular microenvironments and hard to obtain reliable cell images due to focus position and transparency issues. To overcome these problems, miniaturized 3D cell cultures in hydrogels were developed via cell printing techniques where cell spots in hydrogels can be arrayed on the surface of glass slides or plastic chips by microarray spotters and cultured in growth media to form cells encapsulated 3D droplets for various cell-based assays. These approaches can dramatically reduce assay volume, provide accurate control over cellular microenvironments, and allow us to obtain clear 3D cell images for high-content imaging (HCI. In this review, several hydrogels that are compatible to microarray printing robots are discussed for miniaturized 3D cell cultures.

  13. Biocompatible Hydrogels for Microarray Cell Printing and Encapsulation.

    Science.gov (United States)

    Datar, Akshata; Joshi, Pranav; Lee, Moo-Yeal

    2015-10-26

    Conventional drug screening processes are a time-consuming and expensive endeavor, but highly rewarding when they are successful. To identify promising lead compounds, millions of compounds are traditionally screened against therapeutic targets on human cells grown on the surface of 96-wells. These two-dimensional (2D) cell monolayers are physiologically irrelevant, thus, often providing false-positive or false-negative results, when compared to cells grown in three-dimensional (3D) structures such as hydrogel droplets. However, 3D cell culture systems are not easily amenable to high-throughput screening (HTS), thus inherently low throughput, and requiring relatively large volume for cell-based assays. In addition, it is difficult to control cellular microenvironments and hard to obtain reliable cell images due to focus position and transparency issues. To overcome these problems, miniaturized 3D cell cultures in hydrogels were developed via cell printing techniques where cell spots in hydrogels can be arrayed on the surface of glass slides or plastic chips by microarray spotters and cultured in growth media to form cells encapsulated 3D droplets for various cell-based assays. These approaches can dramatically reduce assay volume, provide accurate control over cellular microenvironments, and allow us to obtain clear 3D cell images for high-content imaging (HCI). In this review, several hydrogels that are compatible to microarray printing robots are discussed for miniaturized 3D cell cultures.

  14. Tissue microarray construction for salivary gland tumors study

    Science.gov (United States)

    Paiva-Fonseca, Felipe; de-Almeida, Oslei P.; Ayroza-Rangel, Ana L C.

    2013-01-01

    Objective: To describe and discuss the design, building and usefulness of tissue microarray (TMA) blocks for the study of salivary gland tumors (SGTs). Study Design: Two hundred thirty-eight formalin-fixed, paraffin-embedded SGTs were arranged in blocks of TMA using a manual tissue arrayer. Three representative cores of 1.0, 2.0 or 3.0mm were taken from each original block and their characteristics were analyzed and described. Results: It was created 12 TMA blocks that presented highly representative neoplastic cylinders. However, those neoplasias rich in cystic spaces such as mucoepidermoid carcinoma and Warthin tumor presented more difficulties to be sampled, as the neoplastic tissue available was scarce. Tissue damage and loss during TMA construction was estimated as 3.7%. Conclusion: Representative areas of SGTs, with relatively small loss of tissue, can be obtained with the construction of TMA blocks for molecular studies. However, tumors rich in cystic spaces present more difficulties to be adequately sampled. Key words:Tissue microarray, tma, salivary gland tumors, immunohistochemistry. PMID:22926480

  15. Confidence levels for the comparison of microarray experiments.

    Science.gov (United States)

    Shedden, Kerby

    2004-01-01

    A common experimental strategy utilizing microarrays is to develop a signature of genes responding to some treatment in a model system, and then ask whether the same genes respond in an analogous way in a more natural and uncontrolled environment. In statistical terms, the question posed is whether genes score similarly on some statistical test in two independent data sets. Approaches to this problem ignoring gene/gene correlations common to all microarray data sets are known to give overstated statistical confidence levels. Permutation approaches have been proposed to give more accurate confidence levels, but can not be applied when sample sizes are small. Here we argue that the product moment correlation between test statistics in the two experiments is an ideal measure for summarizing concordance between the experiments, as confidence levels accounting for intergene correlations depend only on a single number - the average squared correlation between gene pairs in the data set. The resulting null standard deviation is shown to vary by less than a factor of two over six distinct experimental data sets, suggesting that a universal constant may be used for this quantity. We show how a hidden assumption of the permutation approach may lead to incorrect p-values, while the analytic approach presented here is shown to be resistant to this assumption.

  16. Genetic Programming Based Ensemble System for Microarray Data Classification

    Directory of Open Access Journals (Sweden)

    Kun-Hong Liu

    2015-01-01

    Full Text Available Recently, more and more machine learning techniques have been applied to microarray data analysis. The aim of this study is to propose a genetic programming (GP based new ensemble system (named GPES, which can be used to effectively classify different types of cancers. Decision trees are deployed as base classifiers in this ensemble framework with three operators: Min, Max, and Average. Each individual of the GP is an ensemble system, and they become more and more accurate in the evolutionary process. The feature selection technique and balanced subsampling technique are applied to increase the diversity in each ensemble system. The final ensemble committee is selected by a forward search algorithm, which is shown to be capable of fitting data automatically. The performance of GPES is evaluated using five binary class and six multiclass microarray datasets, and results show that the algorithm can achieve better results in most cases compared with some other ensemble systems. By using elaborate base classifiers or applying other sampling techniques, the performance of GPES may be further improved.

  17. Microarray Dot Electrodes Utilizing Dielectrophoresis for Cell Characterization

    Directory of Open Access Journals (Sweden)

    Fatimah Ibrahim

    2013-07-01

    Full Text Available During the last three decades; dielectrophoresis (DEP has become a vital tool for cell manipulation and characterization due to its non-invasiveness. It is very useful in the trend towards point-of-care systems. Currently, most efforts are focused on using DEP in biomedical applications, such as the spatial manipulation of cells, the selective separation or enrichment of target cells, high-throughput molecular screening, biosensors and immunoassays. A significant amount of research on DEP has produced a wide range of microelectrode configurations. In this paper; we describe the microarray dot electrode, a promising electrode geometry to characterize and manipulate cells via DEP. The advantages offered by this type of microelectrode are also reviewed. The protocol for fabricating planar microelectrodes using photolithography is documented to demonstrate the fast and cost-effective fabrication process. Additionally; different state-of-the-art Lab-on-a-Chip (LOC devices that have been proposed for DEP applications in the literature are reviewed. We also present our recently designed LOC device, which uses an improved microarray dot electrode configuration to address the challenges facing other devices. This type of LOC system has the capability to boost the implementation of DEP technology in practical settings such as clinical cell sorting, infection diagnosis, and enrichment of particle populations for drug development.

  18. Variance estimation in the analysis of microarray data

    KAUST Repository

    Wang, Yuedong

    2009-04-01

    Microarrays are one of the most widely used high throughput technologies. One of the main problems in the area is that conventional estimates of the variances that are required in the t-statistic and other statistics are unreliable owing to the small number of replications. Various methods have been proposed in the literature to overcome this lack of degrees of freedom problem. In this context, it is commonly observed that the variance increases proportionally with the intensity level, which has led many researchers to assume that the variance is a function of the mean. Here we concentrate on estimation of the variance as a function of an unknown mean in two models: the constant coefficient of variation model and the quadratic variance-mean model. Because the means are unknown and estimated with few degrees of freedom, naive methods that use the sample mean in place of the true mean are generally biased because of the errors-in-variables phenomenon. We propose three methods for overcoming this bias. The first two are variations on the theme of the so-called heteroscedastic simulation-extrapolation estimator, modified to estimate the variance function consistently. The third class of estimators is entirely different, being based on semiparametric information calculations. Simulations show the power of our methods and their lack of bias compared with the naive method that ignores the measurement error. The methodology is illustrated by using microarray data from leukaemia patients.

  19. Characterization of adjacent breast tumors using oligonucleotide microarrays

    International Nuclear Information System (INIS)

    Unger, Meredith A; Rishi, Mazhar; Clemmer, Virginia B; Hartman, Jennifer L; Keiper, Elizabeth A; Greshock, Joel D; Chodosh, Lewis A; Liebman, Michael N; Weber, Barbara L

    2001-01-01

    Current methodology often cannot distinguish second primary breast cancers from multifocal disease, a potentially important distinction for clinical management. In the present study we evaluated the use of oligonucleotide-based microarray analysis in determining the clonality of tumors by comparing gene expression profiles. Total RNA was extracted from two tumors with no apparent physical connection that were located in the right breast of an 87-year-old woman diagnosed with invasive ductal carcinoma (IDC). The RNA was hybridized to the Affymetrix Human Genome U95A Gene Chip ® (12,500 known human genes) and analyzed using the Gene Chip Analysis Suite ® 3.3 (Affymetrix, Inc, Santa Clara, CA, USA) and JMPIN ® 3.2.6 (SAS Institute, Inc, Cary, NC, USA). Gene expression profiles of tumors from five additional patients were compared in order to evaluate the heterogeneity in gene expression between tumors with similar clinical characteristics. The adjacent breast tumors had a pairwise correlation coefficient of 0.987, and were essentially indistinguishable by microarray analysis. Analysis of gene expression profiles from different individuals, however, generated a pairwise correlation coefficient of 0.710. Transcriptional profiling may be a useful diagnostic tool for determining tumor clonality and heterogeneity, and may ultimately impact on therapeutic decision making

  20. Harshlight: a "corrective make-up" program for microarray chips

    Directory of Open Access Journals (Sweden)

    Wittkowski Knut M

    2005-12-01

    Full Text Available Abstract Background Microscopists are familiar with many blemishes that fluorescence images can have due to dust and debris, glass flaws, uneven distribution of fluids or surface coatings, etc. Microarray scans do show similar artifacts, which might affect subsequent analysis. Although all but the starkest blemishes are hard to find by the unaided eye, particularly in high-density oligonucleotide arrays (HDONAs, few tools are available to help with the detection of those defects. Results We develop a novel tool, Harshlight, for the automatic detection and masking of blemishes in HDONA microarray chips. Harshlight uses a combination of statistic and image processing methods to identify three different types of defects: localized blemishes affecting a few probes, diffuse defects affecting larger areas, and extended defects which may invalidate an entire chip. Conclusion We demonstrate the use of Harshlight can materially improve analysis of HDONA chips, especially for experiments with subtle changes between samples. For the widely used MAS5 algorithm, we show that compact blemishes cause an average of 8 gene expression values per chip to change by more than 50%, two of them by more than twofold; our masking algorithm restores about two thirds of this damage. Large-scale artifacts are successfully detected and eliminated.

  1. Electronics and electronic systems

    CERN Document Server

    Olsen, George H

    1987-01-01

    Electronics and Electronic Systems explores the significant developments in the field of electronics and electronic devices. This book is organized into three parts encompassing 11 chapters that discuss the fundamental circuit theory and the principles of analog and digital electronics. This book deals first with the passive components of electronic systems, such as resistors, capacitors, and inductors. These topics are followed by a discussion on the analysis of electronic circuits, which involves three ways, namely, the actual circuit, graphical techniques, and rule of thumb. The remaining p

  2. Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes

    Directory of Open Access Journals (Sweden)

    Eils Roland

    2005-11-01

    Full Text Available Abstract Background The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer studies. Although similar questions for the same type of cancer are addressed in these different studies, a comparative analysis of their results is hampered by the use of heterogeneous microarray platforms and analysis methods. Results In contrast to a meta-analysis approach where results of different studies are combined on an interpretative level, we investigate here how to directly integrate raw microarray data from different studies for the purpose of supervised classification analysis. We use median rank scores and quantile discretization to derive numerically comparable measures of gene expression from different platforms. These transformed data are then used for training of classifiers based on support vector machines. We apply this approach to six publicly available cancer microarray gene expression data sets, which consist of three pairs of studies, each examining the same type of cancer, i.e. breast cancer, prostate cancer or acute myeloid leukemia. For each pair, one study was performed by means of cDNA microarrays and the other by means of oligonucleotide microarrays. In each pair, high classification accuracies (> 85% were achieved with training and testing on data instances randomly chosen from both data sets in a cross-validation analysis. To exemplify the potential of this cross-platform classification analysis, we use two leukemia microarray data sets to show that important genes with regard to the biology of leukemia are selected in an integrated analysis, which are missed in either single-set analysis. Conclusion Cross-platform classification of multiple cancer microarray data sets yields discriminative gene expression signatures that are found and validated on a large number of microarray samples, generated by different laboratories and

  3. A statistical framework for differential network analysis from microarray data

    Directory of Open Access Journals (Sweden)

    Datta Somnath

    2010-02-01

    Full Text Available Abstract Background It has been long well known that genes do not act alone; rather groups of genes act in consort during a biological process. Consequently, the expression levels of genes are dependent on each other. Experimental techniques to detect such interacting pairs of genes have been in place for quite some time. With the advent of microarray technology, newer computational techniques to detect such interaction or association between gene expressions are being proposed which lead to an association network. While most microarray analyses look for genes that are differentially expressed, it is of potentially greater significance to identify how entire association network structures change between two or more biological settings, say normal versus diseased cell types. Results We provide a recipe for conducting a differential analysis of networks constructed from microarray data under two experimental settings. At the core of our approach lies a connectivity score that represents the strength of genetic association or interaction between two genes. We use this score to propose formal statistical tests for each of following queries: (i whether the overall modular structures of the two networks are different, (ii whether the connectivity of a particular set of "interesting genes" has changed between the two networks, and (iii whether the connectivity of a given single gene has changed between the two networks. A number of examples of this score is provided. We carried out our method on two types of simulated data: Gaussian networks and networks based on differential equations. We show that, for appropriate choices of the connectivity scores and tuning parameters, our method works well on simulated data. We also analyze a real data set involving normal versus heavy mice and identify an interesting set of genes that may play key roles in obesity. Conclusions Examining changes in network structure can provide valuable information about the

  4. Sample size for detecting differentially expressed genes in microarray experiments

    Directory of Open Access Journals (Sweden)

    Li Jiangning

    2004-11-01

    Full Text Available Abstract Background Microarray experiments are often performed with a small number of biological replicates, resulting in low statistical power for detecting differentially expressed genes and concomitant high false positive rates. While increasing sample size can increase statistical power and decrease error rates, with too many samples, valuable resources are not used efficiently. The issue of how many replicates are required in a typical experimental system needs to be addressed. Of particular interest is the difference in required sample sizes for similar experiments in inbred vs. outbred populations (e.g. mouse and rat vs. human. Results We hypothesize that if all other factors (assay protocol, microarray platform, data pre-processing were equal, fewer individuals would be needed for the same statistical power using inbred animals as opposed to unrelated human subjects, as genetic effects on gene expression will be removed in the inbred populations. We apply the same normalization algorithm and estimate the variance of gene expression for a variety of cDNA data sets (humans, inbred mice and rats comparing two conditions. Using one sample, paired sample or two independent sample t-tests, we calculate the sample sizes required to detect a 1.5-, 2-, and 4-fold changes in expression level as a function of false positive rate, power and percentage of genes that have a standard deviation below a given percentile. Conclusions Factors that affect power and sample size calculations include variability of the population, the desired detectable differences, the power to detect the differences, and an acceptable error rate. In addition, experimental design, technical variability and data pre-processing play a role in the power of the statistical tests in microarrays. We show that the number of samples required for detecting a 2-fold change with 90% probability and a p-value of 0.01 in humans is much larger than the number of samples commonly used in

  5. A novel multifunctional oligonucleotide microarray for Toxoplasma gondii

    Directory of Open Access Journals (Sweden)

    Chen Feng

    2010-10-01

    Full Text Available Abstract Background Microarrays are invaluable tools for genome interrogation, SNP detection, and expression analysis, among other applications. Such broad capabilities would be of value to many pathogen research communities, although the development and use of genome-scale microarrays is often a costly undertaking. Therefore, effective methods for reducing unnecessary probes while maintaining or expanding functionality would be relevant to many investigators. Results Taking advantage of available genome sequences and annotation for Toxoplasma gondii (a pathogenic parasite responsible for illness in immunocompromised individuals and Plasmodium falciparum (a related parasite responsible for severe human malaria, we designed a single oligonucleotide microarray capable of supporting a wide range of applications at relatively low cost, including genome-wide expression profiling for Toxoplasma, and single-nucleotide polymorphism (SNP-based genotyping of both T. gondii and P. falciparum. Expression profiling of the three clonotypic lineages dominating T. gondii populations in North America and Europe provides a first comprehensive view of the parasite transcriptome, revealing that ~49% of all annotated genes are expressed in parasite tachyzoites (the acutely lytic stage responsible for pathogenesis and 26% of genes are differentially expressed among strains. A novel design utilizing few probes provided high confidence genotyping, used here to resolve recombination points in the clonal progeny of sexual crosses. Recent sequencing of additional T. gondii isolates identifies >620 K new SNPs, including ~11 K that intersect with expression profiling probes, yielding additional markers for genotyping studies, and further validating the utility of a combined expression profiling/genotyping array design. Additional applications facilitating SNP and transcript discovery, alternative statistical methods for quantifying gene expression, etc. are also pursued at

  6. A salmonid EST genomic study: genes, duplications, phylogeny and microarrays

    Directory of Open Access Journals (Sweden)

    Brahmbhatt Sonal

    2008-11-01

    Full Text Available Abstract Background Salmonids are of interest because of their relatively recent genome duplication, and their extensive use in wild fisheries and aquaculture. A comprehensive gene list and a comparison of genes in some of the different species provide valuable genomic information for one of the most widely studied groups of fish. Results 298,304 expressed sequence tags (ESTs from Atlantic salmon (69% of the total, 11,664 chinook, 10,813 sockeye, 10,051 brook trout, 10,975 grayling, 8,630 lake whitefish, and 3,624 northern pike ESTs were obtained in this study and have been deposited into the public databases. Contigs were built and putative full-length Atlantic salmon clones have been identified. A database containing ESTs, assemblies, consensus sequences, open reading frames, gene predictions and putative annotation is available. The overall similarity between Atlantic salmon ESTs and those of rainbow trout, chinook, sockeye, brook trout, grayling, lake whitefish, northern pike and rainbow smelt is 93.4, 94.2, 94.6, 94.4, 92.5, 91.7, 89.6, and 86.2% respectively. An analysis of 78 transcript sets show Salmo as a sister group to Oncorhynchus and Salvelinus within Salmoninae, and Thymallinae as a sister group to Salmoninae and Coregoninae within Salmonidae. Extensive gene duplication is consistent with a genome duplication in the common ancestor of salmonids. Using all of the available EST data, a new expanded salmonid cDNA microarray of 32,000 features was created. Cross-species hybridizations to this cDNA microarray indicate that this resource will be useful for studies of all 68 salmonid species. Conclusion An extensive collection and analysis of salmonid RNA putative transcripts indicate that Pacific salmon, Atlantic salmon and charr are 94–96% similar while the more distant whitefish, grayling, pike and smelt are 93, 92, 89 and 86% similar to salmon. The salmonid transcriptome reveals a complex history of gene duplication that is

  7. Characterization of probiotic Escherichia coli isolates with a novel pan-genome microarray

    DEFF Research Database (Denmark)

    Willenbrock, Hanni; Hallin, Peter Fischer; Wassenaar, Trudy

    2007-01-01

    Background: Microarrays have recently emerged as a novel procedure to evaluate the genetic content of bacterial species. So far, microarrays have mostly covered single or few strains from the same species. However, with cheaper high-throughput sequencing techniques emerging, multiple strains of t...

  8. A Xenopus tropicalis oligonucleotide microarray works across species using RNA from Xenopus laevis.

    Science.gov (United States)

    Chalmers, Andrew D; Goldstone, Kim; Smith, James C; Gilchrist, Mike; Amaya, Enrique; Papalopulu, Nancy

    2005-03-01

    Microarrays have great potential for the study of developmental biology. As a model system Xenopus is well suited for making the most of this potential. However, Xenopus laevis has undergone a genome wide duplication meaning that most genes are represented by two paralogues. This causes a number of problems. Most importantly the presence of duplicated genes mean that a X. laevis microarray will have less or even half the coverage of a similar sized microarray from the closely related but diploid frog Xenopus tropicalis. However, to date, X. laevis is the most commonly used amphibian system for experimental embryology. Therefore, we have tested if a microarray based on sequences from X. tropicalis will work across species using RNA from X. laevis. We produced a pilot oligonucleotide microarray based on sequences from X. tropicalis. The microarray was used to identify genes whose expression levels changed during early X. tropicalis development. The same assay was then carried out using RNA from X. laevis. The cross species experiments gave similar results to those using X. tropicalis RNA. This was true at the whole microarray level and for individual genes, with most genes giving similar results using RNA from X. laevis and X. tropicalis. Furthermore, the overlap in genes identified between a X. laevis and a X. tropicalis set of experiments was only 12% less than the overlap between two sets of X. tropicalis experiments. Therefore researchers can work with X. laevis and still make use of the advantages offered by X. tropicalis microarrays.

  9. Gene Expression Browser: Large-Scale and Cross-Experiment Microarray Data Management, Search & Visualization

    Science.gov (United States)

    The amount of microarray gene expression data in public repositories has been increasing exponentially for the last couple of decades. High-throughput microarray data integration and analysis has become a critical step in exploring the large amount of expression data for biological discovery. Howeve...

  10. Assessing the utility of confirmatory studies following identification of large-scale genomic imbalances by microarray.

    Science.gov (United States)

    Sanmann, Jennifer N; Pickering, Diane L; Golden, Denae M; Stevens, Jadd M; Hempel, Thomas E; Althof, Pamela A; Wiggins, Michele L; Starr, Lois J; Davé, Bhavana J; Sanger, Warren G

    2015-11-01

    The identification of clinically relevant genomic dosage anomalies assists in accurate diagnosis, prognosis, and medical management of affected individuals. Technological advancements within the field, such as the advent of microarray, have markedly increased the resolution of detection; however, clinical laboratories have maintained conventional techniques for confirmation of genomic imbalances identified by microarray to ensure diagnostic accuracy. In recent years the utility of this confirmatory testing of large-scale aberrations has been questioned but has not been scientifically addressed. We retrospectively reviewed 519 laboratory cases with genomic imbalances meeting reportable criteria by microarray and subsequently confirmed with a second technology, primarily fluorescence in situ hybridization. All genomic imbalances meeting reportable criteria detected by microarray were confirmed with a second technology. Microarray analysis generated no false-positive results. Confirmatory testing of large-scale genomic imbalances (deletion of ≥150 kb, duplication of ≥500 kb) solely for the purpose of microarray verification may be unwarranted. In some cases, however, adjunct testing is necessary to overcome limitations inherent to microarray. A recommended clinical strategy for adjunct testing following identified genomic imbalances using microarray is detailed.

  11. Fully Automated Complementary DNA Microarray Segmentation using a Novel Fuzzy-based Algorithm.

    Science.gov (United States)

    Saberkari, Hamidreza; Bahrami, Sheyda; Shamsi, Mousa; Amoshahy, Mohammad Javad; Ghavifekr, Habib Badri; Sedaaghi, Mohammad Hossein

    2015-01-01

    DNA microarray is a powerful approach to study simultaneously, the expression of 1000 of genes in a single experiment. The average value of the fluorescent intensity could be calculated in a microarray experiment. The calculated intensity values are very close in amount to the levels of expression of a particular gene. However, determining the appropriate position of every spot in microarray images is a main challenge, which leads to the accurate classification of normal and abnormal (cancer) cells. In this paper, first a preprocessing approach is performed to eliminate the noise and artifacts available in microarray cells using the nonlinear anisotropic diffusion filtering method. Then, the coordinate center of each spot is positioned utilizing the mathematical morphology operations. Finally, the position of each spot is exactly determined through applying a novel hybrid model based on the principle component analysis and the spatial fuzzy c-means clustering (SFCM) algorithm. Using a Gaussian kernel in SFCM algorithm will lead to improving the quality in complementary DNA microarray segmentation. The performance of the proposed algorithm has been evaluated on the real microarray images, which is available in Stanford Microarray Databases. Results illustrate that the accuracy of microarray cells segmentation in the proposed algorithm reaches to 100% and 98% for noiseless/noisy cells, respectively.

  12. A microarray analysis of the rice transcriptome and its comparison to Arabidopsis

    DEFF Research Database (Denmark)

    Ma, Ligeng; Chen, Chen; Liu, Xigang

    2005-01-01

    Arabidopsis and rice are the only two model plants whose finished phase genome sequence has been completed. Here we report the construction of an oligomer microarray based on the presently known and predicted gene models in the rice genome. This microarray was used to analyze the transcriptional ...

  13. Development, characterization and experimental validation of a cultivated sunflower (Helianthus annuus L.) gene expression oligonucleotide microarray.

    Science.gov (United States)

    Fernandez, Paula; Soria, Marcelo; Blesa, David; DiRienzo, Julio; Moschen, Sebastian; Rivarola, Maximo; Clavijo, Bernardo Jose; Gonzalez, Sergio; Peluffo, Lucila; Príncipi, Dario; Dosio, Guillermo; Aguirrezabal, Luis; García-García, Francisco; Conesa, Ana; Hopp, Esteban; Dopazo, Joaquín; Heinz, Ruth Amelia; Paniego, Norma

    2012-01-01

    Oligonucleotide-based microarrays with accurate gene coverage represent a key strategy for transcriptional studies in orphan species such as sunflower, H. annuus L., which lacks full genome sequences. The goal of this study was the development and functional annotation of a comprehensive sunflower unigene collection and the design and validation of a custom sunflower oligonucleotide-based microarray. A large scale EST (>130,000 ESTs) curation, assembly and sequence annotation was performed using Blast2GO (www.blast2go.de). The EST assembly comprises 41,013 putative transcripts (12,924 contigs and 28,089 singletons). The resulting Sunflower Unigen Resource (SUR version 1.0) was used to design an oligonucleotide-based Agilent microarray for cultivated sunflower. This microarray includes a total of 42,326 features: 1,417 Agilent controls, 74 control probes for sunflower replicated 10 times (740 controls) and 40,169 different non-control probes. Microarray performance was validated using a model experiment examining the induction of senescence by water deficit. Pre-processing and differential expression analysis of Agilent microarrays was performed using the Bioconductor limma package. The analyses based on p-values calculated by eBayes (psunflower unigene collection, and a custom, validated sunflower oligonucleotide-based microarray using Agilent technology. Both the curated unigene collection and the validated oligonucleotide microarray provide key resources for sunflower genome analysis, transcriptional studies, and molecular breeding for crop improvement.

  14. The efficacy of microarray screening for autosomal recessive retinitis pigmentosa in routine clinical practice

    NARCIS (Netherlands)

    Huet, R.A.C. van; Pierrache, L.H.; Meester-Smoor, M.A.; Klaver, C.C.; Born, L.I. van den; Hoyng, C.B.; Wijs, I.J. de; Collin, R.W.J.; Hoefsloot, L.H.; Klevering, B.J.

    2015-01-01

    PURPOSE: To determine the efficacy of multiple versions of a commercially available arrayed primer extension (APEX) microarray chip for autosomal recessive retinitis pigmentosa (arRP). METHODS: We included 250 probands suspected of arRP who were genetically analyzed with the APEX microarray between

  15. Calling biomarkers in milk using a protein microarray on your smartphone

    NARCIS (Netherlands)

    Ludwig, S.K.J.; Tokarski, Christian; Lang, Stefan N.; Ginkel, Van L.A.; Zhu, Hongying; Ozcan, Aydogan; Nielen, M.W.F.

    2015-01-01

    Here we present the concept of a protein microarray-based fluorescence immunoassay for multiple biomarker detection in milk extracts by an ordinary smartphone. A multiplex immunoassay was designed on a microarray chip, having built-in positive and negative quality controls. After the immunoassay

  16. Increasing the specificity and function of DNA microarrays by processing arrays at different stringencies

    DEFF Research Database (Denmark)

    Dufva, Martin; Petersen, Jesper; Poulsen, Lena

    2009-01-01

    DNA microarrays have for a decade been the only platform for genome-wide analysis and have provided a wealth of information about living organisms. DNA microarrays are processed today under one condition only, which puts large demands on assay development because all probes on the array need to f...

  17. Fluorescent microarray for multiplexed quantification of environmental contaminants in seawater samples

    Science.gov (United States)

    The development of a fluorescent multiplexed microarray platform able to detect and quantify a wide variety of pollutants in seawater is reported. The microarray platform has been manufactured by spotting 6 different bioconjugate competitors and it uses a cocktail of 6 monoclonal and polyclonal anti...

  18. Logistic ensembles of Random Spherical Linear Oracles for microarray classification.

    Science.gov (United States)

    Peterson, Leif E; Coleman, Matthew A

    2009-01-01

    Random Spherical Linear Oracles (RSLO) for DNA microarray gene expression data are proposed for classifier fusion. RSLO employs random hyperplane splits of samples in the principal component score space based on the first three principal components (X, Y, Z) of the input feature set. Hyperplane splits are used to assign training(testing) samples to separate logistic regression mini-classifiers, which increases the diversity of voting results since errors are not shared across mini-classifiers. We recommend use of RSLO with 3-4 10-fold CV and re-partitioning samples randomly every ten iterations prior to each 10-fold CV. This equates to a total of 30-40 iterations.

  19. Linear regression-based feature selection for microarray data classification.

    Science.gov (United States)

    Abid Hasan, Md; Hasan, Md Kamrul; Abdul Mottalib, M

    2015-01-01

    Predicting the class of gene expression profiles helps improve the diagnosis and treatment of diseases. Analysing huge gene expression data otherwise known as microarray data is complicated due to its high dimensionality. Hence the traditional classifiers do not perform well where the number of features far exceeds the number of samples. A good set of features help classifiers to classify the dataset efficiently. Moreover, a manageable set of features is also desirable for the biologist for further analysis. In this paper, we have proposed a linear regression-based feature selection method for selecting discriminative features. Our main focus is to classify the dataset more accurately using less number of features than other traditional feature selection methods. Our method has been compared with several other methods and in almost every case the classification accuracy is higher using less number of features than the other popular feature selection methods.

  20. High throughput screening of starch structures using carbohydrate microarrays

    DEFF Research Database (Denmark)

    Tanackovic, Vanja; Rydahl, Maja Gro; Pedersen, Henriette Lodberg

    2016-01-01

    maltooligosaccharides, pure starch samples including a variety of different structures with variations in the amylopectin branching pattern, amylose content and phosphate content, enzymatically modified starches and glycogen were included. Using this technique, different important structures, including amylose content......In this study we introduce the starch-recognising carbohydrate binding module family 20 (CBM20) from Aspergillus niger for screening biological variations in starch molecular structure using high throughput carbohydrate microarray technology. Defined linear, branched and phosphorylated...... and branching degrees could be differentiated in a high throughput fashion. The screening method was validated using transgenic barley grain analysed during development and subjected to germination. Typically, extreme branching or linearity were detected less than normal starch structures. The method offers...

  1. Cohen syndrome diagnosed using microarray comparative genomic hibridization

    Directory of Open Access Journals (Sweden)

    Saldarriaga-Gil, Wilmar

    2017-10-01

    Full Text Available Cohen syndrome (CS is an uncommon autosomal recessive genetic disorder attributed to damage on VPS13B gene, locus 8q22-q23. Characteristic phenotype consists of intellectual disability, microcephaly, facial dysmorphism, ophthalmic abnormalities, truncal obesity and hipotony. Worldwide, around 150 cases have been published, mostly in Finish patients. We report the case of a 3 year-old male, with short height, craniosynostosis, facial dysmorphism, hipotony, and developmental delay. He was diagnosed with Cohen syndrome using Microarray Comparative Genomic Hibridization (aCGH that showed homozygous deletion of 0.153 Mb on 8q22.2 including VPS13B gene, OMIM #216550. With this report we contribute to enlarge epidemiological databases on an uncommon genetic disorder. Besides, we illustrate on the contribution of aCGH to the etiological diagnosis of patients with unexplained intellectual disability, delayed psychomotor development, language difficulties, autism and multiple congenital anomalies.

  2. Computational analysis of microarray gene expression profiles of lung cancer

    Directory of Open Access Journals (Sweden)

    Babichev S. A.

    2016-02-01

    Full Text Available Aim. The article presents the researches on the optimization of the DNA microarray data processing, which is aimed at improving the quality of object clustering. Methods. Data preprocessing was performed with program R using Bioconductor package. Modelling the clustering process was made in the software environment KNIME using the program WEKA functions. Results. The data preprocessing is shown to be optimal while using such techniques as the background correction rma method, quantile normalization, mas PM correction and summarization by mas method. The simulation results have demonstrated a high effectiveness of the clustering algorithm Sota for this category of data. Conclusion. The results of the research have shown that improving the quality of biological object clustering is possible by means of hybridization and optimization of the methods and algorithms at different stages of data processing.

  3. Genome-wide transcription analyses in rice using tiling microarrays

    DEFF Research Database (Denmark)

    Li, Lei; Wang, Xiangfeng; Stolc, Viktor

    2006-01-01

    . We report here a full-genome transcription analysis of the indica rice subspecies using high-density oligonucleotide tiling microarrays. Our results provided expression data support for the existence of 35,970 (81.9%) annotated gene models and identified 5,464 unique transcribed intergenic regions......Sequencing and computational annotation revealed several features, including high gene numbers, unusual composition of the predicted genes and a large number of genes lacking homology to known genes, that distinguish the rice (Oryza sativa) genome from that of other fully sequenced model species...... activity between duplicated segments of the genome. Collectively, our results provide the first whole-genome transcription map useful for further understanding the rice genome. Udgivelsesdato: 2006-Jan...

  4. Reverse phase protein microarray technology in traumatic brain injury.

    Science.gov (United States)

    Gyorgy, Andrea B; Walker, John; Wingo, Dan; Eidelman, Ofer; Pollard, Harvey B; Molnar, Andras; Agoston, Denes V

    2010-09-30

    Antibody based, high throughput proteomics technology represents an exciting new approach in understanding the pathobiologies of complex disorders such as cancer, stroke and traumatic brain injury. Reverse phase protein microarray (RPPA) can complement the classical methods based on mass spectrometry as a high throughput validation and quantification method. RPPA technology can address problematic issues, such as sample complexity, sensitivity, quantification, reproducibility and throughput, which are currently associated with mass spectrometry-based approaches. However, there are technical challenges, predominantly associated with the selection and use of antibodies, preparation and representation of samples and with analyzing and quantifying primary RPPA data. Here we present ways to identify and overcome some of the current issues associated with RPPA. We believe that using stringent quality controls, improved bioinformatics analysis and interpretation of primary RPPA data, this method will significantly contribute in generating new level of understanding about complex disorders at the level of systems biology. Published by Elsevier B.V.

  5. A Versatile Microarray Immobilization Strategy Based on a Biorthogonal Reaction Between Tetrazine and Trans-Cyclooctene.

    Science.gov (United States)

    Wang, Ping; Gao, Liqian; Lei, Haipeng; Lee, Su Seong; Yao, Shao Q; Sun, Hongyan

    2017-01-01

    Given its increasing importance in transforming biomedical research in recent years, microarray technology has become highly popular as a powerful screening platform in detecting biomolecule interactions, discovering new inhibitors, and identifying biomarkers as well as diagnosing disease. The success of microarray technology in various biological applications is highly dependent on the accessibility, the functionality, and the density of the surface bound biomolecules. Therefore, compound immobilization represents a critical step for the successful implementation of microarray screening. Herein we describe a fast and site-specific microarray immobilization approach by using trans-cyclooctene-tetrazine ligation. This approach not only ensures fast immobilization and uniform display of biomolecules, but also allows the optimum orientation of biomolecules after immobilization. All these excellent properties facilitate subsequent interactions of the biomolecules and their interacting partners during the screening process. We envision that the immobilization strategy described here can find useful applications in many other microarray related studies.

  6. Versatile High Resolution Oligosaccharide Microarrays for Plant Glycobiology and Cell Wall Research

    DEFF Research Database (Denmark)

    Pedersen, Henriette Lodberg; Fangel, Jonatan Ulrik; McCleary, Barry

    2012-01-01

    Microarrays are powerful tools for high throughput analysis, and hundreds or thousands of molecular interactions can be assessed simultaneously using very small amounts of analytes. Nucleotide microarrays are well established in plant research, but carbohydrate microarrays are much less established......, and one reason for this is a lack of suitable glycans with which to populate arrays. Polysaccharide microarrays are relatively easy to produce because of the ease of immobilizing large polymers noncovalently onto a variety of microarray surfaces, but they lack analytical resolution because polysaccharides...... for the high throughput characterization of the recognition capabilities of monoclonal antibodies, carbohydrate-binding modules, and other oligosaccharide-binding proteins of biological significance and also that they have potential for the characterization of carbohydrate-active enzymes....

  7. [DNA microarrays and their application in detecting and identifying intestinal pathogens].

    Science.gov (United States)

    Jin, Da-Zhi; Wen, Si-Yuan; Wang, Sheng-Qi

    2006-06-01

    DNA microarrays offer many advantages of high throughout, automation, rapid detection, and so on. Therefore, this technology had been used in many fields such as molecular epidemiology of bacteria, microbial gene identification, disease mechanism, gene mutation, gene expression identification, DNA sequencing and medicine screening etc. The assays for identifying pathogens using DNA microarrays reported aboard recently are introduced. The application of DNA microarrays in detecting and identifying intestinal pathogens mainly includes three aspects: the identification of toxin and characteristic genes of pathogens, the identification of bacterial DNA or RNA directly, the simultaneous detection of a large number of intestinal pathogens with the target - gene of ribosomal RNA. Because of its high efficiency, DNA microarrays is superior to other biological method. Obviously DNA microarrays technology may be useful in identifying intestinal pathogens and have a wide prospect.

  8. Validation of MIMGO: a method to identify differentially expressed GO terms in a microarray dataset

    Directory of Open Access Journals (Sweden)

    Yamada Yoichi

    2012-12-01

    Full Text Available Abstract Background We previously proposed an algorithm for the identification of GO terms that commonly annotate genes whose expression is upregulated or downregulated in some microarray data compared with in other microarray data. We call these “differentially expressed GO terms” and have named the algorithm “matrix-assisted identification method of differentially expressed GO terms” (MIMGO. MIMGO can also identify microarray data in which genes annotated with a differentially expressed GO term are upregulated or downregulated. However, MIMGO has not yet been validated on a real microarray dataset using all available GO terms. Findings We combined Gene Set Enrichment Analysis (GSEA with MIMGO to identify differentially expressed GO terms in a yeast cell cycle microarray dataset. GSEA followed by MIMGO (GSEA + MIMGO correctly identified (p Conclusions MIMGO is a reliable method to identify differentially expressed GO terms comprehensively.

  9. Considerations when using the significance analysis of microarrays (SAM algorithm

    Directory of Open Access Journals (Sweden)

    Timmons James A

    2005-05-01

    Full Text Available Abstract Background Users of microarray technology typically strive to use universally acceptable data analysis strategies to determine significant expression changes in their experiments. One of the most frequently utilised methods for gene expression data analysis is SAM (significance analysis of microarrays. The impact of selection thresholds, on the output from SAM, may critically alter the conclusion of a study, yet this consideration has not been systematically evaluated in any publication. Results We have examined the effect of discrete data selection criteria (qualification criteria for inclusion and response thresholds (out-put filtering on the number of significant genes reported by SAM. The use of a reduced data set by applying arbitrary restrictions vis-à-vis abundance calls (e.g. from D-chip or application of the fold change (FC option within SAM (named the FC hurdle hereafter, can substantially alter the significant gene list when running SAM in Microsoft Excel. We determined that for a given final FC criteria (e.g. 1.5 fold change the FC hurdle applied within Microsoft Excel SAM alters the number of reported genes above the final FC criteria. The reason is that the FC hurdle changes the composition of the control data set, such that a different significance level (q-value is obtained for any given gene. This effect can be so large that it changes subsequent post hoc analysis interpretation, such as ontology overrepresentation analysis. Conclusion Our results argue for caution when using SAM. All data sets analysed with SAM could be reanalysed taking into account the potential impact of the use of arbitrary thresholds to trim data sets before significance testing.

  10. Exon microarray analysis of human dorsolateral prefrontal cortex in alcoholism.

    Science.gov (United States)

    Manzardo, Ann M; Gunewardena, Sumedha; Wang, Kun; Butler, Merlin G

    2014-06-01

    Alcohol abuse is associated with cellular and biochemical disturbances that impact upon protein and nucleic acid synthesis, brain development, function, and behavioral responses. To further characterize the genetic influences in alcoholism and the effects of alcohol consumption on gene expression, we used a highly sensitive exon microarray to examine mRNA expression in human frontal cortex of alcoholics and control males. Messenger RNA was isolated from the dorsolateral prefrontal cortex (dlPFC; Brodmann area 9) of 7 adult alcoholic (6 males, 1 female, mean age 49 years) and 7 matched controls. Affymetrix Human Exon 1.0 ST array was performed according to standard procedures and the results analyzed at the gene level. Microarray findings were validated using quantitative reverse transcription polymerase chain reaction, and the ontology of disturbed genes characterized using Ingenuity Pathway Analysis (IPA). Decreased mRNA expression was observed for genes involved in cellular adhesion (e.g., CTNNA3, ITGA2), transport (e.g., TF, ABCA8), nervous system development (e.g., LRP2, UGT8, GLDN), and signaling (e.g., RASGRP3, LGR5) with influence over lipid and myelin synthesis (e.g., ASPA, ENPP2, KLK6). IPA identified disturbances in network functions associated with neurological disease and development including cellular assembly and organization impacting on psychological disorders. Our data in alcoholism support a reduction in expression of dlPFC mRNA for genes involved with neuronal growth, differentiation, and signaling that targets white matter of the brain. Copyright © 2014 by the Research Society on Alcoholism.

  11. Protein Microarrays-Based Strategies for Life Detection in Astrobiology

    Science.gov (United States)

    Parro, Víctor; Rivas, Luis A.; Gómez-Elvira, Javier

    2008-03-01

    The detection of organic molecules of unambiguous biological origin is fundamental for the confirmation of present or past life. Planetary exploration requires the development of miniaturized apparatus for in situ life detection. Analytical techniques based on mass spectrometry have been traditionally used in space science. Following the Viking landers, gas chromatography-mass spectrometry (GC-MS) for organic detection has gained general acceptance and has been used successfully in the Cassini-Huygens mission to Titan. Microfluidics allows the development of miniaturized capillary electrophoresis devices for the detection of important molecules for life, like amino acids or nucleobases. Recently, a new approach is gaining acceptance in the space science community: the application of the well-known, highly specific, antibody-antigen affinity interaction for the detection and identification of organics and biochemical compounds. Antibodies can specifically bind a plethora of structurally different compounds of a broad range of molecular sizes, from amino acids level to whole cells. Antibody microarray technology allows us to look for the presence of thousands of different compounds in a single assay and in just one square centimeter. Herein, we discuss several important issues—most of which are common with other instruments dealing with life signature detection in the solar system—that must be addressed in order to use antibody microarrays for life detection and planetary exploration. These issues include (1) preservation of biomarkers, (2) the extraction techniques for biomarkers, (3) terrestrial analogues, (4) the antibody stability under space environments, (5) the selection of unequivocal biomarkers for the antibody production, or (6) the instrument design and implementation.

  12. Canine Central Nervous System Neoplasm Phenotyping Using Tissue Microarray Technique.

    Science.gov (United States)

    Spitzbarth, I; Heinrich, F; Herder, V; Recker, T; Wohlsein, P; Baumgärtner, W

    2017-05-01

    Tissue microarrays (TMAs) represent a useful technique for the simultaneous phenotyping of large sample numbers and are particularly suitable for histopathologic tumor research. In this study, TMAs were used to evaluate semiquantitatively the expression of multiple antigens in various canine central nervous system (CNS) neoplasms and to identify markers with potential discriminative diagnostic relevance. Ninety-seven canine CNS neoplasms, previously diagnosed on hematoxylin and eosin sections according to the World Health Organization classification, were investigated on TMAs, with each tumor consisting of 2 cylindrical samples from the center and the periphery of the neoplasm. Tumor cells were phenotyped using a panel of 28 monoclonal and polyclonal antibodies, and hierarchical clustering analysis was applied to group neoplasms according to similarities in their expression profiles. Hierarchical clustering generally grouped cases with similar histologic diagnoses; however, gliomas especially exhibited a considerable heterogeneity in their positivity scores. Multiple tumor groups, such as astrocytomas and oligodendrogliomas, significantly differed in the proportion of positive immunoreaction for certain markers such as p75 NTR , AQP4, GFAP, and S100 protein. The study highlights AQP4 and p75 NTR as novel markers, helping to discriminate between canine astrocytoma and oligodendroglioma. Furthermore, the results suggest that p75 NTR and proteolipid protein may represent useful markers, whose expression inversely correlates with malignant transformation in canine astrocytomas and oligodendrogliomas, respectively. Tissue microarray was demonstrated to be a useful and time-saving tool for the simultaneous immunohistochemical characterization of multiple canine CNS neoplasms. The present study provides a detailed overview of the expression patterns of different types of canine CNS neoplasms.

  13. Microarrays in ecological research: A case study of a cDNA microarray for plant-herbivore interactions

    Directory of Open Access Journals (Sweden)

    Gase Klaus

    2004-09-01

    Full Text Available Abstract Background Microarray technology allows researchers to simultaneously monitor changes in the expression ratios (ERs of hundreds of genes and has thereby revolutionized most of biology. Although this technique has the potential of elucidating early stages in an organism's phenotypic response to complex ecological interactions, to date, it has not been fully incorporated into ecological research. This is partially due to a lack of simple procedures of handling and analyzing the expression ratio (ER data produced from microarrays. Results We describe an analysis of the sources of variation in ERs from 73 hybridized cDNA microarrays, each with 234 herbivory-elicited genes from the model ecological expression system, Nicotiana attenuata, using procedures that are commonly used in ecologic research. Each gene is represented by two independently labeled PCR products and each product was arrayed in quadruplicate. We present a robust method of normalizing and analyzing ERs based on arbitrary thresholds and statistical criteria, and characterize a "norm of reaction" of ERs for 6 genes (4 of known function, 2 of unknown with different ERs as determined across all analyzed arrays to provide a biologically-informed alternative to the use of arbitrary expression ratios in determining significance of expression. These gene-specific ERs and their variance (gene CV were used to calculate array-based variances (array CV, which, in turn, were used to study the effects of array age, probe cDNA quantity and quality, and quality of spotted PCR products as estimates of technical variation. Cluster analysis and a Principal Component Analysis (PCA were used to reveal associations among the transcriptional "imprints" of arrays hybridized with cDNA probes derived from mRNA from N. attenuata plants variously elicited and attacked by different herbivore species and from three congeners: N. quadrivalis, N. longiflora and N. clevelandii. Additionally, the PCA

  14. Image microarrays derived from tissue microarrays (IMA-TMA: New resource for computer-aided diagnostic algorithm development

    Directory of Open Access Journals (Sweden)

    Jennifer A Hipp

    2012-01-01

    Full Text Available Background: Conventional tissue microarrays (TMAs consist of cores of tissue inserted into a recipient paraffin block such that a tissue section on a single glass slide can contain numerous patient samples in a spatially structured pattern. Scanning TMAs into digital slides for subsequent analysis by computer-aided diagnostic (CAD algorithms all offers the possibility of evaluating candidate algorithms against a near-complete repertoire of variable disease morphologies. This parallel interrogation approach simplifies the evaluation, validation, and comparison of such candidate algorithms. A recently developed digital tool, digital core (dCORE, and image microarray maker (iMAM enables the capture of uniformly sized and resolution-matched images, with these representing key morphologic features and fields of view, aggregated into a single monolithic digital image file in an array format, which we define as an image microarray (IMA. We further define the TMA-IMA construct as IMA-based images derived from whole slide images of TMAs themselves. Methods: Here we describe the first combined use of the previously described dCORE and iMAM tools, toward the goal of generating a higher-order image construct, with multiple TMA cores from multiple distinct conventional TMAs assembled as a single digital image montage. This image construct served as the basis of the carrying out of a massively parallel image analysis exercise, based on the use of the previously described spatially invariant vector quantization (SIVQ algorithm. Results: Multicase, multifield TMA-IMAs of follicular lymphoma and follicular hyperplasia were separately rendered, using the aforementioned tools. Each of these two IMAs contained a distinct spectrum of morphologic heterogeneity with respect to both tingible body macrophage (TBM appearance and apoptotic body morphology. SIVQ-based pattern matching, with ring vectors selected to screen for either tingible body macrophages or apoptotic

  15. MicroArray Facility: a laboratory information management system with extended support for Nylon based technologies

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    Beaudoing Emmanuel

    2006-09-01

    Full Text Available Abstract Background High throughput gene expression profiling (GEP is becoming a routine technique in life science laboratories. With experimental designs that repeatedly span thousands of genes and hundreds of samples, relying on a dedicated database infrastructure is no longer an option. GEP technology is a fast moving target, with new approaches constantly broadening the field diversity. This technology heterogeneity, compounded by the informatics complexity of GEP databases, means that software developments have so far focused on mainstream techniques, leaving less typical yet established techniques such as Nylon microarrays at best partially supported. Results MAF (MicroArray Facility is the laboratory database system we have developed for managing the design, production and hybridization of spotted microarrays. Although it can support the widely used glass microarrays and oligo-chips, MAF was designed with the specific idiosyncrasies of Nylon based microarrays in mind. Notably single channel radioactive probes, microarray stripping and reuse, vector control hybridizations and spike-in controls are all natively supported by the software suite. MicroArray Facility is MIAME supportive and dynamically provides feedback on missing annotations to help users estimate effective MIAME compliance. Genomic data such as clone identifiers and gene symbols are also directly annotated by MAF software using standard public resources. The MAGE-ML data format is implemented for full data export. Journalized database operations (audit tracking, data anonymization, material traceability and user/project level confidentiality policies are also managed by MAF. Conclusion MicroArray Facility is a complete data management system for microarray producers and end-users. Particular care has been devoted to adequately model Nylon based microarrays. The MAF system, developed and implemented in both private and academic environments, has proved a robust solution for

  16. A genome-wide 20 K citrus microarray for gene expression analysis

    Directory of Open Access Journals (Sweden)

    Gadea Jose

    2008-07-01

    Full Text Available Abstract Background Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results We have designed and constructed a publicly available genome-wide cDNA microarray that include 21,081 putative unigenes of citrus. As a functional companion to the microarray, a web-browsable database 1 was created and populated with information about the unigenes represented in the microarray, including cDNA libraries, isolated clones, raw and processed nucleotide and protein sequences, and results of all the structural and functional annotation of the unigenes, like general description, BLAST hits, putative Arabidopsis orthologs, microsatellites, putative SNPs, GO classification and PFAM domains. We have performed a Gene Ontology comparison with the full set of Arabidopsis proteins to estimate the genome coverage of the microarray. We have also performed microarray hybridizations to check its usability. Conclusion This new cDNA microarray replaces the first 7K microarray generated two years ago and allows gene expression analysis at a more global scale. We have followed a rational design to minimize cross-hybridization while maintaining its utility for different citrus species. Furthermore, we also provide access to a website with full structural and functional annotation of the unigenes represented in the microarray, along with the ability to use this site to directly perform gene expression analysis using standard tools at different publicly available servers. Furthermore, we show how this microarray offers a good representation of the citrus genome and present the usefulness of this genomic tool for global

  17. Hyperspectral microarray scanning: impact on the accuracy and reliability of gene expression data

    Directory of Open Access Journals (Sweden)

    Martinez M Juanita

    2005-05-01

    Full Text Available Abstract Background Commercial microarray scanners and software cannot distinguish between spectrally overlapping emission sources, and hence cannot accurately identify or correct for emissions not originating from the labeled cDNA. We employed our hyperspectral microarray scanner coupled with multivariate data analysis algorithms that independently identify and quantitate emissions from all sources to investigate three artifacts that reduce the accuracy and reliability of microarray data: skew toward the green channel, dye separation, and variable background emissions. Results Here we demonstrate that several common microarray artifacts resulted from the presence of emission sources other than the labeled cDNA that can dramatically alter the accuracy and reliability of the array data. The microarrays utilized in this study were representative of a wide cross-section of the microarrays currently employed in genomic research. These findings reinforce the need for careful attention to detail to recognize and subsequently eliminate or quantify the presence of extraneous emissions in microarray images. Conclusion Hyperspectral scanning together with multivariate analysis offers a unique and detailed understanding of the sources of microarray emissions after hybridization. This opportunity to simultaneously identify and quantitate contaminant and background emissions in microarrays markedly improves the reliability and accuracy of the data and permits a level of quality control of microarray emissions previously unachievable. Using these tools, we can not only quantify the extent and contribution of extraneous emission sources to the signal, but also determine the consequences of failing to account for them and gain the insight necessary to adjust preparation protocols to prevent such problems from occurring.

  18. The Clinical Utility of a Single-Nucleotide Polymorphism Microarray in Patients With Epilepsy at a Tertiary Medical Center.

    Science.gov (United States)

    Hrabik, Sarah A; Standridge, Shannon M; Greiner, Hansel M; Neilson, Derek E; Pilipenko, Valentina V; Zimmerman, Sarah L; Connor, Jessica A; Spaeth, Christine G

    2015-11-01

    Microarray testing has revolutionized clinical cytogenetics, as it provides a significantly higher resolution and greater clinical yield than karyotype analysis. This study assessed the clinical utility of single-nucleotide polymorphism microarray in patients with epilepsy. Study subjects were patients between the ages of birth to 23 years who were diagnosed with epilepsy and had a microarray performed at Cincinnati Children's Hospital Medical Center. Statistical analysis explored the association of microarray results and brain magnetic resonance imaging (MRI), seizure type, and structural malformations. Approximately 17.7% (26/147) of participants had an abnormal microarray as defined by laboratory guidelines. There were no differences in frequency of abnormal brain MRI or seizure type between the abnormal and normal microarray groups. There was a higher prevalence of musculoskeletal malformations (P microarrays. Clinicians should consider microarray analysis in individuals who have epilepsy, especially in combination with musculoskeletal malformation or cardiovascular malformation. © The Author(s) 2015.

  19. Radioactive cDNA microarray (II): Gene expression profiling of antidepressant treatment by human cDNA microarray

    International Nuclear Information System (INIS)

    Lee, Ji Hye; Kang, Rhee Hun; Ham, Byung Joo; Lee, Min Su; Shin, Kyung Ho; Choe, Jae Gol; Kim, Meyoung Kon

    2003-01-01

    Major depressive disorder is a prevalent psychiatric disorder in primary care, associated with impaired patient functioning and well-being. Fluoxetine is a selective serotonin-reuptake inhibitors (SSRIs) and is a commonly prescribed antidepressant compound. Its action is primarily attributed to selective inhibition of the reuptake of serotonin (5-hydroxytryptamine) in the central nervous system. Objectives ; the aims of this study were two-fold: (1) to determine the usefulness for investigation of the transcription profiles in depression patients, and (2) to assess the differences in gene expression profiles between positive response group and negative response groups by fluoxetine treatment. This study included 53 patients with major depression (26 in positive response group with antidepressant treatment, 27 in negative response group with antidepressant treatment), and 53 healthy controls. To examine the difference of gene expression profile in depression patients, radioactive complementary DNA microarrays were used to evaluate changes in the expression of 1,152 genes in total. Using 33p-labeled probes, this method provided highly sensitive gene expression profiles including brain receptors, drug metabolism, and cellular signaling. Gene transcription profiles were classified into several categories in accordance with the antidepressant gene-regulation. The gene profiles were significantly up-(22 genes) and down-(16 genes) regulated in the positive response group when compared to the control group. Also, in the negative response group, 35 genes were up-regulated and 8 genes were down-regulated when compared to the control group. Consequently, we demonstrated that radioactive human cDNA microarray is highly likely to be an efficient technology for evaluating the gene regulation of antidepressants, such as selective serotonin-reuptake inhibitors (SSRIs), by using high-throughput biotechnology

  20. Radioactive cDNA microarray (II): Gene expression profiling of antidepressant treatment by human cDNA microarray

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Ji Hye; Kang, Rhee Hun; Ham, Byung Joo; Lee, Min Su; Shin, Kyung Ho; Choe, Jae Gol; Kim, Meyoung Kon [College of Medicine, Univ. of Korea, Seoul (Korea, Republic of)

    2003-07-01

    Major depressive disorder is a prevalent psychiatric disorder in primary care, associated with impaired patient functioning and well-being. Fluoxetine is a selective serotonin-reuptake inhibitors (SSRIs) and is a commonly prescribed antidepressant compound. Its action is primarily attributed to selective inhibition of the reuptake of serotonin (5-hydroxytryptamine) in the central nervous system. Objectives ; the aims of this study were two-fold: (1) to determine the usefulness for investigation of the transcription profiles in depression patients, and (2) to assess the differences in gene expression profiles between positive response group and negative response groups by fluoxetine treatment. This study included 53 patients with major depression (26 in positive response group with antidepressant treatment, 27 in negative response group with antidepressant treatment), and 53 healthy controls. To examine the difference of gene expression profile in depression patients, radioactive complementary DNA microarrays were used to evaluate changes in the expression of 1,152 genes in total. Using 33p-labeled probes, this method provided highly sensitive gene expression profiles including brain receptors, drug metabolism, and cellular signaling. Gene transcription profiles were classified into several categories in accordance with the antidepressant gene-regulation. The gene profiles were significantly up-(22 genes) and down-(16 genes) regulated in the positive response group when compared to the control group. Also, in the negative response group, 35 genes were up-regulated and 8 genes were down-regulated when compared to the control group. Consequently, we demonstrated that radioactive human cDNA microarray is highly likely to be an efficient technology for evaluating the gene regulation of antidepressants, such as selective serotonin-reuptake inhibitors (SSRIs), by using high-throughput biotechnology.

  1. Microarray and bioinformatic analyses suggest models for carbon metabolism in the autotroph Acidithiobacillus ferrooxidans

    Energy Technology Data Exchange (ETDEWEB)

    C. Appia-ayme; R. Quatrini; Y. Denis; F. Denizot; S. Silver; F. Roberto; F. Veloso; J. Valdes; J. P. Cardenas; M. Esparza; O. Orellana; E. Jedlicki; V. Bonnefoy; D. Holmes

    2006-09-01

    Acidithiobacillus ferrooxidans is a chemolithoautotrophic bacterium that uses iron or sulfur as an energy and electron source. Bioinformatic analysis was used to identify putative genes and potential metabolic pathways involved in CO2 fixation, 2P-glycolate detoxification, carboxysome formation and glycogen utilization in At. ferrooxidans. Microarray transcript profiling was carried out to compare the relative expression of the predicted genes of these pathways when the microorganism was grown in the presence of iron versus sulfur. Several gene expression patterns were confirmed by real-time PCR. Genes for each of the above predicted pathways were found to be organized into discrete clusters. Clusters exhibited differential gene expression depending on the presence of iron or sulfur in the medium. Concordance of gene expression within each cluster, suggested that they are operons Most notably, clusters of genes predicted to be involved in CO2 fixation, carboxysome formation, 2P-glycolate detoxification and glycogen biosynthesis were up-regulated in sulfur medium, whereas genes involved in glycogen utilization were preferentially expressed in iron medium. These results can be explained in terms of models of gene regulation that suggest how A. ferrooxidans can adjust its central carbon management to respond to changing environmental conditions.

  2. Validation of MIMGO: a method to identify differentially expressed GO terms in a microarray dataset

    Science.gov (United States)

    2012-01-01

    Background We previously proposed an algorithm for the identification of GO terms that commonly annotate genes whose expression is upregulated or downregulated in some microarray data compared with in other microarray data. We call these “differentially expressed GO terms” and have named the algorithm “matrix-assisted identification method of differentially expressed GO terms” (MIMGO). MIMGO can also identify microarray data in which genes annotated with a differentially expressed GO term are upregulated or downregulated. However, MIMGO has not yet been validated on a real microarray dataset using all available GO terms. Findings We combined Gene Set Enrichment Analysis (GSEA) with MIMGO to identify differentially expressed GO terms in a yeast cell cycle microarray dataset. GSEA followed by MIMGO (GSEA + MIMGO) correctly identified (p microarray data in which genes annotated to differentially expressed GO terms are upregulated. We found that GSEA + MIMGO was slightly less effective than, or comparable to, GSEA (Pearson), a method that uses Pearson’s correlation as a metric, at detecting true differentially expressed GO terms. However, unlike other methods including GSEA (Pearson), GSEA + MIMGO can comprehensively identify the microarray data in which genes annotated with a differentially expressed GO term are upregulated or downregulated. Conclusions MIMGO is a reliable method to identify differentially expressed GO terms comprehensively. PMID:23232071

  3. Protein microarray with horseradish peroxidase chemiluminescence for quantification of serum α-fetoprotein.

    Science.gov (United States)

    Zhao, Yuanshun; Zhang, Yonghong; Lin, Dongdong; Li, Kang; Yin, Chengzeng; Liu, Xiuhong; Jin, Boxun; Sun, Libo; Liu, Jinhua; Zhang, Aiying; Li, Ning

    2015-10-01

    To develop and evaluate a protein microarray assay with horseradish peroxidase (HRP) chemiluminescence for quantification of α-fetoprotein (AFP) in serum from patients with hepatocellular carcinoma (HCC). A protein microarray assay for AFP was developed. Serum was collected from patients with HCC and healthy control subjects. AFP was quantified using protein microarray and enzyme-linked immunosorbent assay (ELISA). Serum AFP concentrations determined via protein microarray were positively correlated (r = 0.973) with those determined via ELISA in patients with HCC (n = 60) and healthy control subjects (n = 30). Protein microarray showed 80% sensitivity and 100% specificity for HCC diagnosis. ELISA had 83.3% sensitivity and 100% specificity. Protein microarray effectively distinguished between patients with HCC and healthy control subjects (area under ROC curve 0.974; 95% CI 0.000, 1.000). Protein microarray is a rapid, simple and low-cost alternative to ELISA for detecting AFP in human serum. © The Author(s) 2015.

  4. Flow-pattern Guided Fabrication of High-density Barcode Antibody Microarray.

    Science.gov (United States)

    Ramirez, Lisa S; Wang, Jun

    2016-01-06

    Antibody microarray as a well-developed technology is currently challenged by a few other established or emerging high-throughput technologies. In this report, we renovate the antibody microarray technology by using a novel approach for manufacturing and by introducing new features. The fabrication of our high-density antibody microarray is accomplished through perpendicularly oriented flow-patterning of single stranded DNAs and subsequent conversion mediated by DNA-antibody conjugates. This protocol outlines the critical steps in flow-patterning DNA, producing and purifying DNA-antibody conjugates, and assessing the quality of the fabricated microarray. The uniformity and sensitivity are comparable with conventional microarrays, while our microarray fabrication does not require the assistance of an array printer and can be performed in most research laboratories. The other major advantage is that the size of our microarray units is 10 times smaller than that of printed arrays, offering the unique capability of analyzing functional proteins from single cells when interfacing with generic microchip designs. This barcode technology can be widely employed in biomarker detection, cell signaling studies, tissue engineering, and a variety of clinical applications.

  5. Testing a Microarray to Detect and Monitor Toxic Microalgae in Arcachon Bay in France.

    Science.gov (United States)

    Kegel, Jessica U; Del Amo, Yolanda; Costes, Laurence; Medlin, Linda K

    2013-03-05

    Harmful algal blooms (HABs) occur worldwide, causing health problems and economic damages to fisheries and tourism. Monitoring agencies are therefore essential, yet monitoring is based only on time-consuming light microscopy, a level at which a correct identification can be limited by insufficient morphological characters. The project MIDTAL (Microarray Detection of Toxic Algae)-an FP7-funded EU project-used rRNA genes (SSU and LSU) as a target on microarrays to identify toxic species. Furthermore, toxins were detected with a newly developed multiplex optical Surface Plasmon Resonance biosensor (Multi SPR) and compared with an enzyme-linked immunosorbent assay (ELISA). In this study, we demonstrate the latest generation of MIDTAL microarrays (version 3) and show the correlation between cell counts, detected toxin and microarray signals from field samples taken in Arcachon Bay in France in 2011. The MIDTAL microarray always detected more potentially toxic species than those detected by microscopic counts. The toxin detection was even more sensitive than both methods. Because of the universal nature of both toxin and species microarrays, they can be used to detect invasive species. Nevertheless, the MIDTAL microarray is not completely universal: first, because not all toxic species are on the chip, and second, because invasive species, such as Ostreopsis, already influence European coasts.

  6. Testing a Microarray to Detect and Monitor Toxic Microalgae in Arcachon Bay in France

    Directory of Open Access Journals (Sweden)

    Linda K. Medlin

    2013-03-01

    Full Text Available Harmful algal blooms (HABs occur worldwide, causing health problems and economic damages to fisheries and tourism. Monitoring agencies are therefore essential, yet monitoring is based only on time-consuming light microscopy, a level at which a correct identification can be limited by insufficient morphological characters. The project MIDTAL (Microarray Detection of Toxic Algae—an FP7-funded EU project—used rRNA genes (SSU and LSU as a target on microarrays to identify toxic species. Furthermore, toxins were detected with a newly developed multiplex optical Surface Plasmon Resonance biosensor (Multi SPR and compared with an enzyme-linked immunosorbent assay (ELISA. In this study, we demonstrate the latest generation of MIDTAL microarrays (version 3 and show the correlation between cell counts, detected toxin and microarray signals from field samples taken in Arcachon Bay in France in 2011. The MIDTAL microarray always detected more potentially toxic species than those detected by microscopic counts. The toxin detection was even more sensitive than both methods. Because of the universal nature of both toxin and species microarrays, they can be used to detect invasive species. Nevertheless, the MIDTAL microarray is not completely universal: first, because not all toxic species are on the chip, and second, because invasive species, such as Ostreopsis, already influence European coasts.

  7. Implementation of mutual information and bayes theorem for classification microarray data

    Science.gov (United States)

    Dwifebri Purbolaksono, Mahendra; Widiastuti, Kurnia C.; Syahrul Mubarok, Mohamad; Adiwijaya; Aminy Ma’ruf, Firda

    2018-03-01

    Microarray Technology is one of technology which able to read the structure of gen. The analysis is important for this technology. It is for deciding which attribute is more important than the others. Microarray technology is able to get cancer information to diagnose a person’s gen. Preparation of microarray data is a huge problem and takes a long time. That is because microarray data contains high number of insignificant and irrelevant attributes. So, it needs a method to reduce the dimension of microarray data without eliminating important information in every attribute. This research uses Mutual Information to reduce dimension. System is built with Machine Learning approach specifically Bayes Theorem. This theorem uses a statistical and probability approach. By combining both methods, it will be powerful for Microarray Data Classification. The experiment results show that system is good to classify Microarray data with highest F1-score using Bayesian Network by 91.06%, and Naïve Bayes by 88.85%.

  8. An open-access long oligonucleotide microarray resource for analysis of the human and mouse transcriptomes.

    Science.gov (United States)

    Le Brigand, Kévin; Russell, Roslin; Moreilhon, Chimène; Rouillard, Jean-Marie; Jost, Bernard; Amiot, Franck; Magnone, Virginie; Bole-Feysot, Christine; Rostagno, Philippe; Virolle, Virginie; Defamie, Virginie; Dessen, Philippe; Williams, Gary; Lyons, Paul; Rios, Géraldine; Mari, Bernard; Gulari, Erdogan; Kastner, Philippe; Gidrol, Xavier; Freeman, Tom C; Barbry, Pascal

    2006-07-19

    Two collections of oligonucleotides have been designed for preparing pangenomic human and mouse microarrays. A total of 148,993 and 121,703 oligonucleotides were designed against human and mouse transcripts. Quality scores were created in order to select 25,342 human and 24,109 mouse oligonucleotides. They correspond to: (i) a BLAST-specificity score; (ii) the number of expressed sequence tags matching each probe; (iii) the distance to the 3' end of the target mRNA. Scores were also used to compare in silico the two microarrays with commercial microarrays. The sets described here, called RNG/MRC collections, appear at least as specific and sensitive as those from the commercial platforms. The RNG/MRC collections have now been used by an Anglo-French consortium to distribute more than 3500 microarrays to the academic community. Ad hoc identification of tissue-specific transcripts and a approximately 80% correlation with hybridizations performed on Affymetrix GeneChiptrade mark suggest that the RNG/MRC microarrays perform well. This work provides a comprehensive open resource for investigators working on human and mouse transcriptomes, as well as a generic method to generate new microarray collections in other organisms. All information related to these probes, as well as additional information about commercial microarrays have been stored in a freely-accessible database called MEDIANTE.

  9. Uropathogenic Escherichia coli virulence genes: invaluable approaches for designing DNA microarray probes.

    Science.gov (United States)

    Jahandeh, Nadia; Ranjbar, Reza; Behzadi, Payam; Behzadi, Elham

    2015-01-01

    The pathotypes of uropathogenic Escherichia coli (UPEC) cause different types of urinary tract infections (UTIs). The presence of a wide range of virulence genes in UPEC enables us to design appropriate DNA microarray probes. These probes, which are used in DNA microarray technology, provide us with an accurate and rapid diagnosis and definitive treatment in association with UTIs caused by UPEC pathotypes. The main goal of this article is to introduce the UPEC virulence genes as invaluable approaches for designing DNA microarray probes. Main search engines such as Google Scholar and databases like NCBI were searched to find and study several original pieces of literature, review articles, and DNA gene sequences. In parallel with in silico studies, the experiences of the authors were helpful for selecting appropriate sources and writing this review article. There is a significant variety of virulence genes among UPEC strains. The DNA sequences of virulence genes are fabulous patterns for designing microarray probes. The location of virulence genes and their sequence lengths influence the quality of probes. The use of selected virulence genes for designing microarray probes gives us a wide range of choices from which the best probe candidates can be chosen. DNA microarray technology provides us with an accurate, rapid, cost-effective, sensitive, and specific molecular diagnostic method which is facilitated by designing microarray probes. Via these tools, we are able to have an accurate diagnosis and a definitive treatment regarding UTIs caused by UPEC pathotypes.

  10. Contributions of the EMERALD project to assessing and improving microarray data quality.

    Science.gov (United States)

    Beisvåg, Vidar; Kauffmann, Audrey; Malone, James; Foy, Carole; Salit, Marc; Schimmel, Heinz; Bongcam-Rudloff, Erik; Landegren, Ulf; Parkinson, Helen; Huber, Wolfgang; Brazma, Alvis; Sandvik, Arne K; Kuiper, Martin

    2011-01-01

    While minimum information about a microarray experiment (MIAME) standards have helped to increase the value of the microarray data deposited into public databases like ArrayExpress and Gene Expression Omnibus (GEO), limited means have been available to assess the quality of this data or to identify the procedures used to normalize and transform raw data. The EMERALD FP6 Coordination Action was designed to deliver approaches to assess and enhance the overall quality of microarray data and to disseminate these approaches to the microarray community through an extensive series of workshops, tutorials, and symposia. Tools were developed for assessing data quality and used to demonstrate how the removal of poor-quality data could improve the power of statistical analyses and facilitate analysis of multiple joint microarray data sets. These quality metrics tools have been disseminated through publications and through the software package arrayQualityMetrics. Within the framework provided by the Ontology of Biomedical Investigations, ontology was developed to describe data transformations, and software ontology was developed for gene expression analysis software. In addition, the consortium has advocated for the development and use of external reference standards in microarray hybridizations and created the Molecular Methods (MolMeth) database, which provides a central source for methods and protocols focusing on microarray-based technologies.

  11. Fabrication and characterisation of high performance polypyrrole modified microarray sensor for ascorbic acid determination

    Energy Technology Data Exchange (ETDEWEB)

    Samseya, J. [Alagappa University, Karaikudi, Tamil Nadu (India); Srinivasan, R., E-mail: sivarunjan@gmail.com [Central Electro Chemical Research Insititute, Karaikudi, Tamil Nadu (India); Chang, Yu-Tsern; Tsao, Cheng-Wen [Department of Cosmetic Applications, Taoyuan Innovation Institute of Technology, Taiwan (China); Vasantha, V.S. [Madurai Kamaraj University, Madurai, Tamil Nadu (India)

    2013-09-02

    Graphical abstract: -- Highlights: •Gold microelectrode array (Au/MEA) with electrode of 12 μm diameter was fabricated by photolithography technique. •Subsequently, polypyrrole (Ppy) modified gold microarrays sensor (Ppy/Au/MEA) was prepared. •Ppy/Au/MEA used for ascorbic acid determination in the presence of different neurotransmitters. •The micro array exhibited wide linear range, very high sensitivity and very low LOD than the earlier reports. •It was used successfully to test ascorbic acid in different types real samples. -- Abstract: In this study, gold microelectrode array (Au/MEA) with electrode of 12 μm diameter was fabricated by photolithography technique. Subsequently, polypyrrole (Ppy) modified gold microarrays sensor (Ppy/Au/MEA) was prepared by cyclic voltammetry technique. The deposition potential range and number of cycles were optimised in order to get optimum thickness of Ppy film. Scanning Electron Microscope and Atomic Force Microscope investigations reveal that Ppy coating formed at 3 cycles is porous with thickness of 1.5 μm which exhibiting high catalytic current for ascorbic acid (AA) in square wave technique (SWV). In contrast to earlier sensors designs, these Ppy/Au/MEA sensors exhibits lower detection limit (LOD) of 10 nm towards AA at physiological conditions. It also exhibits enhanced sensitivity (2.5 mA cm{sup −2} mM{sup −1}) and long range of linear detection limit from 10 nm to 2.8 mM. In the same way, polypyrrole modified macro Au (Ppy/Au/MA) biosensor was also fabricated and its electro catalytic property towards AA was compared with that of Ppy/Au/MEA. The Ppy/Au/MA exhibits sensitivity of only 0.27 mA cm{sup −2} mM{sup −1}, LOD of 5 μM and linear range of 10 μM to 2.2 mM. Hence, our investigations indicate that the Ppy/Au/MEA could serve as highly sensitive sensor for AA than any of the earlier designs. So, the Ppy/Au/MEA electrode was utilised for determination AA in a wide variety of real samples.

  12. Tumour auto-antibody screening: performance of protein microarrays using SEREX derived antigens

    International Nuclear Information System (INIS)

    Stempfer, René; Weinhäusel, Andreas; Syed, Parvez; Vierlinger, Klemens; Pichler, Rudolf; Meese, Eckart; Leidinger, Petra; Ludwig, Nicole; Kriegner, Albert; Nöhammer, Christa

    2010-01-01

    The simplicity and potential of minimal invasive testing using serum from patients make auto-antibody based biomarkers a very promising tool for use in diagnostics of cancer and auto-immune disease. Although several methods exist for elucidating candidate-protein markers, immobilizing these onto membranes and generating so called macroarrays is of limited use for marker validation. Especially when several hundred samples have to be analysed, microarrays could serve as a good alternative since processing macro membranes is cumbersome and reproducibility of results is moderate. Candidate markers identified by SEREX (serological identification of antigens by recombinant expression cloning) screenings of brain and lung tumour were used for macroarray and microarray production. For microarray production recombinant proteins were expressed in E. coli by autoinduction and purified His-tag (histidine-tagged) proteins were then used for the production of protein microarrays. Protein arrays were hybridized with the serum samples from brain and lung tumour patients. Methods for the generation of microarrays were successfully established when using antigens derived from membrane-based selection. Signal patterns obtained by microarrays analysis of brain and lung tumour patients' sera were highly reproducible (R = 0.92-0.96). This provides the technical foundation for diagnostic applications on the basis of auto-antibody patterns. In this limited test set, the assay provided high reproducibility and a broad dynamic range to classify all brain and lung samples correctly. Protein microarray is an efficient means for auto-antibody-based detection when using SEREX-derived clones expressing antigenic proteins. Protein microarrays are preferred to macroarrays due to the easier handling and the high reproducibility of auto-antibody testing. Especially when using only a few microliters of patient samples protein microarrays are ideally suited for validation of auto

  13. SCK-CEN Genomic Platform: the microarray technology

    International Nuclear Information System (INIS)

    Benotmane, R.

    2006-01-01

    The human body contains approximately 10 14 cells, wherein each one is a nucleus. The nucleus contains 2x23 chromosomes, or two complete sets of the human genome, one set coming from the mother and the other from the father. In principle each set includes 30.000-40.000 genes. If the genome was a book, it would be twenty-three chapters, called chromosomes,each chapter with several thousand stories, called genes. Each story made up of paragraphs, called exons and introns. Each paragraph made up of 3 letter words, called codons. Each word is written with letters called bases (AGCT). But the whole is written in a single very long sentence, which is the DNA molecule or deoxy nucleic acid. The usual state of DNA is two complementary strands intertwined forming a double helix. In the cell, DNA is duplicated during each cell division to ensure the transmission of the genome to the daughter cells. For expression, the DNA is transcribed to messenger RNA. The RNA is edited and finally translated to a protein, each three bases coding for one amino acid. When the whole message is translated, the chain of amino acids folds itself up into a distinctive shape that depends on its sequence. Proteins are the effectors of the genes, and are responsible for all metabolic, hormonal and enzymatic reactions in the cells. The expressed RNA determines the amount of proteins to be produced and subsequently the desired effect (strong or weak) in the cell. The microarray technology aims at quantifying the amount of RNA present in the cell from each expressed gene, and at evaluating the changes of these amounts after exposure of the cell to toxic chemicals, ionising radiation or other stress components. The global picture of expressed genes helps to understand the affected genetic pathways in the cell at the molecular level. The microarray technology is used in the Radiobiology and Microbiology topics to study the effect of ionising radiation on human cells and mouse tissue, as well as the

  14. On the Statics for Micro-Array Data Analysis

    Science.gov (United States)

    Urushibara, Tomoko; Akasaka, Shizu; Ito, Makiko; Suzuki, Tomonori; Miyazaki, Satoru

    2010-01-01

    data, we might get a different result because the distinct definition for micro array data has not been set yet. It means that from the same data we will get different results depending on researchers. We are afraid that this problem will have a big effect on developing new medicines and to progress the next step, like a 2nd screening. So, we suggest that we should have certain guidelines to analyze Micro-Array data validly with statistic method and it will surely be helpful for Micro-Array analysis for medical studies in the future.

  15. Gene expression profiling in cluster headache: a pilot microarray study.

    Science.gov (United States)

    Sjöstrand, Christina; Duvefelt, Kristina; Steinberg, Anna; Remahl, Ingela Nilsson; Waldenlind, Elisabet; Hillert, Jan

    2006-01-01

    Cluster headache (CH) is a primary neurovascular headache disorder characterized by attacks of excruciating pain accompanied by ipsilateral autonomic symptoms. CH pathophysiology is presumed to involve an activation of hypothalamic and trigeminovascular systems, but inflammation and immunological mechanisms have also been hypothesized to be of importance. To identify differentially expressed genes during different clinical phases of CH, assuming that changes of pathophysiological importance would also be seen in peripheral venous blood. Blood samples were drawn at 3 consecutive occasions from 3 episodic CH patients: during attacks, between attacks and in remission, and at 1 occasion from 3 matched controls. Global gene expression was analyzed with microarray tehnology using the Affymetrix Human Genome U133 2.0 Plus GeneChip Set, covering more than 54,000 gene transcripts, corresponding to almost 22,000 genes. Quantitative RT-PCR on S100P gene expression was analyzed in 6 patients and 14 controls. Overall, quite small differences were seen intraindividually and large differences interindividually. However, pairwise comparisons of signal values showed upregulation of several S100 calcium binding proteins; S100A8 (calgranulin A), S100A12 (calgranulin C), and S100P during active phase of the disease compared to remission. Also, annexin A3 (calcium-binding) and ICAM3 showed upregulation. BIRC1 (neuronal apoptosis inhibitory protein), CREB5, HLA-DQA1, and HLA-DQB1 were upregulated in patients compared to controls. The upregulation of S100P during attack versus remission was confirmed by quantitative RT-PCR analysis. The S100A8 and S100A12 proteins are considered markers of non-infectious inflammatory disease, while the function of S100P is still largely unknown. Furthermore, upregulation of HLA-DQ genes in CH patients may also indicate an inflammatory response. Upregulation of these pro-inflammatory genes during the active phase of CH has not formerly been reported. Data

  16. Carbohydrate Microarray Technology Applied to High-Throughput Mapping of Plant Cell Wall Glycans Using Comprehensive Microarray Polymer Profiling (CoMPP).

    Science.gov (United States)

    Kračun, Stjepan Krešimir; Fangel, Jonatan Ulrik; Rydahl, Maja Gro; Pedersen, Henriette Lodberg; Vidal-Melgosa, Silvia; Willats, William George Tycho

    2017-01-01

    Cell walls are an important feature of plant cells and a major component of the plant glycome. They have both structural and physiological functions and are critical for plant growth and development. The diversity and complexity of these structures demand advanced high-throughput techniques to answer questions about their structure, functions and roles in both fundamental and applied scientific fields. Microarray technology provides both the high-throughput and the feasibility aspects required to meet that demand. In this chapter, some of the most recent microarray-based techniques relating to plant cell walls are described together with an overview of related contemporary techniques applied to carbohydrate microarrays and their general potential in glycoscience. A detailed experimental procedure for high-throughput mapping of plant cell wall glycans using the comprehensive microarray polymer profiling (CoMPP) technique is included in the chapter and provides a good example of both the robust and high-throughput nature of microarrays as well as their applicability to plant glycomics.

  17. Assessment of centrifugation using for accelerated immunological microarray analysis for blood cells investigation

    Directory of Open Access Journals (Sweden)

    A. V. Shishkin

    2011-01-01

    Full Text Available Phase of incubation microarray with cell suspension is prolonged when cells are investigated. It takes from 20 to 60 min if cell sedimentation on the surface of microarray is the result of gravity . Decrease of this stage duration is possible due to centrifugation. In th is article influence of centrifugation on results of analysis is considered. Changes of morphological description of cells are estimated when they a re precipitatedwith different acceleration. Also availability of centrifugation using when it is necessary to obtain the high density of cell binding in test regions of microarray if cells concentration in sample is small is demonstrated.

  18. Design of custom oligonucleotide microarrays for single species or interspecies hybrids using Array Oligo Selector.

    Science.gov (United States)

    Caudy, Amy A

    2011-01-01

    New technologies for DNA sequencing have made it feasible to determine the genome sequence of any organism of interest. This sequence is the resource required to create tools for downstream studies, including DNA microarrays. A number of vendors can produce DNA microarrays containing customer-specified sequences, allowing investigators to design and order arrays customized for any species of interest. Freely available, user-friendly computer programs are available for designing microarray probes. These design programs can be used to create probes that distinguish between two related genomes, allowing investigation of gene expression or gene representation in intra- or interspecies hybrids or in samples containing DNA from multiple species.

  19. The Longhorn Array Database (LAD): an open-source, MIAME compliant implementation of the Stanford Microarray Database (SMD).

    Science.gov (United States)

    Killion, Patrick J; Sherlock, Gavin; Iyer, Vishwanath R

    2003-08-20

    The power of microarray analysis can be realized only if data is systematically archived and linked to biological annotations as well as analysis algorithms. The Longhorn Array Database (LAD) is a MIAME compliant microarray database that operates on PostgreSQL and Linux. It is a fully open source version of the Stanford Microarray Database (SMD), one of the largest microarray databases. LAD is available at http://www.longhornarraydatabase.org Our development of LAD provides a simple, free, open, reliable and proven solution for storage and analysis of two-color microarray data.

  20. The Longhorn Array Database (LAD: An Open-Source, MIAME compliant implementation of the Stanford Microarray Database (SMD

    Directory of Open Access Journals (Sweden)

    Iyer Vishwanath R

    2003-08-01

    Full Text Available Abstract Background The power of microarray analysis can be realized only if data is systematically archived and linked to biological annotations as well as analysis algorithms. Description The Longhorn Array Database (LAD is a MIAME compliant microarray database that operates on PostgreSQL and Linux. It is a fully open source version of the Stanford Microarray Database (SMD, one of the largest microarray databases. LAD is available at http://www.longhornarraydatabase.org Conclusions Our development of LAD provides a simple, free, open, reliable and proven solution for storage and analysis of two-color microarray data.

  1. Parallel Assisted Assembly of Multilayer DNA and Protein Nanoparticle Structures Using a CMOS Electronic Array

    Science.gov (United States)

    Heller, Michael J.; Dehlinger, Dietrich A.; Sullivan, Benjamin D.

    2006-09-01

    A CMOS electronic microarray device was used to carry out the rapid parallel assembly of functionalized nanoparticles into multilayer structures. Electronic microarrays produce reconfigurable DC electric fields that allow DNA, proteins as well as charged molecules to be rapidly transported from the bulk solution and addressed to specifically activated sites on the array surface. Such a device was used to carry out the assisted self-assembly DNA, biotin and streptavidin derivatized fluorescent nanoparticles into multilayer structures. Nanoparticle addressing could be carried out in about 15 seconds, and forty depositions of nanoparticles were completed in less than one hour. The final multilayered 3D nanostructures were verified by scanning electron microscopy.

  2. Implementation of tissue microarrays technique for cancer research in Cuba

    Directory of Open Access Journals (Sweden)

    Tania Lahera-Sánchez

    2015-08-01

    Full Text Available The tissue microarray (TMA technique is based on making cylindrical cores from paraffin donor blocks and transfer to a single recipient block. The TMA has revolutionized the field of pathology for the possibility to evaluate multiple samples in one slide. There is no precedent of this subject in Cuba, so the objective of this research was to implement the TMA technique. The concordance of the results obtained by complete section and the TMA were evaluated for this purpose, in the evaluation of the estrogen receptors (ER, progesterone (PR and epidermal growth factor type 2 (HER2 in samples of breast cancer. Forty-five paraffin-embedded samples from women diagnosed with breast cancer at the Institute of Oncology in 2012 were studied. Two TMA blocks were constructed, and subsequently the expression of markers ER, PR and HER2 was determined by immunohistochemistry, in the complete section of tissue and in the TMA. Kappa index was used for concordance analysis. A good concordance was obtained for all three markers (ER k=0.8272; PR k=0.793 and HER2 k=0.716. This study constitutes the first report on the TMA technique in Cuba and shows that it is a valuable tool, suggesting its potential use in translational research and clinical trials on vaccines.

  3. Deciphering cellular morphology and biocompatibility using polymer microarrays

    International Nuclear Information System (INIS)

    Pernagallo, Salvatore; Unciti-Broceta, Asier; DIaz-Mochon, Juan Jose; Bradley, Mark

    2008-01-01

    A quantitative and qualitative analysis of cellular adhesion, morphology and viability is essential in understanding and designing biomaterials such as those involved in implant surfaces or as tissue-engineering scaffolds. As a means to simultaneously perform these studies in a high-throughput (HT) manner, we report a normalized protocol which allows the rapid analysis of a large number of potential cell binding substrates using polymer microarrays and high-content fluorescence microscopy. The method was successfully applied to the discovery of optimal polymer substrates from a 214-member polyurethane library with mouse fibroblast cells (L929), as well as simultaneous evaluation of cell viability and cellular morphology. Analysis demonstrated high biocompatibility of the binding polymers and permitted the identification of several different cellular morphologies, showing that specific polymer interactions may provoke changes in cell shape. In addition, SAR studies showed a clear correspondence between cellular adhesion and polymer structure. The approach can be utilized to perform multiple experiments (up to 1024 single experiments per slide) in a highly reproducible manner, leading to the generation of vast amounts of data in a short time period (48-72 h) while reducing dramatically the quantities of polymers, reagents and cells used

  4. Expression profiling using a hexamer-based universal microarray.

    Science.gov (United States)

    Roth, Matthew E; Feng, Li; McConnell, Kevin J; Schaffer, Paul J; Guerra, Cesar E; Affourtit, Jason P; Piper, Kevin R; Guccione, Lorri; Hariharan, Jayashree; Ford, Maura J; Powell, Stephen W; Krishnaswamy, Harish; Lane, Jennifer; Guccione, Lisa; Intrieri, Gino; Merkel, Jane S; Perbost, Clotilde; Valerio, Anthony; Zolla, Brenda; Graham, Carol D; Hnath, Jonathan; Michaelson, Chris; Wang, Rixin; Ying, Baoge; Halling, Conrad; Parman, Craig E; Raha, Debasish; Orr, Brent; Jedrzkiewicz, Barbara; Liao, Ji; Tevelev, Anton; Mattessich, Martin J; Kranz, David M; Lacey, Michelle; Kaufman, Joseph C; Kim, Junhyong; Latimer, Darin R; Lizardi, Paul M

    2004-04-01

    We describe a transcriptional analysis platform consisting of a universal micro-array system (UMAS) combined with an enzymatic manipulation step that is capable of generating expression profiles from any organism without requiring a priori species-specific knowledge of transcript sequences. The transcriptome is converted to cDNA and processed with restriction endonucleases to generate low-complexity pools (approximately 80-120) of equal length DNA fragments. The resulting material is amplified and detected with the UMAS system, comprising all possible 4,096 (4(6)) DNA hexamers. Ligation to the arrays yields thousands of 14-mer sequence tags. The compendium of signals from all pools in the array-of-universal arrays comprises a full-transcriptome expression profile. The technology was validated by analysis of the galactose response of Saccharomyces cerevisiae, and the resulting profiles showed excellent agreement with the literature and real-time PCR assays. The technology was also used to demonstrate expression profiling from a hybrid organism in a proof-of-concept experiment where a T-cell receptor gene was expressed in yeast.

  5. Probabilistic estimation of microarray data reliability and underlying gene expression

    Directory of Open Access Journals (Sweden)

    Sigvardsson Mikael

    2003-09-01

    Full Text Available Abstract Background The availability of high throughput methods for measurement of mRNA concentrations makes the reliability of conclusions drawn from the data and global quality control of samples and hybridization important issues. We address these issues by an information theoretic approach, applied to discretized expression values in replicated gene expression data. Results Our approach yields a quantitative measure of two important parameter classes: First, the probability P(σ|S that a gene is in the biological state σ in a certain variety, given its observed expression S in the samples of that variety. Second, sample specific error probabilities which serve as consistency indicators of the measured samples of each variety. The method and its limitations are tested on gene expression data for developing murine B-cells and a t-test is used as reference. On a set of known genes it performs better than the t-test despite the crude discretization into only two expression levels. The consistency indicators, i.e. the error probabilities, correlate well with variations in the biological material and thus prove efficient. Conclusions The proposed method is effective in determining differential gene expression and sample reliability in replicated microarray data. Already at two discrete expression levels in each sample, it gives a good explanation of the data and is comparable to standard techniques.

  6. Application of four dyes in gene expression analyses by microarrays

    Directory of Open Access Journals (Sweden)

    van Schooten Frederik J

    2005-07-01

    Full Text Available Abstract Background DNA microarrays are widely used in gene expression analyses. To increase throughput and minimize costs without reducing gene expression data obtained, we investigated whether four mRNA samples can be analyzed simultaneously by applying four different fluorescent dyes. Results Following tests for cross-talk of fluorescence signals, Alexa 488, Alexa 594, Cyanine 3 and Cyanine 5 were selected for hybridizations. For self-hybridizations, a single RNA sample was labelled with all dyes and hybridized on commercial cDNA arrays or on in-house spotted oligonucleotide arrays. Correlation coefficients for all combinations of dyes were above 0.9 on the cDNA array. On the oligonucleotide array they were above 0.8, except combinations with Alexa 488, which were approximately 0.5. Standard deviation of expression differences for replicate spots were similar on the cDNA array for all dye combinations, but on the oligonucleotide array combinations with Alexa 488 showed a higher variation. Conclusion In conclusion, the four dyes can be used simultaneously for gene expression experiments on the tested cDNA array, but only three dyes can be used on the tested oligonucleotide array. This was confirmed by hybridizations of control with test samples, as all combinations returned similar numbers of differentially expressed genes with comparable effects on gene expression.

  7. [HLA-DQA1 genotyping by using oligonucleotide microarrays].

    Science.gov (United States)

    Wang, Tong; Wang, Tian-Jiao; He, Qun; Zhang, Yu-Kui; Ma, Jia-Ming; Hou, Wei-Jian; Wang, Shao-Cheng; Pan, Zhong-Cheng; Zhao, Yu-Jie

    2006-02-01

    In order to fabricate the HLA-DQA1 genotyping chip and develop an integrated, parallel technical platform to type HLA system, a pair of primers and a set of probes were designed according to the sequences of HLA-DQA1 exon 2, where the polymorphism is concentrated. The oligonucleotide chip was made with the methods developed in our laboratory. The target DNA was asymmetrically amplified with the labeled sense primer. The signals were scanned and analyzed after the hybridization between microarray and PCR product. The allele types of the samples were identified. The result was verified by the standard DNA and DNA sequencing. The results showed that the genotyping was successfully carried out in 50 standard DNA samples and 50 clinical samples. Among them, results of the 50 standard DNA samples matched their templates. In the other 50 samples, results of the randomly selected 10 matched their sequencing results except that two of them got the incompletely result. In reproducible tests, the signal reappear rate was 95%. It is concluded that HLA-DQA1 genotyping by using our array system is simple and convenient with satisfied accuracy and reproducibility.

  8. Analysis of Chromothripsis by Combined FISH and Microarray Analysis.

    Science.gov (United States)

    MacKinnon, Ruth N

    2018-01-01

    Fluorescence in situ hybridization (FISH) to metaphase chromosomes, in conjunction with SNP array, array CGH, or whole genome sequencing, can help determine the organization of abnormal genomes after chromothripsis and other types of complex genome rearrangement. DNA microarrays can identify the changes in copy number, but they do not give information on the organization of the abnormal chromosomes, balanced rearrangements, or abnormalities of the centromeres and other regions comprised of highly repetitive DNA. Many of these details can be determined by the strategic use of metaphase FISH. FISH is a single-cell technique, so it can identify low-frequency chromosome abnormalities, and it can determine which chromosome abnormalities occur in the same or different clonal populations. These are important considerations in cancer. Metaphase chromosomes are intact, so information about abnormalities of the chromosome homologues is preserved. Here we describe strategies for working out the organization of highly rearranged genomes by combining SNP array data with various metaphase FISH methods. This approach can also be used to address some of the uncertainties arising from whole genome or mate-pair sequencing data.

  9. An Efficient Ensemble Learning Method for Gene Microarray Classification

    Directory of Open Access Journals (Sweden)

    Alireza Osareh

    2013-01-01

    Full Text Available The gene microarray analysis and classification have demonstrated an effective way for the effective diagnosis of diseases and cancers. However, it has been also revealed that the basic classification techniques have intrinsic drawbacks in achieving accurate gene classification and cancer diagnosis. On the other hand, classifier ensembles have received increasing attention in various applications. Here, we address the gene classification issue using RotBoost ensemble methodology. This method is a combination of Rotation Forest and AdaBoost techniques which in turn preserve both desirable features of an ensemble architecture, that is, accuracy and diversity. To select a concise subset of informative genes, 5 different feature selection algorithms are considered. To assess the efficiency of the RotBoost, other nonensemble/ensemble techniques including Decision Trees, Support Vector Machines, Rotation Forest, AdaBoost, and Bagging are also deployed. Experimental results have revealed that the combination of the fast correlation-based feature selection method with ICA-based RotBoost ensemble is highly effective for gene classification. In fact, the proposed method can create ensemble classifiers which outperform not only the classifiers produced by the conventional machine learning but also the classifiers generated by two widely used conventional ensemble learning methods, that is, Bagging and AdaBoost.

  10. Application of Phenotype Microarray technology to soil microbiology

    Science.gov (United States)

    Mocali, Stefano

    2016-04-01

    It is well established that soil microorganisms are extremely diverse and only a small fraction has been successfully cultured in the laboratory. Furthermore, addressing the functionality of genomes is one of the most important and challenging tasks of today's biology. In particular the ability to link genotypes to corresponding phenotypes is of interest in the reconstruction and biotechnological manipulation of metabolic pathways. High-throughput culture in micro wells provides a method for rapid screening of a wide variety of growth conditions and commercially available plates contain a large number of substrates, nutrient sources, and inhibitors, which can provide an assessment of the phenotype of an organism. Thus, over the last years, Phenotype Microarray (PM) technology has been used to address many specific issues related to the metabolic functionality of microorganisms. However, computational tools that could directly link PM data with the gene(s) of interest followed by the extraction of information on gene-phenotype correlation are still missing. Here potential applications of phenotype arrays to soil microorganisms, use of the plates in stress response studies and for assessment of phenotype of environmental communities are described. Considerations and challenges in data interpretation and visualization, including data normalization, statistics, and curve fitting are also discussed. In particular, here we present DuctApe, a suite that allows the analysis of both genomic sequences and PM data, to find metabolic differences among PM experiments and to correlate them with KEGG pathways and gene presence/absence patterns.

  11. Microarray analysis of microbiota of gingival lesions in noma patients.

    Directory of Open Access Journals (Sweden)

    Antoine Huyghe

    Full Text Available Noma (cancrum oris is a gangrenous disease of unknown etiology affecting the maxillo-facial region of young children in extremely limited resource countries. In an attempt to better understand the microbiological events occurring during this disease, we used phylogenetic and low-density microarrays targeting the 16S rRNA gene to characterize the gingival flora of acute noma and acute necrotizing gingivitis (ANG lesions, and compared them to healthy control subjects of the same geographical and social background. Our observations raise doubts about Fusobacterium necrophorum, a previously suspected causative agent of noma, as this species was not associated with noma lesions. Various oral pathogens were more abundant in noma lesions, notably Atopobium spp., Prevotella intermedia, Peptostreptococcus spp., Streptococcus pyogenes and Streptococcus anginosus. On the other hand, pathogens associated with periodontal diseases such as Aggregatibacter actinomycetemcomitans, Capnocytophaga spp., Porphyromonas spp. and Fusobacteriales were more abundant in healthy controls. Importantly, the overall loss of bacterial diversity observed in noma samples as well as its homology to that of ANG microbiota supports the hypothesis that ANG might be the immediate step preceding noma.

  12. Bioconjugated fluorescent zeolite L nanocrystals as labels in protein microarrays.

    Science.gov (United States)

    Li, Zhen; Luppi, Gianluigi; Geiger, Albert; Josel, Hans-Peter; De Cola, Luisa

    2011-11-18

    Zeolite L nanocrystals, as inorganic host material containing hydrophobic fluorophore N,N'-bis(2,6-dimethylphenyl)perylene-3,4,9,10-tetracarboxylic diimide in the unidirectional channels, are developed as new labels for biosensor systems. The external surface of the particles is modified with carboxylic acid groups for conjugation to primary amines of biomolecules such as antibodies. Anti-digoxigenin (anti-DIG) is selected to be immobilized on zeolite L via N-hydroxysulfosuccinimide ester linker. Together with DIG, it serves as a good universal binding pair for diverse analyte detection owing to the high binding affinity and low background noise. The conjugates are characterized by the dynamic light scattering technique for their hydrodynamic diameters and by enzyme-linked immunosorbent assay for antigen-antibody binding behavior. The characterizations prove that anti-DIG antibodies are successfully immobilized on zeolite L with their binding activities maintained. The microarray fluorescent sandwich immunoassay based on such nanocrystalline labels shows high sensitivity in a thyroid-stimulating hormone assay with the lower detection limit down to the femtomolar range. These new fluorescent labels possess great potential for in vitro diagnostics applications. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  13. Reproducibility of gene expression across generations of Affymetrix microarrays

    Directory of Open Access Journals (Sweden)

    Haslett Judith N

    2003-06-01

    Full Text Available Abstract Background The development of large-scale gene expression profiling technologies is rapidly changing the norms of biological investigation. But the rapid pace of change itself presents challenges. Commercial microarrays are regularly modified to incorporate new genes and improved target sequences. Although the ability to compare datasets across generations is crucial for any long-term research project, to date no means to allow such comparisons have been developed. In this study the reproducibility of gene expression levels across two generations of Affymetrix GeneChips® (HuGeneFL and HG-U95A was measured. Results Correlation coefficients were computed for gene expression values across chip generations based on different measures of similarity. Comparing the absolute calls assigned to the individual probe sets across the generations found them to be largely unchanged. Conclusion We show that experimental replicates are highly reproducible, but that reproducibility across generations depends on the degree of similarity of the probe sets and the expression level of the corresponding transcript.

  14. Common Subcluster Mining in Microarray Data for Molecular Biomarker Discovery.

    Science.gov (United States)

    Sadhu, Arnab; Bhattacharyya, Balaram

    2017-10-11

    Molecular biomarkers can be potential facilitators for detection of cancer at early stage which is otherwise difficult through conventional biomarkers. Gene expression data from microarray experiments on both normal and diseased cell samples provide enormous scope to explore genetic relations of disease using computational techniques. Varied patterns of expressions of thousands of genes at different cell conditions along with inherent experimental error make the task of isolating disease related genes challenging. In this paper, we present a data mining method, common subcluster mining (CSM), to discover highly perturbed genes under diseased condition from differential expression patterns. The method builds heap through superposing near centroid clusters from gene expression data of normal samples and extracts its core part. It, thus, isolates genes exhibiting the most stable state across normal samples and constitute a reference set for each centroid. It performs the same operation on datasets from corresponding diseased samples and isolates the genes showing drastic changes in their expression patterns. The method thus finds the disease-sensitive genesets when applied to datasets of lung cancer, prostrate cancer, pancreatic cancer, breast cancer, leukemia and pulmonary arterial hypertension. In majority of the cases, few new genes are found over and above some previously reported ones. Genes with distinct deviations in diseased samples are prospective candidates for molecular biomarkers of the respective disease.

  15. Application of microarray analysis on computer cluster and cloud platforms.

    Science.gov (United States)

    Bernau, C; Boulesteix, A-L; Knaus, J

    2013-01-01

    Analysis of recent high-dimensional biological data tends to be computationally intensive as many common approaches such as resampling or permutation tests require the basic statistical analysis to be repeated many times. A crucial advantage of these methods is that they can be easily parallelized due to the computational independence of the resampling or permutation iterations, which has induced many statistics departments to establish their own computer clusters. An alternative is to rent computing resources in the cloud, e.g. at Amazon Web Services. In this article we analyze whether a selection of statistical projects, recently implemented at our department, can be efficiently realized on these cloud resources. Moreover, we illustrate an opportunity to combine computer cluster and cloud resources. In order to compare the efficiency of computer cluster and cloud implementations and their respective parallelizations we use microarray analysis procedures and compare their runtimes on the different platforms. Amazon Web Services provide various instance types which meet the particular needs of the different statistical projects we analyzed in this paper. Moreover, the network capacity is sufficient and the parallelization is comparable in efficiency to standard computer cluster implementations. Our results suggest that many statistical projects can be efficiently realized on cloud resources. It is important to mention, however, that workflows can change substantially as a result of a shift from computer cluster to cloud computing.

  16. Bulk segregant analysis using single nucleotide polymorphism microarrays.

    Directory of Open Access Journals (Sweden)

    Anthony Becker

    2011-01-01

    Full Text Available Bulk segregant analysis (BSA using microarrays, and extreme array mapping (XAM have recently been used to rapidly identify genomic regions associated with phenotypes in multiple species. These experiments, however, require the identification of single feature polymorphisms (SFP between the cross parents for each new combination of genotypes, which raises the cost of experiments. The availability of the genomic polymorphism data in Arabidopsis thaliana, coupled with the efficient designs of Single Nucleotide Polymorphism (SNP genotyping arrays removes the requirement for SFP detection and lowers the per array cost, thereby lowering the overall cost per experiment. To demonstrate that these approaches would be functional on SNP arrays and determine confidence intervals, we analyzed hybridizations of natural accessions to the Arabidopsis ATSNPTILE array and simulated BSA or XAM given a variety of gene models, populations, and bulk selection parameters. Our results show a striking degree of correlation between the genotyping output of both methods, which suggests that the benefit of SFP genotyping in context of BSA can be had with the cheaper, more efficient SNP arrays. As a final proof of concept, we hybridized the DNA from bulks of an F2 mapping population of a Sulfur and Selenium ionomics mutant to both the Arabidopsis ATTILE1R and ATSNPTILE arrays, which produced almost identical results. We have produced R scripts that prompt the user for the required parameters and perform the BSA analysis using the ATSNPTILE1 array and have provided them as supplemental data files.

  17. Polysaccharide Microarray Technology for the Detection of Burkholderia Pseudomallei and Burkholderia Mallei Antibodies

    National Research Council Canada - National Science Library

    Parthasarathy, Narayanan; DeShazer, David; England, Marilyn; Waag, David M

    2006-01-01

    .... This polysaccharide array was tested with success for detecting B. pseudomallei and B. mallei serum (human and animal) antibodies. The advantages of this microarray technology over the current serodiagnosis of the above bacterial infections were discussed.

  18. An Efficient Covalent Coating on Glass Slides for Preparation of Optical Oligonucleotide Microarrays

    Directory of Open Access Journals (Sweden)

    Atefeh Pourjahed

    2013-12-01

    The agarose-PLL microarrays had the highest signal (2546 and lowest background signal (205 in hybridization, suggesting that the prepared slides are suitable in analyzing wide concentration range of analytes.

  19. Chromosomal microarrays testing in children with developmental disabilities and congenital anomalies

    Directory of Open Access Journals (Sweden)

    Guillermo Lay‐Son

    2015-03-01

    Conclusion: Chromosomal microarray analysis is a useful and powerful tool for diagnosis of developmental diseases, by allowing accurate diagnosis, improving the diagnosis rate, and discovering new etiologies. The higher cost is a limitation for widespread use in this setting.

  20. Direct labeling of serum proteins by fluorescent dye for antibody microarray.

    Science.gov (United States)

    Klimushina, M V; Gumanova, N G; Metelskaya, V A

    2017-05-06

    Analysis of serum proteome by antibody microarray is used to identify novel biomarkers and to study signaling pathways including protein phosphorylation and protein-protein interactions. Labeling of serum proteins is important for optimal performance of the antibody microarray. Proper choice of fluorescent label and optimal concentration of protein loaded on the microarray ensure good quality of imaging that can be reliably scanned and processed by the software. We have optimized direct serum protein labeling using fluorescent dye Arrayit Green 540 (Arrayit Corporation, USA) for antibody microarray. Optimized procedure produces high quality images that can be readily scanned and used for statistical analysis of protein composition of the serum. Copyright © 2017 Elsevier Inc. All rights reserved.

  1. The Plasmodium falciparum Sexual Development Transcriptome: A Microarray Analysis using Ontology-Based Pattern Identification

    National Research Council Canada - National Science Library

    Young, Jason A; Fivelman, Quinton L; Blair, Peter L; de la Vega, Patricia; Le Roch, Karine G; Zhou, Yingyao; Carucci, Daniel J; Baker, David A; Winzeler, Elizabeth A

    2005-01-01

    ... a full-genome high-density oligonucleotide microarray. The interpretation of this transcriptional data was aided by applying a novel knowledge-based data-mining algorithm termed ontology-based pattern identification (OPI...

  2. Microarray data visualization and analysis with the Longhorn Array Database (LAD).

    Science.gov (United States)

    Killion, Patrick J; Iyer, Vishwanath R

    2004-12-01

    The wide availability and use of DNA microarrays has brought the power of whole-genome functional characterization to a large variety of research environments. Microarrays, however, also introduce significant infrastructural and analytical concerns with respect to the long-term warehousing, annotation, and visualization of immense data sets. The Longhorn Array Database (LAD) is a MIAME-compliant microarray database that operates on PostgreSQL and Linux. It is a free and completely open-source software solution, and provides a systematic and proven environment in which vast experiment sets can be safely archived, securely accessed, biologically annotated, quantitatively analyzed, and visually explored. This unit provides the complete set of information needed to successfully deploy, configure, and use LAD for the purposes of two-color DNA microarray analysis and visualization.

  3. A simple spreadsheet-based, MIAME-supportive format for microarray data: MAGE-TAB

    Directory of Open Access Journals (Sweden)

    White Joseph

    2006-11-01

    Full Text Available Abstract Background Sharing of microarray data within the research community has been greatly facilitated by the development of the disclosure and communication standards MIAME and MAGE-ML by the MGED Society. However, the complexity of the MAGE-ML format has made its use impractical for laboratories lacking dedicated bioinformatics support. Results We propose a simple tab-delimited, spreadsheet-based format, MAGE-TAB, which will become a part of the MAGE microarray data standard and can be used for annotating and communicating microarray data in a MIAME compliant fashion. Conclusion MAGE-TAB will enable laboratories without bioinformatics experience or support to manage, exchange and submit well-annotated microarray data in a standard format using a spreadsheet. The MAGE-TAB format is self-contained, and does not require an understanding of MAGE-ML or XML.

  4. A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

    NARCIS (Netherlands)

    Sontrop, H.M.J.; Moerland, P.D.; Van den Ham, R.; Reinders, M.J.T.; Verhaegh, W.F.J.

    2009-01-01

    Background: Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for

  5. A fully scalable online pre-processing algorithm for short oligonucleotide microarray atlases

    NARCIS (Netherlands)

    Lahti, L.M.; Torrente, A.; Elo, L.L.; Brazma, A.; Rung, J.

    2013-01-01

    Rapid accumulation of large and standardized microarray data collections is opening up novel opportunities for holistic characterization of genome function. The limited scalability of current preprocessing techniques has, however, formed a bottleneck for full utilization of these data resources.

  6. Using pre-existing microarray datasets to increase experimental power: application to insulin resistance.

    Directory of Open Access Journals (Sweden)

    Bernie J Daigle

    2010-03-01

    Full Text Available Although they have become a widely used experimental technique for identifying differentially expressed (DE genes, DNA microarrays are notorious for generating noisy data. A common strategy for mitigating the effects of noise is to perform many experimental replicates. This approach is often costly and sometimes impossible given limited resources; thus, analytical methods are needed which increase accuracy at no additional cost. One inexpensive source of microarray replicates comes from prior work: to date, data from hundreds of thousands of microarray experiments are in the public domain. Although these data assay a wide range of conditions, they cannot be used directly to inform any particular experiment and are thus ignored by most DE gene methods. We present the SVD Augmented Gene expression Analysis Tool (SAGAT, a mathematically principled, data-driven approach for identifying DE genes. SAGAT increases the power of a microarray experiment by using observed coexpression relationships from publicly available microarray datasets to reduce uncertainty in individual genes' expression measurements. We tested the method on three well-replicated human microarray datasets and demonstrate that use of SAGAT increased effective sample sizes by as many as 2.72 arrays. We applied SAGAT to unpublished data from a microarray study investigating transcriptional responses to insulin resistance, resulting in a 50% increase in the number of significant genes detected. We evaluated 11 (58% of these genes experimentally using qPCR, confirming the directions of expression change for all 11 and statistical significance for three. Use of SAGAT revealed coherent biological changes in three pathways: inflammation, differentiation, and fatty acid synthesis, furthering our molecular understanding of a type 2 diabetes risk factor. We envision SAGAT as a means to maximize the potential for biological discovery from subtle transcriptional responses, and we provide it as a

  7. Identification of chromosomal errors in human preimplantation embryos with oligonucleotide DNA microarray.

    Directory of Open Access Journals (Sweden)

    Lifeng Liang

    Full Text Available A previous study comparing the performance of different platforms for DNA microarray found that the oligonucleotide (oligo microarray platform containing 385K isothermal probes had the best performance when evaluating dosage sensitivity, precision, specificity, sensitivity and copy number variations border definition. Although oligo microarray platform has been used in some research fields and clinics, it has not been used for aneuploidy screening in human embryos. The present study was designed to use this new microarray platform for preimplantation genetic screening in the human. A total of 383 blastocysts from 72 infertility patients with either advanced maternal age or with previous miscarriage were analyzed after biopsy and microarray. Euploid blastocysts were transferred to patients and clinical pregnancy and implantation rates were measured. Chromosomes in some aneuploid blastocysts were further analyzed by fluorescence in-situ hybridization (FISH to evaluate accuracy of the results. We found that most (58.1% of the blastocysts had chromosomal abnormalities that included single or multiple gains and/or losses of chromosome(s, partial chromosome deletions and/or duplications in both euploid and aneuploid embryos. Transfer of normal euploid blastocysts in 34 cycles resulted in 58.8% clinical pregnancy and 54.4% implantation rates. Examination of abnormal blastocysts by FISH showed that all embryos had matching results comparing microarray and FISH analysis. The present study indicates that oligo microarray conducted with a higher resolution and a greater number of probes is able to detect not only aneuploidy, but also minor chromosomal abnormalities, such as partial chromosome deletion and/or duplication in human embryos. Preimplantation genetic screening of the aneuploidy by DNA microarray is an advanced technology used to select embryos for transfer and improved embryo implantation can be obtained after transfer of the screened normal

  8. Detection and Identification of Common Food-Borne Viruses with a Tiling Microarray

    OpenAIRE

    Chen, Haifeng; Mammel, Mark; Kulka, Mike; Patel, Isha; Jackson, Scott; Goswami, Biswendu B.

    2011-01-01

    Microarray hybridization based identification of viral genotypes is increasingly assuming importance due to outbreaks of multiple pathogenic viruses affecting humans causing wide-spread morbidity and mortality. Surprisingly, microarray based identification of food-borne viruses, one of the largest groups of pathogenic viruses, causing more than 1.5 billion infections world-wide every year, has lagged behind. Cell-culture techniques are either unavailable or time consuming for routine applicat...

  9. Probe Region Expression Estimation for RNA-Seq Data for Improved Microarray Comparability.

    Science.gov (United States)

    Uziela, Karolis; Honkela, Antti

    2015-01-01

    Rapidly growing public gene expression databases contain a wealth of data for building an unprecedentedly detailed picture of human biology and disease. This data comes from many diverse measurement platforms that make integrating it all difficult. Although RNA-sequencing (RNA-seq) is attracting the most attention, at present, the rate of new microarray studies submitted to public databases far exceeds the rate of new RNA-seq studies. There is clearly a need for methods that make it easier to combine data from different technologies. In this paper, we propose a new method for processing RNA-seq data that yields gene expression estimates that are much more similar to corresponding estimates from microarray data, hence greatly improving cross-platform comparability. The method we call PREBS is based on estimating the expression from RNA-seq reads overlapping the microarray probe regions, and processing these estimates with standard microarray summarisation algorithms. Using paired microarray and RNA-seq samples from TCGA LAML data set we show that PREBS expression estimates derived from RNA-seq are more similar to microarray-based expression estimates than those from other RNA-seq processing methods. In an experiment to retrieve paired microarray samples from a database using an RNA-seq query sample, gene signatures defined based on PREBS expression estimates were found to be much more accurate than those from other methods. PREBS also allows new ways of using RNA-seq data, such as expression estimation for microarray probe sets. An implementation of the proposed method is available in the Bioconductor package "prebs."

  10. The efficacy of microarray screening for autosomal recessive retinitis pigmentosa in routine clinical practice.

    Science.gov (United States)

    van Huet, Ramon A C; Pierrache, Laurence H M; Meester-Smoor, Magda A; Klaver, Caroline C W; van den Born, L Ingeborgh; Hoyng, Carel B; de Wijs, Ilse J; Collin, Rob W J; Hoefsloot, Lies H; Klevering, B Jeroen

    2015-01-01

    To determine the efficacy of multiple versions of a commercially available arrayed primer extension (APEX) microarray chip for autosomal recessive retinitis pigmentosa (arRP). We included 250 probands suspected of arRP who were genetically analyzed with the APEX microarray between January 2008 and November 2013. The mode of inheritance had to be autosomal recessive according to the pedigree (including isolated cases). If the microarray identified a heterozygous mutation, we performed Sanger sequencing of exons and exon-intron boundaries of that specific gene. The efficacy of this microarray chip with the additional Sanger sequencing approach was determined by the percentage of patients that received a molecular diagnosis. We also collected data from genetic tests other than the APEX analysis for arRP to provide a detailed description of the molecular diagnoses in our study cohort. The APEX microarray chip for arRP identified the molecular diagnosis in 21 (8.5%) of the patients in our cohort. Additional Sanger sequencing yielded a second mutation in 17 patients (6.8%), thereby establishing the molecular diagnosis. In total, 38 patients (15.2%) received a molecular diagnosis after analysis using the microarray and additional Sanger sequencing approach. Further genetic analyses after a negative result of the arRP microarray (n = 107) resulted in a molecular diagnosis of arRP (n = 23), autosomal dominant RP (n = 5), X-linked RP (n = 2), and choroideremia (n = 1). The efficacy of the commercially available APEX microarray chips for arRP appears to be low, most likely caused by the limitations of this technique and the genetic and allelic heterogeneity of RP. Diagnostic yields up to 40% have been reported for next-generation sequencing (NGS) techniques that, as expected, thereby outperform targeted APEX analysis.

  11. Correction of technical bias in clinical microarray data improves concordance with known biological information

    DEFF Research Database (Denmark)

    Eklund, Aron Charles; Szallasi, Zoltan Imre

    2008-01-01

    The performance of gene expression microarrays has been well characterized using controlled reference samples, but the performance on clinical samples remains less clear. We identified sources of technical bias affecting many genes in concert, thus causing spurious correlations in clinical data...... sets and false associations between genes and clinical variables. We developed a method to correct for technical bias in clinical microarray data, which increased concordance with known biological relationships in multiple data sets....

  12. A comparison of microarray and MPSS technology platforms for expression analysis of Arabidopsis

    OpenAIRE

    Chen, Junfeng; Agrawal, Vikas; Rattray, Magnus; West, Marilyn AL; St Clair, Dina A; Michelmore, Richard W; Coughlan, Sean J; Meyers, Blake C

    2007-01-01

    Abstract Background Several high-throughput technologies can measure in parallel the abundance of many mRNA transcripts within a sample. These include the widely-used microarray as well as the more recently developed methods based on sequence tag abundances such as the Massively Parallel Signature Sequencing (MPSS) technology. A comparison of microarray and MPSS technologies can help to establish the metrics for data comparisons across these technology platforms and determine some of the fact...

  13. Development, characterization and experimental validation of a cultivated sunflower (Helianthus annuus L. gene expression oligonucleotide microarray.

    Directory of Open Access Journals (Sweden)

    Paula Fernandez

    Full Text Available Oligonucleotide-based microarrays with accurate gene coverage represent a key strategy for transcriptional studies in orphan species such as sunflower, H. annuus L., which lacks full genome sequences. The goal of this study was the development and functional annotation of a comprehensive sunflower unigene collection and the design and validation of a custom sunflower oligonucleotide-based microarray. A large scale EST (>130,000 ESTs curation, assembly and sequence annotation was performed using Blast2GO (www.blast2go.de. The EST assembly comprises 41,013 putative transcripts (12,924 contigs and 28,089 singletons. The resulting Sunflower Unigen Resource (SUR version 1.0 was used to design an oligonucleotide-based Agilent microarray for cultivated sunflower. This microarray includes a total of 42,326 features: 1,417 Agilent controls, 74 control probes for sunflower replicated 10 times (740 controls and 40,169 different non-control probes. Microarray performance was validated using a model experiment examining the induction of senescence by water deficit. Pre-processing and differential expression analysis of Agilent microarrays was performed using the Bioconductor limma package. The analyses based on p-values calculated by eBayes (p<0.01 allowed the detection of 558 differentially expressed genes between water stress and control conditions; from these, ten genes were further validated by qPCR. Over-represented ontologies were identified using FatiScan in the Babelomics suite. This work generated a curated and trustable sunflower unigene collection, and a custom, validated sunflower oligonucleotide-based microarray using Agilent technology. Both the curated unigene collection and the validated oligonucleotide microarray provide key resources for sunflower genome analysis, transcriptional studies, and molecular breeding for crop improvement.

  14. Methods for interpreting lists of affected genes obstained in a DNA microarray experiment

    OpenAIRE

    Hedegaard, J.; Arce, A.M.G.; Bicciato, S.; Bonnet, A.; Buitenhuis, B.; Collado, M.C.; Conley, L.N.; San Cristobal, M.; Ferrari, F.; Garrido, J.J.; Groenen, M.A.M.; Hornshoj, H.; Hulsegge, B.; Jiang, L.; Jimenez-Marin, A.

    2009-01-01

    Background - The aim of this paper was to describe and compare the methods used and the results obtained by the participants in a joint EADGENE (European Animal Disease Genomic Network of Excellence) and SABRE (Cutting Edge Genomics for Sustainable Animal Breeding) workshop focusing on post analysis of microarray data. The participating groups were provided with identical lists of microarray probes, including test statistics for three different contrasts, and the normalised log-ratios for eac...

  15. Systematic review of accuracy of prenatal diagnosis for abnormal chromosome diseases by microarray technology.

    Science.gov (United States)

    Xu, H B; Yang, H; Liu, G; Chen, H

    2014-10-31

    The accuracy of prenatal diagnosis for abnormal chromosome diseases by chromosome microarray technology and karyotyping were compared. A literature search was carried out in the MEDLINE database with the keywords "chromosome" and "karyotype" and "genetic testing" and "prenatal diagnosis" and "oligonucleotide array sequence". The studies obtained were filtered by using the QUADAS tool, and studies conforming to the quality standard were fully analyzed. There was one paper conforming to the QUADAS standards including 4406 gravidas with adaptability syndromes of prenatal diagnosis including elderly parturient women, abnormal structure by type-B ultrasound, and other abnormalities. Microarray technology yielded successful diagnoses in 4340 cases (98.8%), and there was no need for tissue culture in 87.9% of the samples. All aneuploids and non-parallel translocations in 4282 cases of non-chimera identified by karyotyping could be detected using microarray analysis technology, whereas parallel translocations and fetal triploids could not be detected by microarray analysis technology. In the samples with normal karyotyping results, type-B ultrasound showed that 6% of chromosomal deficiencies or chromosome duplications could be detected by microarray technology, and the same abnormal chromosomes were detected in 1.7% of elderly parturient women and samples with positive serology screening results. In the prenatal diagnosis test, compared with karyotyping, microarray technology could identify the extra cell genetic information with clinical significance, aneuploids, and non-parallel translocations; however, its disadvantage is that it could not identify parallel translocations and triploids.

  16. Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.

    Science.gov (United States)

    Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

    2016-09-19

    Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp.

  17. Application of a New Genetic Deafness Microarray for Detecting Mutations in the Deaf in China.

    Science.gov (United States)

    Wu, Hong; Feng, Yong; Jiang, Lu; Pan, Qian; Liu, Yalan; Liu, Chang; He, Chufeng; Chen, Hongsheng; Liu, Xueming; Hu, Chang; Hu, Yiqiao; Mei, Lingyun

    2016-01-01

    The aim of this study was to evaluate the GoldenGate microarray as a diagnostic tool and to elucidate the contribution of the genes on this array to the development of both nonsyndromic and syndromic sensorineural hearing loss in China. We developed a microarray to detect 240 mutations underlying syndromic and nonsyndromic sensorineural hearing loss. The microarray was then used for analysis of 382 patients with nonsyndromic sensorineural hearing loss (including 15 patients with enlarged vestibular aqueduct syndrome), 21 patients with Waardenburg syndrome, and 60 unrelated controls. Subsequently, we analyzed the sensitivity, specificity, and reproducibility of this new approach after Sanger sequencing-based verification, and also determined the contribution of the genes on this array to the development of distinct hearing disorders. The sensitivity and specificity of the microarray chip were 98.73% and 98.34%, respectively. Genetic defects were identified in 61.26% of the patients with nonsyndromic sensorineural hearing loss, and 9 causative genes were identified. The molecular etiology was confirmed in 19.05% and 46.67% of the patients with Waardenburg syndrome and enlarged vestibular aqueduct syndrome, respectively. Our new mutation-based microarray comprises an accurate and comprehensive genetic tool for the detection of sensorineural hearing loss. This microarray-based detection method could serve as a first-pass screening (before next-generation-sequencing screening) for deafness-causing mutations in China.

  18. Fabrication and photoelectrochemical characteristics of the patterned CdS microarrays on indium tin oxide substrates.

    Science.gov (United States)

    Meng, Xu; Lu, Yongjuan; Yang, Baoping; Yi, Gewen; Jia, Junhong

    2010-12-01

    In an effort to investigate the extraordinary photoelectrochemical characteristics of nanostructured CdS thin films in promising photovoltaic device applications, the patterned CdS microarrays with different feature sizes (50, 130, and 250 μm in diameter) were successfully fabricated on indium tin oxide (ITO) glass substrates using the chemical bath deposition method. The ultraviolet lithography process was employed for fabricating patterned octadecyltrichlorosilane (OTS) self-assembled monolayers (SAMs) as the functional organic thin layer template. The results show that the regular and compact patterned CdS microarrays had been deposited onto ITO glass surfaces, with clear edges demarcating the boundaries between the patterned CdS region and substrate under an optimal depositing condition. The microarrays consisted of pure nanocrystalline CdS with average crystallite size of about 10.7 nm. The photocurrent response and the optical adsorption of the patterned CdS microarray thin films increased with the decrease of the feature size, which was due to the increased CdS surface area, as well as the increased optical path length within the patterned CdS thin films, resulting from multiple reflection of incident light. The resistivity values increase with the increase of feature size, due to the increase of the relative amount of gaps between CdS microarrays with increasing the feature size of patterned CdS microarrays.

  19. Evaluation of a gene information summarization system by users during the analysis process of microarray datasets.

    Science.gov (United States)

    Yang, Jianji; Cohen, Aaron; Hersh, William

    2009-02-05

    Summarization of gene information in the literature has the potential to help genomics researchers translate basic research into clinical benefits. Gene expression microarrays have been used to study biomarkers for disease and discover novel types of therapeutics and the task of finding information in journal articles on sets of genes is common for translational researchers working with microarray data. However, manually searching and scanning the literature references returned from PubMed is a time-consuming task for scientists. We built and evaluated an automatic summarizer of information on genes studied in microarray experiments. The Gene Information Clustering and Summarization System (GICSS) is a system that integrates two related steps of the microarray data analysis process: functional gene clustering and gene information gathering. The system evaluation was conducted during the process of genomic researchers analyzing their own experimental microarray datasets. The clusters generated by GICSS were validated by scientists during their microarray analysis process. In addition, presenting sentences in the abstract provided significantly more important information to the users than just showing the title in the default PubMed format. The evaluation results suggest that GICSS can be useful for researchers in genomic area. In addition, the hybrid evaluation method, partway between intrinsic and extrinsic system evaluation, may enable researchers to gauge the true usefulness of the tool for the scientists in their natural analysis workflow and also elicit suggestions for future enhancements. GICSS can be accessed online at: http://ir.ohsu.edu/jianji/index.html.

  20. Application of a New Genetic Deafness Microarray for Detecting Mutations in the Deaf in China.

    Directory of Open Access Journals (Sweden)

    Hong Wu

    Full Text Available The aim of this study was to evaluate the GoldenGate microarray as a diagnostic tool and to elucidate the contribution of the genes on this array to the development of both nonsyndromic and syndromic sensorineural hearing loss in China.We developed a microarray to detect 240 mutations underlying syndromic and nonsyndromic sensorineural hearing loss. The microarray was then used for analysis of 382 patients with nonsyndromic sensorineural hearing loss (including 15 patients with enlarged vestibular aqueduct syndrome, 21 patients with Waardenburg syndrome, and 60 unrelated controls. Subsequently, we analyzed the sensitivity, specificity, and reproducibility of this new approach after Sanger sequencing-based verification, and also determined the contribution of the genes on this array to the development of distinct hearing disorders.The sensitivity and specificity of the microarray chip were 98.73% and 98.34%, respectively. Genetic defects were identified in 61.26% of the patients with nonsyndromic sensorineural hearing loss, and 9 causative genes were identified. The molecular etiology was confirmed in 19.05% and 46.67% of the patients with Waardenburg syndrome and enlarged vestibular aqueduct syndrome, respectively.Our new mutation-based microarray comprises an accurate and comprehensive genetic tool for the detection of sensorineural hearing loss. This microarray-based detection method could serve as a first-pass screening (before next-generation-sequencing screening for deafness-causing mutations in China.

  1. Use of non-amplified RNA samples for microarray analysis of gene expression.

    Directory of Open Access Journals (Sweden)

    Hiroko Sudo

    Full Text Available Demand for high quality gene expression data has driven the development of revolutionary microarray technologies. The quality of the data is affected by the performance of the microarray platform as well as how the nucleic acid targets are prepared. The most common method for target nucleic acid preparation includes in vitro transcription amplification of the sample RNA. Although this method requires a small amount of starting material and is reported to have high reproducibility, there are also technical disadvantages such as amplification bias and the long, laborious protocol. Using RNA derived from human brain, breast and colon, we demonstrate that a non-amplification method, which was previously shown to be inferior, could be transformed to a highly quantitative method with a dynamic range of five orders of magnitude. Furthermore, the correlation coefficient calculated by comparing microarray assays using non-amplified samples with qRT-PCR assays was approximately 0.9, a value much higher than when samples were prepared using amplification methods. Our results were also compared with data from various microarray platforms studied in the MicroArray Quality Control (MAQC project. In combination with micro-columnar 3D-Gene™ microarray, this non-amplification method is applicable to a variety of genetic analyses, including biomarker screening and diagnostic tests for cancer.

  2. mRNA expression in rabbit experimental aneurysms: a study using gene chip microarrays.

    Science.gov (United States)

    Mangrum, W I; Farassati, F; Kadirvel, R; Kolbert, C P; Raghavakaimal, S; Dai, D; Ding, Y H; Grill, D; Khurana, V G; Kallmes, D F

    2007-05-01

    The molecular characteristics of intracranial aneurysms are still poorly documented. A rabbit elastase aneurysm model has been helpful in the evaluation of devices and strategies involved in endovascular treatment of aneurysms. The goal of this project was to document the molecular changes, assessed by gene chip microarrays, associated with the creation of aneurysms in this model compared with the contralateral carotid artery. A microarray of rabbit genes of interest was constructed using rabbit nucleotide sequences from GenBank. Elastase-induced saccular aneurysms were created at the origin of the right common carotid artery in 4 rabbits. Twelve weeks after aneurysm creation, RNA was isolated from the aneurysm as well as the contralateral common carotid artery and used for microarray experiments. Reverse transcription-polymerase chain reaction (RT-PCR) was performed on 1 animal as a confirmatory test. Ninety-six (46%) of 209 genes in the microarray were differentially expressed in the rabbit aneurysm compared with the contralateral common carotid artery. In general, differential gene expression followed specific molecular pathways. Similarities were found between rabbit aneurysms and human intracranial aneurysms, including increased metalloproteinase activity and decreased production of the extracellular matrix. RT-PCR results confirmed the differential expression found by the gene chip microarray. The molecular characteristics of the rabbit elastase-induced saccular aneurysm are described. The rabbit aneurysm model shares some molecular features with human intracranial aneurysms. Future studies can use the rabbit model and the new rabbit gene chip microarray to study the molecular aspects of saccular aneurysms.

  3. Microarray analysis reveals the actual specificity of enrichment media used for food safety assessment.

    Science.gov (United States)

    Kostić, Tanja; Stessl, Beatrix; Wagner, Martin; Sessitsch, Angela

    2011-06-01

    Microbial diagnostic microarrays are tools for simultaneous detection and identification of microorganisms in food, clinical, and environmental samples. In comparison to classic methods, microarray-based systems have the potential for high throughput, parallelism, and miniaturization. High specificity and high sensitivity of detection have been demonstrated. A microbial diagnostic microarray for the detection of the most relevant bacterial food- and waterborne pathogens and indicator organisms was developed and thoroughly validated. The microarray platform based on sequence-specific end labeling of oligonucleotides and the phylogenetically robust gyrB marker gene allowed a highly specific (resolution on genus and/or species level) and sensitive (0.1% relative and 10(4) CFU absolute sensitivity) detection of the target pathogens. In initial challenge studies of the applicability of microarray-based food analysis, we obtained results demonstrating the questionable specificity of standardized culture-dependent microbiological detection methods. Taking into consideration the importance of reliable food safety assessment methods, comprehensive performance assessment is essential. Results demonstrate the potential of this new pathogen diagnostic microarray to evaluate culture-based standard methods in microbiological food analysis.

  4. Gene selection for microarray data classification via subspace learning and manifold regularization.

    Science.gov (United States)

    Tang, Chang; Cao, Lijuan; Zheng, Xiao; Wang, Minhui

    2017-12-19

    With the rapid development of DNA microarray technology, large amount of genomic data has been generated. Classification of these microarray data is a challenge task since gene expression data are often with thousands of genes but a small number of samples. In this paper, an effective gene selection method is proposed to select the best subset of genes for microarray data with the irrelevant and redundant genes removed. Compared with original data, the selected gene subset can benefit the classification task. We formulate the gene selection task as a manifold regularized subspace learning problem. In detail, a projection matrix is used to project the original high dimensional microarray data into a lower dimensional subspace, with the constraint that the original genes can be well represented by the selected genes. Meanwhile, the local manifold structure of original data is preserved by a Laplacian graph regularization term on the low-dimensional data space. The projection matrix can serve as an importance indicator of different genes. An iterative update algorithm is developed for solving the problem. Experimental results on six publicly available microarray datasets and one clinical dataset demonstrate that the proposed method performs better when compared with other state-of-the-art methods in terms of microarray data classification. Graphical Abstract The graphical abstract of this work.

  5. Which Members of the Microbial Communities Are Active? Microarrays

    Science.gov (United States)

    Morris, Brandon E. L.

    Here, we introduce the concept of microarrays, discuss the advantages of several different types of arrays and present a case study that illustrates a targeted-profiling approach to bioremediation of a hydrocarbon-contaminated site in an Arctic environment. The majority of microorganisms in the terrestrial subsurface, particularly those involved in 'heavy oil' formation, reservoir souring or biofouling remain largely uncharacterised (Handelsman, 2004). There is evidence though that these processes are biologically catalysed, including stable isotopic composition of hydrocarbons in oil formations (Pallasser, 2000; Sun et al., 2005), the absence of biodegraded oil from reservoirs warmer than 80°C (Head et al., 2003) or negligible biofouling in the absence of biofilms (Dobretsov et al., 2009; Lewandowski and Beyenal, 2008), and all clearly suggest an important role for microorganisms in the deep biosphere in general and oilfield systems in particular. While the presence of sulphate-reducing bacteria in oilfields was first observed in the early twentieth century (Bastin, 1926), it was only through careful experiments with isolates from oil systems or contaminated environments that unequivocal evidence for hydrocarbon biodegradation under anaerobic conditions was provided (for a review, see Widdel et al., 2006). Work with pure cultures and microbial enrichments also led to the elucidation of the biochemistry of anaerobic aliphatic and aromatic hydrocarbon degradation and the identification of central metabolites and genes involved in the process, e.g. (Callaghan et al., 2008; Griebler et al., 2003; Kropp et al., 2000). This information could then be extrapolated to the environment to monitor degradation processes and determine if in situ microbial populations possessed the potential for contaminant bioremediation, e.g. Parisi et al. (2009). While other methods have also been developed to monitor natural attenuation of hydrocarbons (Meckenstock et al., 2004), we are

  6. Graph-based iterative Group Analysis enhances microarray interpretation

    Directory of Open Access Journals (Sweden)

    Amtmann Anna

    2004-07-01

    Full Text Available Abstract Background One of the most time-consuming tasks after performing a gene expression experiment is the biological interpretation of the results by identifying physiologically important associations between the differentially expressed genes. A large part of the relevant functional evidence can be represented in the form of graphs, e.g. metabolic and signaling pathways, protein interaction maps, shared GeneOntology annotations, or literature co-citation relations. Such graphs are easily constructed from available genome annotation data. The problem of biological interpretation can then be described as identifying the subgraphs showing the most significant patterns of gene expression. We applied a graph-based extension of our iterative Group Analysis (iGA approach to obtain a statistically rigorous identification of the subgraphs of interest in any evidence graph. Results We validated the Graph-based iterative Group Analysis (GiGA by applying it to the classic yeast diauxic shift experiment of DeRisi et al., using GeneOntology and metabolic network information. GiGA reliably identified and summarized all the biological processes discussed in the original publication. Visualization of the detected subgraphs allowed the convenient exploration of the results. The method also identified several processes that were not presented in the original paper but are of obvious relevance to the yeast starvation response. Conclusions GiGA provides a fast and flexible delimitation of the most interesting areas in a microarray experiment, and leads to a considerable speed-up and improvement of the interpretation process.

  7. Identification of different subtypes of breast cancer using tissue microarray.

    Science.gov (United States)

    Munirah, M A; Siti-Aishah, M A; Reena, M Z; Sharifah, N A; Rohaizak, M; Norlia, A; Rafie, M K M; Asmiati, A; Hisham, A; Fuad, I; Shahrun, N S; Das, S

    2011-01-01

    Breast cancer may be classified into luminal A, luminal B, HER2+/ER-, basal-like and normal-like subtypes based on gene expression profiling or immunohistochemical (IHC) characteristics. The main aim of the present study was to classify breast cancer into molecular subtypes based on immunohistochemistry findings and correlate the subtypes with clinicopathological factors. Two hundred and seventeen primary breast carcinomas tumor tissues were immunostained for ER, PR, HER2, CK5/6, EGFR, CK8/18, p53 and Ki67 using tissue microarray technique. All subtypes were significantly associated with Malay ethnic background (p=0.035) compared to other racial origins. The most common subtypes of breast cancers were luminal A and was significantly associated with low histological grade (p<0.000) and p53 negativity (p=0.003) compared to HER2+/ER-, basal-like and normal-like subtypes with high histological grade (p<0.000) and p53 positivity (p=0.003). Luminal B subtype had the smallest mean tumor size (p=0.009) and also the highest mean number of lymph nodes positive (p=0.032) compared to other subtypes. All markers except EGFR and Ki67 were significantly associated with the subtypes. The most common histological type was infiltrating ductal carcinoma, NOS. Majority of basal-like subtype showed comedo-type necrosis (68.8%) and infiltrative margin (81.3%). Our studies suggest that IHC can be used to identify the different subtypes of breast cancer and all subtypes were significantly associated with race, mean tumor size, mean number of lymph node positive, histological grade and all immunohistochemical markers except EGFR and Ki67.

  8. EST and microarray analysis of horn development in Onthophagus beetles

    Directory of Open Access Journals (Sweden)

    Tang Zuojian

    2009-10-01

    Full Text Available Abstract Background The origin of novel traits and their subsequent diversification represent central themes in evo-devo and evolutionary ecology. Here we explore the genetic and genomic basis of a class of traits that is both novel and highly diverse, in a group of organisms that is ecologically complex and experimentally tractable: horned beetles. Results We developed two high quality, normalized cDNA libraries for larval and pupal Onthophagus taurus and sequenced 3,488 ESTs that assembled into 451 contigs and 2,330 singletons. We present the annotation and a comparative analysis of the conservation of the sequences. Microarrays developed from the combined libraries were then used to contrast the transcriptome of developing primordia of head horns, prothoracic horns, and legs. Our experiments identify a first comprehensive list of candidate genes for the evolution and diversification of beetle horns. We find that developing horns and legs show many similarities as well as important differences in their transcription profiles, suggesting that the origin of horns was mediated partly, but not entirely, by the recruitment of genes involved in the formation of more traditional appendages such as legs. Furthermore, we find that horns developing from the head and prothorax differ in their transcription profiles to a degree that suggests that head and prothoracic horns are not serial homologs, but instead may have evolved independently from each other. Conclusion We have laid the foundation for a systematic analysis of the genetic basis of horned beetle development and diversification with the potential to contribute significantly to several major frontiers in evolutionary developmental biology.

  9. Meta-analysis of gene expression microarrays with missing replicates

    Directory of Open Access Journals (Sweden)

    Leckie Christopher

    2011-03-01

    Full Text Available Abstract Background Many different microarray experiments are publicly available today. It is natural to ask whether different experiments for the same phenotypic conditions can be combined using meta-analysis, in order to increase the overall sample size. However, some genes are not measured in all experiments, hence they cannot be included or their statistical significance cannot be appropriately estimated in traditional meta-analysis. Nonetheless, these genes, which we refer to as incomplete genes, may also be informative and useful. Results We propose a meta-analysis framework, called "Incomplete Gene Meta-analysis", which can include incomplete genes by imputing the significance of missing replicates, and computing a meta-score for every gene across all datasets. We demonstrate that the incomplete genes are worthy of being included and our method is able to appropriately estimate their significance in two groups of experiments. We first apply the Incomplete Gene Meta-analysis and several comparable methods to five breast cancer datasets with an identical set of probes. We simulate incomplete genes by randomly removing a subset of probes from each dataset and demonstrate that our method consistently outperforms two other methods in terms of their false discovery rate. We also apply the methods to three gastric cancer datasets for the purpose of discriminating diffuse and intestinal subtypes. Conclusions Meta-analysis is an effective approach that identifies more robust sets of differentially expressed genes from multiple studies. The incomplete genes that mainly arise from the use of different platforms may also have statistical and biological importance but are ignored or are not appropriately involved by previous studies. Our Incomplete Gene Meta-analysis is able to incorporate the incomplete genes by estimating their significance. The results on both breast and gastric cancer datasets suggest that the highly ranked genes and associated GO

  10. Expanding the substantial interactome of NEMO using protein microarrays.

    LENUS (Irish Health Repository)

    Fenner, Beau J

    2010-01-01

    Signal transduction by the NF-kappaB pathway is a key regulator of a host of cellular responses to extracellular and intracellular messages. The NEMO adaptor protein lies at the top of this pathway and serves as a molecular conduit, connecting signals transmitted from upstream sensors to the downstream NF-kappaB transcription factor and subsequent gene activation. The position of NEMO within this pathway makes it an attractive target from which to search for new proteins that link NF-kappaB signaling to additional pathways and upstream effectors. In this work, we have used protein microarrays to identify novel NEMO interactors. A total of 112 protein interactors were identified, with the most statistically significant hit being the canonical NEMO interactor IKKbeta, with IKKalpha also being identified. Of the novel interactors, more than 30% were kinases, while at least 25% were involved in signal transduction. Binding of NEMO to several interactors, including CALB1, CDK2, SAG, SENP2 and SYT1, was confirmed using GST pulldown assays and coimmunoprecipitation, validating the initial screening approach. Overexpression of CALB1, CDK2 and SAG was found to stimulate transcriptional activation by NF-kappaB, while SYT1 overexpression repressed TNFalpha-dependent NF-kappaB transcriptional activation in human embryonic kidney cells. Corresponding with this finding, RNA silencing of CDK2, SAG and SENP2 reduced NF-kappaB transcriptional activation, supporting a positive role for these proteins in the NF-kappaB pathway. The identification of a host of new NEMO interactors opens up new research opportunities to improve understanding of this essential cell signaling pathway.

  11. Tissue microarray use for immunohistochemical study of ameloblastoma.

    Science.gov (United States)

    Neves-Silva, Rodrigo; Fonseca, Felipe Paiva; de Jesus, Adriana Souza; Pontes, Hélder Antônio Rebelo; Rocha, André Caroli; Brandão, Thais Bianca; Vargas, Pablo Agustin; Lopes, Márcio Ajudarte; de Almeida, Oslei Paes; Santos-Silva, Alan Roger

    2016-10-01

    Ameloblastoma is a locally aggressive odontogenic tumor with high rates of recurrence. To better understand the molecular basis of ameloblastoma, tissue microarray (TMA) may represent a useful tool. However, despite TMA has been considered a high-throughput technique for different human neoplasms, it remains to be validated in the ameloblastoma context. Therefore, the objective of this study was to validate TMA for immunohistochemical study of ameloblastoma, determining its most appropriate design. Forty cases of ameloblastoma were manually distributed in two TMA blocks assembled in triplicate containing 1.0- and 2.0-mm cores (20 cases each). Immunohistochemistry for cytokeratins 14 and 19, and Bcl-2 and Ki-67 was performed, and semiquantitative analysis was performed. Results obtained with TMA sections were compared to their corresponding conventional whole-section slides (CWSS). Kappa statistical test demonstrated that both 1.0- and 2.0-mm cores assessed as duplicate or triplicate significantly correlated with CWSS, with higher levels obtained using Ki67 (k = 0.98, 0.97, 0.88, 0.87) and CK19 (k = 0.62, 0.58, 0.85, 0.85). There was no significant difference between 1.0- and 2.0-mm cores, and between duplicate and triplicate values. 1.0-mm TMA showed a higher index of core loss (33.74% vs. 4.99%). Using a manual arrayer, it was demonstrated that 1.0-mm TMA arranged in duplicate is a valid method for ameloblastoma immunohistochemical study with satisfactory levels of agreement between TMA cylinders and CWSS. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  12. Regularized binormal ROC method in disease classification using microarray data

    Directory of Open Access Journals (Sweden)

    Huang Jian

    2006-05-01

    Full Text Available Abstract Background An important application of microarrays is to discover genomic biomarkers, among tens of thousands of genes assayed, for disease diagnosis and prognosis. Thus it is of interest to develop efficient statistical methods that can simultaneously identify important biomarkers from such high-throughput genomic data and construct appropriate classification rules. It is also of interest to develop methods for evaluation of classification performance and ranking of identified biomarkers. Results The ROC (receiver operating characteristic technique has been widely used in disease classification with low dimensional biomarkers. Compared with the empirical ROC approach, the binormal ROC is computationally more affordable and robust in small sample size cases. We propose using the binormal AUC (area under the ROC curve as the objective function for two-sample classification, and the scaled threshold gradient directed regularization method for regularized estimation and biomarker selection. Tuning parameter selection is based on V-fold cross validation. We develop Monte Carlo based methods for evaluating the stability of individual biomarkers and overall prediction performance. Extensive simulation studies show that the proposed approach can generate parsimonious models with excellent classification and prediction performance, under most simulated scenarios including model mis-specification. Application of the method to two cancer studies shows that the identified genes are reasonably stable with satisfactory prediction performance and biologically sound implications. The overall classification performance is satisfactory, with small classification errors and large AUCs. Conclusion In comparison to existing methods, the proposed approach is computationally more affordable without losing the optimality possessed by the standard ROC method.

  13. Effect of normalization on significance testing for oligonucleotide microarrays.

    Science.gov (United States)

    Parrish, Rudolph S; Spencer, Horace J

    2004-08-01

    Normalization techniques are used to reduce variation among gene expression measurements in oligonucleotide microarrays in an effort to improve the quality of the data and the power of significance tests for detecting differential expression. Of several such proposed methods, two that have commonly been employed include median-interquartile range normalization and quantile normalization. The median-IQR method applied directly to fold-changes for paired data also was considered. Two methods for calculating gene expression values include the MAS 5.0 algorithm [Affymetrix. (2002). Statistical Algorithms Description Document. Santa Clara, CA: Affymetrix, Inc. http://www.affymetrix.com/support/technical/whitepapers/sadd-whitepaper.pdf] and the RMA method [Irizarry, R. A., Bolstad, B. M., Collin, F., Cope, L. M., Hobbs, B., Speed, T. P. (2003a). Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Res. 31(4,e15); Irizarry, R. A., Hobbs, B., Collin, F., Beazer-Barclay, Y. D., Antonellis, K. J., Scherf, U., Speed, T. P. (2003b). Exploration, normalization, and summaries of high density oligonucleotide array probe-level data. Biostatistics 4(2):249-264; Irizarry, R. A., Gautier, L., Cope, L. (2003c). An R package for analysis of Affymetrix oligonucleotide arrays. In: Parmigiani, R. I. G., Garrett, E. S., Ziegler, S., eds. The Analysis of Gene Expression Data: Methods and Software. Berlin: Springer, pp. 102-119]. In considering these methods applied to a prostate cancer data set derived from paired samples on normal and tumor tissue, it is shown that normalization methods may lead to substantial inflation of the number of genes identified by paired-t significance tests even after adjustment for multiple testing. This is shown to be due primarily to an unintended effect that normalization has on the experimental error variance. The impact appears to be greater in the RMA method compared to the MAS 5.0 algorithm and for quantile normalization compared to median

  14. Electronic Cigarettes

    Science.gov (United States)

    ... New FDA Regulations Text Size: A A A Electronic Cigarettes Electronic cigarettes (e-cigarettes) are battery operated products designed to ... more about: The latest news and events about electronic cigarettes on this FDA page Electronic cigarette basics on ...

  15. Electronic technology

    International Nuclear Information System (INIS)

    Kim, Jin Su

    2010-07-01

    This book is composed of five chapters, which introduces electronic technology about understanding of electronic, electronic component, radio, electronic application, communication technology, semiconductor on its basic, free electron and hole, intrinsic semiconductor and semiconductor element, Diode such as PN junction diode, characteristic of junction diode, rectifier circuit and smoothing circuit, transistor on structure of transistor, characteristic of transistor and common emitter circuit, electronic application about electronic equipment, communication technology and education, robot technology and high electronic technology.

  16. A new approach to species determination for yeast strains: DNA microarray-based comparative genomic hybridization using a yeast DNA microarray with 6000 genes.

    Science.gov (United States)

    Watanabe, Takahito; Murata, Yoshinori; Oka, Syuichi; Iwahashi, Hitoshi

    2004-03-01

    DNA-DNA hybridization is known as the superior method in the elucidation of relationships between closely related taxa, such as species and strain. For species determination we propose a new DNA-DNA hybridization method: the DNA microarray-based comparative genomic hybridization (CGH) method, using a yeast DNA microarray with approximately 6000 genes. The genome from a yeast strain as a sample strain (Sample) was labelled with Cy3-dye and hybridized to a single DNA microarray, together with the Cy5-labelled genome of S. cerevisiae S288C as a reference strain (Reference). The log2 ratio values [log2[Cy3(Sample)/Cy5(Reference)]: Ratio] of signal intensities of all the gene spots were estimated and divided into the following groups: Ratio < or = -1; -1 < Ratio < 1; 1 < or = Ratio. The hybridization profiles of the genomes of type strains belonging to the genus Saccharomyces were significantly different from that of S. cerevisiae S288C. The Ratio-based grouping allowed us to discriminate between some species from S. cerevisiae more clearly. Furthermore, cluster analysis discriminated between closely related species and strains. Using this method, we were able to not only perform species determination but also to obtain information on alternation in gene copy number of such gene amplifications and deletions with single-gene resolution. These observations indicated that DNA microarray-based CGH is a powerful system for species determination and comparative genome analysis. Copyright 2004 John Wiley & Sons, Ltd.

  17. A gene expression microarray for Nicotiana benthamiana based on de novo transcriptome sequence assembly.

    Science.gov (United States)

    Goralski, Michal; Sobieszczanska, Paula; Obrepalska-Steplowska, Aleksandra; Swiercz, Aleksandra; Zmienko, Agnieszka; Figlerowicz, Marek

    2016-01-01

    Nicotiana benthamiana has been widely used in laboratories around the world for studying plant-pathogen interactions and posttranscriptional gene expression silencing. Yet the exploration of its transcriptome has lagged behind due to the lack of both adequate sequence information and genome-wide analysis tools, such as DNA microarrays. Despite the increasing use of high-throughput sequencing technologies, the DNA microarrays still remain a popular gene expression tool, because they are cheaper and less demanding regarding bioinformatics skills and computational effort. We designed a gene expression microarray with 103,747 60-mer probes, based on two recently published versions of N. benthamiana transcriptome (v.3 and v.5). Both versions were reconstructed from RNA-Seq data of non-strand-specific pooled-tissue libraries, so we defined the sense strand of the contigs prior to designing the probe. To accomplish this, we combined a homology search against Arabidopsis thaliana proteins and hybridization to a test 244k microarray containing pairs of probes, which represented individual contigs. We identified the sense strand in 106,684 transcriptome contigs and used this information to design an Nb-105k microarray on an Agilent eArray platform. Following hybridization of RNA samples from N. benthamiana roots and leaves we demonstrated that the new microarray had high specificity and sensitivity for detection of differentially expressed transcripts. We also showed that the data generated with the Nb-105k microarray may be used to identify incorrectly assembled contigs in the v.5 transcriptome, by detecting inconsistency in the gene expression profiles, which is indicated using multiple microarray probes that match the same v.5 primary transcripts. We provided a complete design of an oligonucleotide microarray that may be applied to the research of N. benthamiana transcriptome. This, in turn, will allow the N. benthamiana research community to take full advantage of

  18. Simplified microarray system for simultaneously detecting rifampin, isoniazid, ethambutol, and streptomycin resistance markers in Mycobacterium tuberculosis.

    Science.gov (United States)

    Linger, Yvonne; Kukhtin, Alexander; Golova, Julia; Perov, Alexander; Lambarqui, Amine; Bryant, Lexi; Rudy, George B; Dionne, Kim; Fisher, Stefanie L; Parrish, Nicole; Chandler, Darrell P

    2014-06-01

    We developed a simplified microarray test for detecting and identifying mutations in rpoB, katG, inhA, embB, and rpsL and compared the analytical performance of the test to that of phenotypic drug susceptibility testing (DST). The analytical sensitivity was estimated to be at least 110 genome copies per amplification reaction. The microarray test correctly detected 95.2% of mutations for which there was a sequence-specific probe on the microarray and 100% of 96 wild-type sequences. In a blinded analysis of 153 clinical isolates, microarray sensitivity for first-line drugs relative to phenotypic DST (true resistance) was 100% for rifampin (RIF) (14/14), 90.0% for isoniazid (INH) (36/40), 70% for ethambutol (EMB) (7/10), and 89.1% (57/64) combined. Microarray specificity (true susceptibility) for first-line agents was 95.0% for RIF (132/139), 98.2% for INH (111/113), and 98.6% for EMB (141/143). Overall microarray specificity for RIF, INH, and EMB combined was 97.2% (384/395). The overall positive and negative predictive values for RIF, INH, and EMB combined were 84.9% and 98.3%, respectively. For the second-line drug streptomycin (STR), overall concordance between the agar proportion method and microarray analysis was 89.5% (137/153). Sensitivity was 34.8% (8/23) because of limited microarray coverage for STR-conferring mutations, and specificity was 99.2% (129/130). All false-susceptible discrepant results were a consequence of DNA mutations that are not represented by a specific microarray probe. There were zero invalid results from 220 total tests. The simplified microarray system is suitable for detecting resistance-conferring mutations in clinical M. tuberculosis isolates and can now be used for prospective trials or integrated into an all-in-one, closed-amplicon consumable. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

  19. The Electron

    Energy Technology Data Exchange (ETDEWEB)

    Thomson, George

    1972-01-01

    Electrons are elementary particles of atoms that revolve around and outside the nucleus and have a negative charge. This booklet discusses how electrons relate to electricity, some applications of electrons, electrons as waves, electrons in atoms and solids, the electron microscope, among other things.

  20. Hard electronics; Hard electronics

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-03-01

    Hard material technologies were surveyed to establish the hard electronic technology which offers superior characteristics under hard operational or environmental conditions as compared with conventional Si devices. The following technologies were separately surveyed: (1) The device and integration technologies of wide gap hard semiconductors such as SiC, diamond and nitride, (2) The technology of hard semiconductor devices for vacuum micro- electronics technology, and (3) The technology of hard new material devices for oxides. The formation technology of oxide thin films made remarkable progress after discovery of oxide superconductor materials, resulting in development of an atomic layer growth method and mist deposition method. This leading research is expected to solve such issues difficult to be easily realized by current Si technology as high-power, high-frequency and low-loss devices in power electronics, high temperature-proof and radiation-proof devices in ultimate electronics, and high-speed and dense- integrated devices in information electronics. 432 refs., 136 figs., 15 tabs.

  1. Microarray long oligo probe designing for Escherichia coli: an in-silico DNA marker extraction.

    Science.gov (United States)

    Behzadi, Payam; Najafi, Ali; Behzadi, Elham; Ranjbar, Reza

    2016-01-01

    Urinary tract infections are predominant diseases which may be caused by different pathogenic microorganisms, particularly Escherichia coli (E.coli). DNA microarray technology is an accurate, rapid, sensitive, and specific diagnostic tool which may lead to definite diagnosis and treatment of several infectious diseases. DNA microarray is a multi-process method in which probe designing plays an important. Therefore, the authors of the present study have tried to design a range of effective and proper long oligo microarray probes for detection and identification of different strains of pathogenic E.coli and in particular, uropathogenic E.coli (UPEC). E.coli O26 H11 11368 uid41021 was selected as the standard strain for probe designing. This strain encompasses the largest nucleotide sequence and the most number of genes among other pathogenic strains of E.coli. For performing this in silico survey, NCBI database, GReview Server, PanSeq Server, Oligoanalyzer tool, and AlleleID 7.7 were used to design accurate, appropriate, effective, and flexible long oligo microarray probes. Moreover, the genome of E.coli and its closely related microorganisms were compared. In this study, 15 long oligo microarray probes were designed for detecting and identifying different strains of E.coli such as UPEC. These probes possessed the best physico-chemical characteristics. The functional and structural properties of the designed probes were recognized by practical tools and softwares. The use of reliable advanced technologies and methodologies for probe designing guarentees the high quality of microarray probes and makes DNA microarray technology more flexible and an effective diagnostic technique.

  2. High-resolution microarray in the assessment of fetal anomalies detected by ultrasound.

    Science.gov (United States)

    Charan, Poonam; Woodrow, Nicole; Walker, Sue P; Ganesamoorthy, Devika; McGillivray, George; Palma-Dias, Ricardo

    2014-02-01

    The main aim of this study was to determine the feasibility of using high-resolution microarray to assist with prenatal diagnosis of ultrasound-detected fetal abnormality and to describe the frequency of abnormal results in different categories of fetal anomalies. Prospective cross-sectional study was conducted on women diagnosed with a fetal anomaly (ies) between February 2009 and December 2011 who were offered testing by microarray analysis (Affymetrix 2.7M SNP) and fluorescent in situ hybridisation (FISH) instead of standard karyotyping. Fetal anomalies were categorised according to organ system involvement. One hundred and eighteen women consented to testing with microarray. Eleven of one hundred eighteen (9.3%) cases had aneuploidy detected by FISH. Of the remaining 107, 23 (21.5%) had an abnormality detected on microarray, only three of which would have been detected using the combination of six-probe FISH and banded karyotype. The maximum expected yield for six-probe FISH and karyotype was thus 14/118 (11.8%), compared to 34/118 (28.8%), P microarray, 10 (43%) were pathogenic, six (26%) were long continuous stretches of homozygosity and seven (30%) were of uncertain significance. The maximum yield was in cases with cardiovascular (100%); multiple (40%); central nervous system (CNS) (25%) and skeletal (9%) abnormalities. This study has confirmed the feasibility of translation of microarray into clinical practice. 11.8% (14/118) of the cases would have a genetic basis of an abnormality with a FISH and banded karyotype. This figure is approximately tripled to 28.8% (34/118) if we offer FISH and microarray. High yield for imbalances are multiple, cardiovascular, CNS and skeletal abnormalities. © 2014 The Royal Australian and New Zealand College of Obstetricians and Gynaecologists.

  3. RNA-seq and microarray complement each other in transcriptome profiling

    Science.gov (United States)

    2012-01-01

    Background RNA-seq and microarray are the two popular methods employed for genome-wide transcriptome profiling. Current comparison studies have shown that transcriptome quantified by these two methods correlated well. However, none of them have addressed if they complement each other, considering the strengths and the limitations inherent with them. The pivotal requirement to address this question is the knowledge of a well known data set. In this regard, HrpX regulome from pathogenic bacteria serves as an ideal choice as the target genes of HrpX transcription factor are well studied due to their central role in pathogenicity. Results We compared the performance of RNA-seq and microarray in their ability to detect known HrpX target genes by profiling the transcriptome from the wild-type and the hrpX mutant strains of γ-Proteobacterium Xanthomonas citri subsp. citri. Our comparative analysis indicated that gene expression levels quantified by RNA-seq and microarray well-correlated both at absolute as well as relative levels (Spearman correlation-coefficient, rs > 0.76). Further, the expression levels quantified by RNA-seq and microarray for the significantly differentially expressed genes (DEGs) also well-correlated with qRT-PCR based quantification (rs = 0.58 to 0.94). Finally, in addition to the 55 newly identified DEGs, 72% of the already known HrpX target genes were detected by both RNA-seq and microarray, while, the remaining 28% could only be detected by either one of the methods. Conclusions This study has significantly advanced our understanding of the regulome of the critical transcriptional factor HrpX. RNA-seq and microarray together provide a more comprehensive picture of HrpX regulome by uniquely identifying new DEGs. Our study demonstrated that RNA-seq and microarray complement each other in transcriptome profiling. PMID:23153100

  4. Identifying Cancer Biomarkers From Microarray Data Using Feature Selection and Semisupervised Learning.

    Science.gov (United States)

    Chakraborty, Debasis; Maulik, Ujjwal

    2014-01-01

    Microarrays have now gone from obscurity to being almost ubiquitous in biological research. At the same time, the statistical methodology for microarray analysis has progressed from simple visual assessments of results to novel algorithms for analyzing changes in expression profiles. In a micro-RNA (miRNA) or gene-expression profiling experiment, the expression levels of thousands of genes/miRNAs are simultaneously monitored to study the effects of certain treatments, diseases, and developmental stages on their expressions. Microarray-based gene expression profiling can be used to identify genes, whose expressions are changed in response to pathogens or other organisms by comparing gene expression in infected to that in uninfected cells or tissues. Recent studies have revealed that patterns of altered microarray expression profiles in cancer can serve as molecular biomarkers for tumor diagnosis, prognosis of disease-specific outcomes, and prediction of therapeutic responses. Microarray data sets containing expression profiles of a number of miRNAs or genes are used to identify biomarkers, which have dysregulation in normal and malignant tissues. However, small sample size remains a bottleneck to design successful classification methods. On the other hand, adequate number of microarray data that do not have clinical knowledge can be employed as additional source of information. In this paper, a combination of kernelized fuzzy rough set (KFRS) and semisupervised support vector machine (S(3)VM) is proposed for predicting cancer biomarkers from one miRNA and three gene expression data sets. Biomarkers are discovered employing three feature selection methods, including KFRS. The effectiveness of the proposed KFRS and S(3)VM combination on the microarray data sets is demonstrated, and the cancer biomarkers identified from miRNA data are reported. Furthermore, biological significance tests are conducted for miRNA cancer biomarkers.

  5. THEME: a web tool for loop-design microarray data analysis.

    Science.gov (United States)

    Chen, Chaang-Ray; Shu, Wun-Yi; Tsai, Min-Lung; Cheng, Wei-Chung; Hsu, Ian C

    2012-02-01

    A number of recent studies have shown that loop-design is more efficient than reference control design. Data analysis for loop-design microarray experiments is commonly undertaken using linear models and statistical tests. These techniques require specialized knowledge in statistical programming. However, limited loop-design web-based tools are available. We have developed the THEME (Tsing Hua Engine of Microarray Experiment) that exploits all necessary data analysis tools for loop-design microarray studies. THEME allows users to construct linear models and to apply multiple user-defined statistical tests of hypotheses for detection of DEG (differentially expressed genes). Users can modify entries of design matrix for experimental design as well as that of contrast matrix for statistical tests of hypotheses. The output of multiple user-defined statistical tests of hypotheses, DEG lists, can be cross-validated. The web platform provides data assessment and visualization tools that significantly assist users when evaluating the performance of microarray experimental procedures. THEME is also a MIAME (Minimal Information About a Microarray Experiment) compliant system, which enables users to export formatted files for GEO (Gene Expression Omnibus) submission. THEME offers comprehensive web services to biologists for data analysis of loop-design microarray experiments. This web-based resource is especially useful for core facility service as well as collaboration projects when researchers are not at the same site. Data analysis procedures, starting from uploading raw data files to retrieving DEG lists, can be flexibly operated with natural workflows. These features make THEME a reliable and powerful on-line system for data analysis of loop-design microarrays. The THEME server is available at http://metadb.bmes.nthu.edu.tw/theme/. Copyright © 2011 Elsevier Ltd. All rights reserved.

  6. Inter-Platform comparability of microarrays in acute lymphoblastic leukemia

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    Mintz Michelle

    2004-09-01

    for prognostic variables. We have also been able to validate the gene predictors with high accuracy using an independent dataset generated on cDNA arrays. Conclusion Interarray comparisons such as this one will further enhance the ability to integrate data from several generations of microarray experiments and will help to break down barriers to the assimilation of existing datasets into a comprehensive data pool.

  7. Characterization of influenza vaccine immunogenicity using influenza antigen microarrays.

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    Jordan V Price

    Full Text Available Existing methods to measure influenza vaccine immunogenicity prohibit detailed analysis of epitope determinants recognized by immunoglobulins. The development of highly multiplex proteomics platforms capable of capturing a high level of antibody binding information will enable researchers and clinicians to generate rapid and meaningful readouts of influenza-specific antibody reactivity.We developed influenza hemagglutinin (HA whole-protein and peptide microarrays and validated that the arrays allow detection of specific antibody reactivity across a broad dynamic range using commercially available antibodies targeted to linear and conformational HA epitopes. We derived serum from blood draws taken from 76 young and elderly subjects immediately before and 28±7 days post-vaccination with the 2008/2009 trivalent influenza vaccine and determined the antibody reactivity of these sera to influenza array antigens.Using linear regression and correcting for multiple hypothesis testing by the Benjamini and Hochberg method of permutations over 1000 resamplings, we identified antibody reactivity to influenza whole-protein and peptide array features that correlated significantly with age, H1N1, and B-strain post-vaccine titer as assessed through a standard microneutralization assay (p<0.05, q <0.2. Notably, we identified several peptide epitopes that were inversely correlated with regard to age and seasonal H1N1 and B-strain neutralization titer (p<0.05, q <0.2, implicating reactivity to these epitopes in age-related defects in response to H1N1 influenza. We also employed multivariate linear regression with cross-validation to build models based on age and pre-vaccine peptide reactivity that predicted vaccine-induced neutralization of seasonal H1N1 and H3N2 influenza strains with a high level of accuracy (84.7% and 74.0%, respectively.Our methods provide powerful tools for rapid and accurate measurement of broad antibody-based immune responses to influenza

  8. Filtering for increased power for microarray data analysis

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    Hess Ann M

    2009-01-01

    Full Text Available Abstract Background Due to the large number of hypothesis tests performed during the process of routine analysis of microarray data, a multiple testing adjustment is certainly warranted. However, when the number of tests is very large and the proportion of differentially expressed genes is relatively low, the use of a multiple testing adjustment can result in very low power to detect those genes which are truly differentially expressed. Filtering allows for a reduction in the number of tests and a corresponding increase in power. Common filtering methods include filtering by variance, average signal or MAS detection call (for Affymetrix arrays. We study the effects of filtering in combination with the Benjamini-Hochberg method for false discovery rate control and q-value for false discovery rate estimation. Results Three case studies are used to compare three different filtering methods in combination with the two false discovery rate methods and three different preprocessing methods. For the case studies considered, filtering by detection call and variance (on the original scale consistently led to an increase in the number of differentially expressed genes identified. On the other hand, filtering by variance on the log2 scale had a detrimental effect when paired with MAS5 or PLIER preprocessing methods, even when the testing was done on the log2 scale. A simulation study was done to further examine the effect of filtering by variance. We find that filtering by variance leads to higher power, often with a decrease in false discovery rate, when paired with either of the false discovery rate methods considered. This holds regardless of the proportion of genes which are differentially expressed or whether we assume dependence or independence among genes. Conclusion The case studies show that both detection call and variance filtering are viable methods of filtering which can increase the number of differentially expressed genes identified. The

  9. Electron radiography

    Science.gov (United States)

    Merrill, Frank E.; Morris, Christopher

    2005-05-17

    A system capable of performing radiography using a beam of electrons. Diffuser means receive a beam of electrons and diffuse the electrons before they enter first matching quadrupoles where the diffused electrons are focused prior to the diffused electrons entering an object. First imaging quadrupoles receive the focused diffused electrons after the focused diffused electrons have been scattered by the object for focusing the scattered electrons. Collimator means receive the scattered electrons and remove scattered electrons that have scattered to large angles. Second imaging quadrupoles receive the collimated scattered electrons and refocus the collimated scattered electrons and map the focused collimated scattered electrons to transverse locations on an image plane representative of the electrons' positions in the object.

  10. Evaluation criteria of rat hepatocytes transcriptome analysis under the influence of interferon alpha by DNA microarray

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    Kuklin A. V.

    2013-10-01

    Full Text Available The changes induced in transcriptome of rat hepatocytes treated with interferon alpha (IFN during three and six hours were analyzed by DNA microarray. Aim. To conduct a stepwise analysis of the results of microarray experiment and to determine whether they meet/fail to the conventional requirements. Methods. The files obtained after scanning microarrays were subjected to the analysis in statistical environment R by Bioconductor’s packages «affy», «simpleaffy», «affyPLM» and BRB Array Tools software for paired T-test. Results. All microarrays had quality metrics lying within recommended ranges, passed quality control, were normalized and are comparable with each other. The T-test revealed 28 and 124 differentially expressed genes after three and six hours of cells cultivation with IFNα , respectively. Conclusions. The obtained data meet the conventional criteria of quality and are applicable for further evaluation of their biological significance. The R-codes used in this study can be used for the analysis of the microarrays data.

  11. Cross-platform comparison of microarray-based multiple-class prediction.

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    Xiaohui Fan

    Full Text Available High-throughput microarray technology has been widely applied in biological and medical decision-making research during the past decade. However, the diversity of platforms has made it a challenge to re-use and/or integrate datasets generated in different experiments or labs for constructing array-based diagnostic models. Using large toxicogenomics datasets generated using both Affymetrix and Agilent microarray platforms, we carried out a benchmark evaluation of cross-platform consistency in multiple-class prediction using three widely-used machine learning algorithms. After an initial assessment of model performance on different platforms, we evaluated whether predictive signature features selected in one platform could be directly used to train a model in the other platform and whether predictive models trained using data from one platform could predict datasets profiled using the other platform with comparable performance. Our results established that it is possible to successfully apply multiple-class prediction models across different commercial microarray platforms, offering a number of important benefits such as accelerating the possible translation of biomarkers identified with microarrays to clinically-validated assays. However, this investigation focuses on a technical platform comparison and is actually only the beginning of exploring cross-platform consistency. Further studies are needed to confirm the feasibility of microarray-based cross-platform prediction, especially using independent datasets.

  12. PMA: Protein Microarray Analyser, a user-friendly tool for data processing and normalization.

    Science.gov (United States)

    Da Gama Duarte, Jessica; Goosen, Ryan W; Lawry, Peter J; Blackburn, Jonathan M

    2018-02-27

    Protein microarrays provide a high-throughput platform to measure protein interactions and associated functions, and can aid in the discovery of cancer biomarkers. The resulting protein microarray data can however be subject to systematic bias and noise, thus requiring a robust data processing, normalization and analysis pipeline to ensure high quality and robust results. To date, a comprehensive data processing pipeline is yet to be developed. Furthermore, a lack of analysis consistency is evident amongst different research groups, thereby impeding collaborative data consolidation and comparison. Thus, we sought to develop an accessible data processing tool using methods that are generalizable to the protein microarray field and which can be adapted to individual array layouts with minimal software engineering expertise. We developed an improved version of a previously developed pipeline of protein microarray data processing and implemented it as an open source software tool, with particular focus on widening its use and applicability. The Protein Microarray Analyser software presented here includes the following tools: (1) neighbourhood background correction, (2) net intensity correction, (3) user-defined noise threshold, (4) user-defined CV threshold amongst replicates and (5) assay controls, (6) composite 'pin-to-pin' normalization amongst sub-arrays, and (7) 'array-to-array' normalization amongst whole arrays.

  13. Genomic Microarray in Fetuses with Early Growth Restriction: A Multicenter Study.

    Science.gov (United States)

    Borrell, Antoni; Grande, Maribel; Meler, Eva; Sabrià, Joan; Mazarico, Edurne; Muñoz, Anna; Rodriguez-Revenga, Laia; Badenas, Cèlia; Figueras, Francesc

    2017-01-01

    Little information is available about the risk of microdeletion and microduplication syndromes in fetal growth restriction (FGR) with a normal karyotype. To assess the incremental yield of genomic microarray over conventional karyotyping in fetuses with early growth restriction. Genomic microarray was prospectively performed in fetuses with early growth restriction defined as a fetal weight below the 3rd percentile estimated before 32 weeks of pregnancy, and a normal quantitative fluorescent polymerase chain reaction result. The incremental yield of genomic microarray was defined by the rate of fetuses presenting with a pathogenic copy number variant below 10 Mb. Among 133 fetuses with early FGR, a 6.8% (95% CI: 2.5-11.0) incremental yield of genomic microarray over karyotyping was observed. This incremental yield was 4.8% (95% CI: 0.2-9.3) in isolated FGR, 10% (95% CI: 0-20.7) in FGR with nonstructural anomalies, and 10.5% (95% CI: 0-24.3) in FGR with structural anomalies. Our multicenter study reveals that 6.8% of fetuses with early growth restriction present with submicroscopic anomalies after common aneuploidies were excluded. Even when FGR is observed as an isolated finding, genomic microarray analysis should be considered after or instead of karyotyping, due to its 4.8% incremental yield. © 2016 S. Karger AG, Basel.

  14. Microarray analysis of potential genes in the pathogenesis of recurrent oral ulcer.

    Science.gov (United States)

    Han, Jingying; He, Zhiwei; Li, Kun; Hou, Lu

    2015-01-01

    Recurrent oral ulcer seriously threatens patients' daily life and health. This study investigated potential genes and pathways that participate in the pathogenesis of recurrent oral ulcer by high throughput bioinformatic analysis. RT-PCR and Western blot were applied to further verify screened interleukins effect. Recurrent oral ulcer related genes were collected from websites and papers, and further found out from Human Genome 280 6.0 microarray data. Each pathway of recurrent oral ulcer related genes were got through chip hybridization. RT-PCR was applied to test four recurrent oral ulcer related genes to verify the microarray data. Data transformation, scatter plot, clustering analysis, and expression pattern analysis were used to analyze recurrent oral ulcer related gene expression changes. Recurrent oral ulcer gene microarray was successfully established. Microarray showed that 551 genes involved in recurrent oral ulcer activity and 196 genes were recurrent oral ulcer related genes. Of them, 76 genes up-regulated, 62 genes down-regulated, and 58 genes up-/down-regulated. Total expression level up-regulated 752 times (60%) and down-regulated 485 times (40%). IL-2 plays an important role in the occurrence, development and recurrence of recurrent oral ulcer on the mRNA and protein levels. Gene microarray can be used to analyze potential genes and pathways in recurrent oral ulcer. IL-2 may be involved in the pathogenesis of recurrent oral ulcer.

  15. A molecular beacon microarray based on a quantum dot label for detecting single nucleotide polymorphisms.

    Science.gov (United States)

    Guo, Qingsheng; Bai, Zhixiong; Liu, Yuqian; Sun, Qingjiang

    2016-03-15

    In this work, we report the application of streptavidin-coated quantum dot (strAV-QD) in molecular beacon (MB) microarray assays by using the strAV-QD to label the immobilized MB, avoiding target labeling and meanwhile obviating the use of amplification. The MBs are stem-loop structured oligodeoxynucleotides, modified with a thiol and a biotin at two terminals of the stem. With the strAV-QD labeling an "opened" MB rather than a "closed" MB via streptavidin-biotin reaction, a sensitive and specific detection of label-free target DNA sequence is demonstrated by the MB microarray, with a signal-to-background ratio of 8. The immobilized MBs can be perfectly regenerated, allowing the reuse of the microarray. The MB microarray also is able to detect single nucleotide polymorphisms, exhibiting genotype-dependent fluorescence signals. It is demonstrated that the MB microarray can perform as a 4-to-2 encoder, compressing the genotype information into two outputs. Copyright © 2015 Elsevier B.V. All rights reserved.

  16. On the classification techniques in data mining for microarray data classification

    Science.gov (United States)

    Aydadenta, Husna; Adiwijaya

    2018-03-01

    Cancer is one of the deadly diseases, according to data from WHO by 2015 there are 8.8 million more deaths caused by cancer, and this will increase every year if not resolved earlier. Microarray data has become one of the most popular cancer-identification studies in the field of health, since microarray data can be used to look at levels of gene expression in certain cell samples that serve to analyze thousands of genes simultaneously. By using data mining technique, we can classify the sample of microarray data thus it can be identified with cancer or not. In this paper we will discuss some research using some data mining techniques using microarray data, such as Support Vector Machine (SVM), Artificial Neural Network (ANN), Naive Bayes, k-Nearest Neighbor (kNN), and C4.5, and simulation of Random Forest algorithm with technique of reduction dimension using Relief. The result of this paper show performance measure (accuracy) from classification algorithm (SVM, ANN, Naive Bayes, kNN, C4.5, and Random Forets).The results in this paper show the accuracy of Random Forest algorithm higher than other classification algorithms (Support Vector Machine (SVM), Artificial Neural Network (ANN), Naive Bayes, k-Nearest Neighbor (kNN), and C4.5). It is hoped that this paper can provide some information about the speed, accuracy, performance and computational cost generated from each Data Mining Classification Technique based on microarray data.

  17. Magnetic Scanometric DNA Microarray Detection of Methyl Tertiary Butyl Ether Degrading Bacteria for Environmental Monitoring

    Science.gov (United States)

    Chan, Mei-Lin; Jaramillo, Gerardo; Hristova, Krassimira R.; Horsley, David A.

    2010-01-01

    A magnetoresistive biosensing platform based on a single magnetic tunnel junction (MTJ) scanning probe and DNA microarrays labeled with magnetic particles has been developed to provide an inexpensive, sensitive and reliable detection of DNA. The biosensing platform was demonstrated on a DNA microarray assay for quantifying bacteria capable of degrading methyl tertiary-butyl ether (MTBE), where concentrations as low as 10 pM were detectable. Synthetic probe bacterial DNA was immobilized on a microarray glass slide surface, hybridized with the 48 base pair long biotinylated target DNA and subsequently incubated with streptavidin-coated 2.8 μm diameter magnetic particles. The biosensing platform then makes use of a micron-sized MTJ sensor that was raster scanned across a 3 mm by 5 mm glass slide area to capture the stray magnetic field from the tagged DNA and extract two dimensional magnetic field images of the microarray. The magnetic field output is then averaged over each 100 μm diameter DNA array spot to extract the magnetic spot intensity, analogous to the fluorescence spot intensity used in conventional optical scanners. The magnetic scanning result is compared with results from a commercial laser scanner and particle coverage optical counting to demonstrate the dynamic range and linear sensitivity of the biosensing platform as a potentially inexpensive, sensitive and portable alternative for DNA microarray detection for field applications. PMID:20889328

  18. The PowerAtlas: a power and sample size atlas for microarray experimental design and research

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    Wang Jelai

    2006-02-01

    Full Text Available Abstract Background Microarrays permit biologists to simultaneously measure the mRNA abundance of thousands of genes. An important issue facing investigators planning microarray experiments is how to estimate the sample size required for good statistical power. What is the projected sample size or number of replicate chips needed to address the multiple hypotheses with acceptable accuracy? Statistical methods exist for calculating power based upon a single hypothesis, using estimates of the variability in data from pilot studies. There is, however, a need for methods to estimate power and/or required sample sizes in situations where multiple hypotheses are being tested, such as in microarray experiments. In addition, investigators frequently do not have pilot data to estimate the sample sizes required for microarray studies. Results To address this challenge, we have developed a Microrarray PowerAtlas 1. The atlas enables estimation of statistical power by allowing investigators to appropriately plan studies by building upon previous studies that have similar experimental characteristics. Currently, there are sample sizes and power estimates based on 632 experiments from Gene Expression Omnibus (GEO. The PowerAtlas also permits investigators to upload their own pilot data and derive power and sample size estimates from these data. This resource will be updated regularly with new datasets from GEO and other databases such as The Nottingham Arabidopsis Stock Center (NASC. Conclusion This resource provides a valuable tool for investigators who are planning efficient microarray studies and estimating required sample sizes.

  19. MIGS-GPU: Microarray Image Gridding and Segmentation on the GPU.

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    Katsigiannis, Stamos; Zacharia, Eleni; Maroulis, Dimitris

    2017-05-01

    Complementary DNA (cDNA) microarray is a powerful tool for simultaneously studying the expression level of thousands of genes. Nevertheless, the analysis of microarray images remains an arduous and challenging task due to the poor quality of the images that often suffer from noise, artifacts, and uneven background. In this study, the MIGS-GPU [Microarray Image Gridding and Segmentation on Graphics Processing Unit (GPU)] software for gridding and segmenting microarray images is presented. MIGS-GPU's computations are performed on the GPU by means of the compute unified device architecture (CUDA) in order to achieve fast performance and increase the utilization of available system resources. Evaluation on both real and synthetic cDNA microarray images showed that MIGS-GPU provides better performance than state-of-the-art alternatives, while the proposed GPU implementation achieves significantly lower computational times compared to the respective CPU approaches. Consequently, MIGS-GPU can be an advantageous and useful tool for biomedical laboratories, offering a user-friendly interface that requires minimum input in order to run.

  20. BIOPHYSICAL PROPERTIES OF NUCLEIC ACIDS AT SURFACES RELEVANT TO MICROARRAY PERFORMANCE

    Science.gov (United States)

    Rao, Archana N.; Grainger, David W.

    2014-01-01

    Both clinical and analytical metrics produced by microarray-based assay technology have recognized problems in reproducibility, reliability and analytical sensitivity. These issues are often attributed to poor understanding and control of nucleic acid behaviors and properties at solid-liquid interfaces. Nucleic acid hybridization, central to DNA and RNA microarray formats, depends on the properties and behaviors of single strand (ss) nucleic acids (e.g., probe oligomeric DNA) bound to surfaces. ssDNA’s persistence length, radius of gyration, electrostatics, conformations on different surfaces and under various assay conditions, its chain flexibility and curvature, charging effects in ionic solutions, and fluorescent labeling all influence its physical chemistry and hybridization under assay conditions. Nucleic acid (e.g., both RNA and DNA) target interactions with immobilized ssDNA strands are highly impacted by these biophysical states. Furthermore, the kinetics, thermodynamics, and enthalpic and entropic contributions to DNA hybridization reflect global probe/target structures and interaction dynamics. Here we review several biophysical issues relevant to oligomeric nucleic acid molecular behaviors at surfaces and their influences on duplex formation that influence microarray assay performance. Correlation of biophysical aspects of single and double-stranded nucleic acids with their complexes in bulk solution is common. Such analysis at surfaces is not commonly reported, despite its importance to microarray assays. We seek to provide further insight into nucleic acid-surface challenges facing microarray diagnostic formats that have hindered their clinical adoption and compromise their research quality and value as genomics tools. PMID:24765522

  1. SNP Microarray in FISH Negative Clinically Suspected 22q11.2 Microdeletion Syndrome

    Science.gov (United States)

    Jain, Manish; Kalsi, Amanpreet Kaur

    2016-01-01

    The present study evaluated the role of SNP microarray in 101 cases of clinically suspected FISH negative (noninformative/normal) 22q11.2 microdeletion syndrome. SNP microarray was carried out using 300 K HumanCytoSNP-12 BeadChip array or CytoScan 750 K array. SNP microarray identified 8 cases of 22q11.2 microdeletions and/or microduplications in addition to cases of chromosomal abnormalities and other pathogenic/likely pathogenic CNVs. Clinically suspected specific deletions (22q11.2) were detectable in approximately 8% of cases by SNP microarray, mostly from FISH noninformative cases. This study also identified several LOH/AOH loci with known and well-defined UPD (uniparental disomy) disorders. In conclusion, this study suggests more strict clinical criteria for FISH analysis. However, if clinical criteria are few or doubtful, in particular newborn/neonate in intensive care, SNP microarray should be the first screening test to be ordered. FISH is ideal test for detecting mosaicism, screening family members, and prenatal diagnosis in proven families. PMID:27051557

  2. SNP Microarray in FISH Negative Clinically Suspected 22q11.2 Microdeletion Syndrome.

    Science.gov (United States)

    Halder, Ashutosh; Jain, Manish; Kalsi, Amanpreet Kaur

    2016-01-01

    The present study evaluated the role of SNP microarray in 101 cases of clinically suspected FISH negative (noninformative/normal) 22q11.2 microdeletion syndrome. SNP microarray was carried out using 300 K HumanCytoSNP-12 BeadChip array or CytoScan 750 K array. SNP microarray identified 8 cases of 22q11.2 microdeletions and/or microduplications in addition to cases of chromosomal abnormalities and other pathogenic/likely pathogenic CNVs. Clinically suspected specific deletions (22q11.2) were detectable in approximately 8% of cases by SNP microarray, mostly from FISH noninformative cases. This study also identified several LOH/AOH loci with known and well-defined UPD (uniparental disomy) disorders. In conclusion, this study suggests more strict clinical criteria for FISH analysis. However, if clinical criteria are few or doubtful, in particular newborn/neonate in intensive care, SNP microarray should be the first screening test to be ordered. FISH is ideal test for detecting mosaicism, screening family members, and prenatal diagnosis in proven families.

  3. Merging microarray data, robust feature selection, and predicting prognosis in prostate cancer

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    Kevin R. Coombes

    2006-01-01

    Full Text Available Motivation: Individual microarray studies searching for prognostic biomarkers often have few samples and low statistical power; however, publicly accessible data sets make it possible to combine data across studies.Method: We present a novel approach for combining microarray data across institutions and platforms. We introduce a new algorithm, robust greedy feature selection (RGFS, to select predictive genes.Results: We combined two prostate cancer microarray data sets, confirmed the appropriateness of the approach with the Kolmogorov-Smirnov goodness-of-fit test, and built several predictive models. The best logistic regression model with stepwise forward selection used 7 genes and had a misclassification rate of 31%. Models that combined LDA with different feature selection algorithms had misclassification rates between 19% and 33%, and the sets of genes in the models varied substantially during cross-validation. When we combined RGFS with LDA, the best model used two genes and had a misclassification rate of 15%.Availability: Affymetrix U95Av2 array data are available at http://www.broad.mit.edu/cgi-bin/cancer/datasets.cgi. The cDNA microarray data are available through the Stanford Microarray Database (http://cmgm.stanford.edu/pbrown/. GeneLink software is freely available at http://bioinformatics.mdanderson.org/GeneLink/. DNA-Chip Analyzer software is publicly available at http://biosun1.harvard.edu/complab/dchip/.

  4. BASE--2nd generation software for microarray data management and analysis.

    Science.gov (United States)

    Vallon-Christersson, Johan; Nordborg, Nicklas; Svensson, Martin; Häkkinen, Jari

    2009-10-12

    Microarray experiments are increasing in size and samples are collected asynchronously over long time. Available data are re-analysed as more samples are hybridized. Systematic use of collected data requires tracking of biomaterials, array information, raw data, and assembly of annotations. To meet the information tracking and data analysis challenges in microarray experiments we reimplemented and improved BASE version 1.2. The new BASE presented in this report is a comprehensive annotable local microarray data repository and analysis application providing researchers with an efficient information management and analysis tool. The information management system tracks all material from biosource, via sample and through extraction and labelling to raw data and analysis. All items in BASE can be annotated and the annotations can be used as experimental factors in downstream analysis. BASE stores all microarray experiment related data regardless if analysis tools for specific techniques or data formats are readily available. The BASE team is committed to continue improving and extending BASE to make it usable for even more experimental setups and techniques, and we encourage other groups to target their specific needs leveraging on the infrastructure provided by BASE. BASE is a comprehensive management application for information, data, and analysis of microarray experiments, available as free open source software at http://base.thep.lu.se under the terms of the GPLv3 license.

  5. Fabrication of protein microarrays for alpha fetoprotein detection by using a rapid photo-immobilization process

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    Sirasa Yodmongkol

    2016-03-01

    Full Text Available In this study, protein microarrays based on sandwich immunoassays are generated to quantify the amount of alpha fetoprotein (AFP in blood serum. For chip generation a mixture of capture antibody and a photoactive copolymer consisting of N,N-dimethylacrylamide (DMAA, methacryloyloxy benzophenone (MaBP, and Na-4-styrenesulfonate (SSNa was spotted onto unmodified polymethyl methacrylate (PMMA substrates. Subsequently to printing of the microarray, the polymer and protein were photochemically cross-linked and the forming, biofunctionalized hydrogels simultaneously bound to the chip surface by short UV- irradiation. The obtained biochip was incubated with AFP antigen, followed by biotinylated AFP antibody and streptavidin-Cy5 and the fluorescence signal read-out. The developed microarray biochip covers the range of AFP in serum samples such as maternal serum in the range of 5 and 100 ng/ml. The chip production process is based on a fast and simple immobilization process, which can be applied to conventional plastic surfaces. Therefore, this protein microarray production process is a promising method to fabricate biochips for AFP screening processes. Keywords: Photo-immobilization, Protein microarray, Alpha fetoprotein, Hydrogel, 3D surface, Down syndrome

  6. An efficient algorithm for the stochastic simulation of the hybridization of DNA to microarrays

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    Laurenzi Ian J

    2009-12-01

    Full Text Available Abstract Background Although oligonucleotide microarray technology is ubiquitous in genomic research, reproducibility and standardization of expression measurements still concern many researchers. Cross-hybridization between microarray probes and non-target ssDNA has been implicated as a primary factor in sensitivity and selectivity loss. Since hybridization is a chemical process, it may be modeled at a population-level using a combination of material balance equations and thermodynamics. However, the hybridization reaction network may be exceptionally large for commercial arrays, which often possess at least one reporter per transcript. Quantification of the kinetics and equilibrium of exceptionally large chemical systems of this type is numerically infeasible with customary approaches. Results In this paper, we present a robust and computationally efficient algorithm for the simulation of hybridization processes underlying microarray assays. Our method may be utilized to identify the extent to which nucleic acid targets (e.g. cDNA will cross-hybridize with probes, and by extension, characterize probe robustnessusing the information specified by MAGE-TAB. Using this algorithm, we characterize cross-hybridization in a modified commercial microarray assay. Conclusions By integrating stochastic simulation with thermodynamic prediction tools for DNA hybridization, one may robustly and rapidly characterize of the selectivity of a proposed microarray design at the probe and "system" levels. Our code is available at http://www.laurenzi.net.

  7. BASE - 2nd generation software for microarray data management and analysis

    Directory of Open Access Journals (Sweden)

    Nordborg Nicklas

    2009-10-01

    Full Text Available Abstract Background Microarray experiments are increasing in size and samples are collected asynchronously over long time. Available data are re-analysed as more samples are hybridized. Systematic use of collected data requires tracking of biomaterials, array information, raw data, and assembly of annotations. To meet the information tracking and data analysis challenges in microarray experiments we reimplemented and improved BASE version 1.2. Results The new BASE presented in this report is a comprehensive annotable local microarray data repository and analysis application providing researchers with an efficient information management and analysis tool. The information management system tracks all material from biosource, via sample and through extraction and labelling to raw data and analysis. All items in BASE can be annotated and the annotations can be used as experimental factors in downstream analysis. BASE stores all microarray experiment related data regardless if analysis tools for specific techniques or data formats are readily available. The BASE team is committed to continue improving and extending BASE to make it usable for even more experimental setups and techniques, and we encourage other groups to target their specific needs leveraging on the infrastructure provided by BASE. Conclusion BASE is a comprehensive management application for information, data, and analysis of microarray experiments, available as free open source software at http://base.thep.lu.se under the terms of the GPLv3 license.

  8. Detection of NASBA amplified bacterial tmRNA molecules on SLICSel designed microarray probes.

    Science.gov (United States)

    Scheler, Ott; Kaplinski, Lauris; Glynn, Barry; Palta, Priit; Parkel, Sven; Toome, Kadri; Maher, Majella; Barry, Thomas; Remm, Maido; Kurg, Ants

    2011-02-28

    We present a comprehensive technological solution for bacterial diagnostics using tmRNA as a marker molecule. A robust probe design algorithm for microbial detection microarray is implemented. The probes were evaluated for specificity and, combined with NASBA (Nucleic Acid Sequence Based Amplification) amplification, for sensitivity. We developed a new web-based program SLICSel for the design of hybridization probes, based on nearest-neighbor thermodynamic modeling. A SLICSel minimum binding energy difference criterion of 4 kcal/mol was sufficient to design of Streptococcus pneumoniae tmRNA specific microarray probes. With lower binding energy difference criteria, additional hybridization specificity tests on the microarray were needed to eliminate non-specific probes. Using SLICSel designed microarray probes and NASBA we were able to detect S. pneumoniae tmRNA from a series of total RNA dilutions equivalent to the RNA content of 0.1-10 CFU. The described technological solution and both its separate components SLICSel and NASBA-microarray technology independently are applicative for many different areas of microbial diagnostics.

  9. Detection of NASBA amplified bacterial tmRNA molecules on SLICSel designed microarray probes

    Directory of Open Access Journals (Sweden)

    Toome Kadri

    2011-02-01

    Full Text Available Abstract Background We present a comprehensive technological solution for bacterial diagnostics using tmRNA as a marker molecule. A robust probe design algorithm for microbial detection microarray is implemented. The probes were evaluated for specificity and, combined with NASBA (Nucleic Acid Sequence Based Amplification amplification, for sensitivity. Results We developed a new web-based program SLICSel for the design of hybridization probes, based on nearest-neighbor thermodynamic modeling. A SLICSel minimum binding energy difference criterion of 4 kcal/mol was sufficient to design of Streptococcus pneumoniae tmRNA specific microarray probes. With lower binding energy difference criteria, additional hybridization specificity tests on the microarray were needed to eliminate non-specific probes. Using SLICSel designed microarray probes and NASBA we were able to detect S. pneumoniae tmRNA from a series of total RNA dilutions equivalent to the RNA content of 0.1-10 CFU. Conclusions The described technological solution and both its separate components SLICSel and NASBA-microarray technology independently are applicative for many different areas of microbial diagnostics.

  10. Multiplex RT-PCR and Automated Microarray for Detection of Eight Bovine Viruses.

    Science.gov (United States)

    Lung, O; Furukawa-Stoffer, T; Burton Hughes, K; Pasick, J; King, D P; Hodko, D

    2017-12-01

    Microarrays can be a useful tool for pathogen detection as it allow for simultaneous interrogation of the presence of a large number of genetic sequences in a sample. However, conventional microarrays require extensive manual handling and multiple pieces of equipment for printing probes, hybridization, washing and signal detection. In this study, a reverse transcription (RT)-PCR with an accompanying novel automated microarray for simultaneous detection of eight viruses that affect cattle [vesicular stomatitis virus (VSV), bovine viral diarrhoea virus type 1 and type 2, bovine herpesvirus 1, bluetongue virus, malignant catarrhal fever virus, rinderpest virus (RPV) and parapox viruses] is described. The assay accurately identified a panel of 37 strains of the target viruses and identified a mixed infection. No non-specific reactions were observed with a panel of 23 non-target viruses associated with livestock. Vesicular stomatitis virus was detected as early as 2 days post-inoculation in oral swabs from experimentally infected animals. The limit of detection of the microarray assay was as low as 1 TCID 50 /ml for RPV. The novel microarray platform automates the entire post-PCR steps of the assay and integrates electrophoretic-driven capture probe printing in a single user-friendly instrument that allows array layout and assay configuration to be user-customized on-site. © 2016 Her Majesty the Queen in Right of Canada.

  11. Detection of NASBA amplified bacterial tmRNA molecules on SLICSel designed microarray probes

    LENUS (Irish Health Repository)

    Scheler, Ott

    2011-02-28

    Abstract Background We present a comprehensive technological solution for bacterial diagnostics using tmRNA as a marker molecule. A robust probe design algorithm for microbial detection microarray is implemented. The probes were evaluated for specificity and, combined with NASBA (Nucleic Acid Sequence Based Amplification) amplification, for sensitivity. Results We developed a new web-based program SLICSel for the design of hybridization probes, based on nearest-neighbor thermodynamic modeling. A SLICSel minimum binding energy difference criterion of 4 kcal\\/mol was sufficient to design of Streptococcus pneumoniae tmRNA specific microarray probes. With lower binding energy difference criteria, additional hybridization specificity tests on the microarray were needed to eliminate non-specific probes. Using SLICSel designed microarray probes and NASBA we were able to detect S. pneumoniae tmRNA from a series of total RNA dilutions equivalent to the RNA content of 0.1-10 CFU. Conclusions The described technological solution and both its separate components SLICSel and NASBA-microarray technology independently are applicative for many different areas of microbial diagnostics.

  12. Development of an oligonucleotide-based microarray to detect multiple foodborne pathogens.

    Science.gov (United States)

    Suo, Biao; He, Yiping; Paoli, George; Gehring, Andrew; Tu, Shu-I; Shi, Xianming

    2010-04-01

    Escherichia coli O157:H7, Salmonella enterica, Listeria monocytogenes and Campylobacter jejuni are considered important pathogens causing the most food-related human illnesses worldwide. Current methods for pathogen detection have limitations in the effectiveness of identifying multiple foodborne pathogens. In this study, a pathogen detection microarray was developed using various 70-mer oligonucleotides specifically targeting the above pathogens. To reduce the cost of detection, each microarray chip was designed and fabricated to accommodate 12 identical arrays which could be used for screening up to 12 different samples. To achieve high detection sensitivity and specificity, target-specific DNA amplification instead of whole genome random amplification was used prior to microarray analysis. Combined with 14-plex PCR amplification of target sequences, the microarray unambiguously distinguished all 4 pathogens with a detection sensitivity of 1 x 10(-4) ng (approximately 20 copies) of each genomic DNA. Applied the assay to 39 fresh meat samples, 16 samples were found to be contaminated by either 1 or 2 of these pathogens. The co-occurrences of Salmonella and E. coli O157:H7, Salmonella and L. monocytogenes in the same meat samples were also observed. Overall, the microarray combined with multiplex PCR method was able to effectively screen single or multiple pathogens in food samples and to provide important genotypic information related to pathogen virulence.

  13. SNP Microarray in FISH Negative Clinically Suspected 22q11.2 Microdeletion Syndrome

    Directory of Open Access Journals (Sweden)

    Ashutosh Halder

    2016-01-01

    Full Text Available The present study evaluated the role of SNP microarray in 101 cases of clinically suspected FISH negative (noninformative/normal 22q11.2 microdeletion syndrome. SNP microarray was carried out using 300 K HumanCytoSNP-12 BeadChip array or CytoScan 750 K array. SNP microarray identified 8 cases of 22q11.2 microdeletions and/or microduplications in addition to cases of chromosomal abnormalities and other pathogenic/likely pathogenic CNVs. Clinically suspected specific deletions (22q11.2 were detectable in approximately 8% of cases by SNP microarray, mostly from FISH noninformative cases. This study also identified several LOH/AOH loci with known and well-defined UPD (uniparental disomy disorders. In conclusion, this study suggests more strict clinical criteria for FISH analysis. However, if clinical criteria are few or doubtful, in particular newborn/neonate in intensive care, SNP microarray should be the first screening test to be ordered. FISH is ideal test for detecting mosaicism, screening family members, and prenatal diagnosis in proven families.

  14. A probabilistic framework for microarray data analysis: fundamental probability models and statistical inference.

    Science.gov (United States)

    Ogunnaike, Babatunde A; Gelmi, Claudio A; Edwards, Jeremy S

    2010-05-21

    Gene expression studies generate large quantities of data with the defining characteristic that the number of genes (whose expression profiles are to be determined) exceed the number of available replicates by several orders of magnitude. Standard spot-by-spot analysis still seeks to extract useful information for each gene on the basis of the number of available replicates, and thus plays to the weakness of microarrays. On the other hand, because of the data volume, treating the entire data set as an ensemble, and developing theoretical distributions for these ensembles provides a framework that plays instead to the strength of microarrays. We present theoretical results that under reasonable assumptions, the distribution of microarray intensities follows the Gamma model, with the biological interpretations of the model parameters emerging naturally. We subsequently establish that for each microarray data set, the fractional intensities can be represented as a mixture of Beta densities, and develop a procedure for using these results to draw statistical inference regarding differential gene expression. We illustrate the results with experimental data from gene expression studies on Deinococcus radiodurans following DNA damage using cDNA microarrays. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

  15. Assessing the Clinical Utility of SNP Microarray for Prader-Willi Syndrome due to Uniparental Disomy.

    Science.gov (United States)

    Santoro, Stephanie L; Hashimoto, Sayaka; McKinney, Aimee; Mihalic Mosher, Theresa; Pyatt, Robert; Reshmi, Shalini C; Astbury, Caroline; Hickey, Scott E

    2017-01-01

    Maternal uniparental disomy (UPD) 15 is one of the molecular causes of Prader-Willi syndrome (PWS), a multisystem disorder which presents with neonatal hypotonia and feeding difficulty. Current diagnostic algorithms differ regarding the use of SNP microarray to detect PWS. We retrospectively examined the frequency with which SNP microarray could identify regions of homozygosity (ROH) in patients with PWS. We determined that 7/12 (58%) patients with previously confirmed PWS by methylation analysis and microsatellite-positive UPD studies had ROH (>10 Mb) by SNP microarray. Additional assessment of 5,000 clinical microarrays, performed from 2013 to present, determined that only a single case of ROH for chromosome 15 was not caused by an imprinting disorder or identity by descent. We observed that ROH for chromosome 15 is rarely incidental and strongly associated with hypotonic infants having features of PWS. Although UPD microsatellite studies remain essential to definitively establish the presence of UPD, SNP microarray has important utility in the timely diagnostic algorithm for PWS. © 2017 S. Karger AG, Basel.

  16. Fuzzy support vector machine: an efficient rule-based classification technique for microarrays.

    Science.gov (United States)

    Hajiloo, Mohsen; Rabiee, Hamid R; Anooshahpour, Mahdi

    2013-01-01

    The abundance of gene expression microarray data has led to the development of machine learning algorithms applicable for tackling disease diagnosis, disease prognosis, and treatment selection problems. However, these algorithms often produce classifiers with weaknesses in terms of accuracy, robustness, and interpretability. This paper introduces fuzzy support vector machine which is a learning algorithm based on combination of fuzzy classifiers and kernel machines for microarray classification. Experimental results on public leukemia, prostate, and colon cancer datasets show that fuzzy support vector machine applied in combination with filter or wrapper feature selection methods develops a robust model with higher accuracy than the conventional microarray classification models such as support vector machine, artificial neural network, decision trees, k nearest neighbors, and diagonal linear discriminant analysis. Furthermore, the interpretable rule-base inferred from fuzzy support vector machine helps extracting biological knowledge from microarray data. Fuzzy support vector machine as a new classification model with high generalization power, robustness, and good interpretability seems to be a promising tool for gene expression microarray classification.

  17. Support vector machine and principal component analysis for microarray data classification

    Science.gov (United States)

    Astuti, Widi; Adiwijaya

    2018-03-01

    Cancer is a leading cause of death worldwide although a significant proportion of it can be cured if it is detected early. In recent decades, technology called microarray takes an important role in the diagnosis of cancer. By using data mining technique, microarray data classification can be performed to improve the accuracy of cancer diagnosis compared to traditional techniques. The characteristic of microarray data is small sample but it has huge dimension. Since that, there is a challenge for researcher to provide solutions for microarray data classification with high performance in both accuracy and running time. This research proposed the usage of Principal Component Analysis (PCA) as a dimension reduction method along with Support Vector Method (SVM) optimized by kernel functions as a classifier for microarray data classification. The proposed scheme was applied on seven data sets using 5-fold cross validation and then evaluation and analysis conducted on term of both accuracy and running time. The result showed that the scheme can obtained 100% accuracy for Ovarian and Lung Cancer data when Linear and Cubic kernel functions are used. In term of running time, PCA greatly reduced the running time for every data sets.

  18. Prediction of qualitative outcome of oligonucleotide microarray hybridization by measurement of RNA integrity using the 2100 Bioanalyzer capillary electrophoresis system.

    Science.gov (United States)

    Kiewe, Philipp; Gueller, Saskia; Komor, Martina; Stroux, Andrea; Thiel, Eckhard; Hofmann, Wolf-Karsten

    2009-12-01

    RNA quality is critical to achieve valid results in microarray experiments and to save resources. The RNA integrity number (RIN) can be measured with minimal sample consumption by microfluidics-based capillary electrophoresis. To determine whether RIN can predict the qualitative outcome of microarray hybridization, we measured RIN in total RNA samples from 484 different experiments by the 2100 Bioanalyzer system and correlated with the percentage of present calls (%pc) of downstream oligonucleotide microarrays. The correlation coefficient for RNA and %pc in all 408 samples for which the bioanalyzer algorithm was able to produce an RIN was 0.475 (p RNA sample is appropriate for successful microarray hybridization.

  19. Human Thrombin Detection Through a Sandwich Aptamer Microarray: Interaction Analysis in Solution and in Solid Phase

    Science.gov (United States)

    Sosic, Alice; Meneghello, Anna; Cretaio, Erica; Gatto, Barbara

    2011-01-01

    We have developed an aptamer-based microarray for human thrombin detection exploiting two non-overlapping DNA thrombin aptamers recognizing different exosites of the target protein. The 15-mer aptamer (TBA1) binds the fibrinogen-binding site, whereas the 29-mer aptamer (TBA2) binds the heparin binding domain. Extensive analysis on the complex formation between human thrombin and modified aptamers was performed by Electrophoresis Mobility Shift Assay (EMSA), in order to verify in solution whether the chemical modifications introduced would affect aptamers/protein recognition. The validated system was then applied to the aptamer microarray, using the solid phase system devised by the solution studies. Finally, the best procedure for Sandwich Aptamer Microarray (SAM) and the specificity of the sandwich formation for the developed aptasensor for human thrombin were optimized. PMID:22163703

  20. A DNA Microarray-Based Assay to Detect Dual Infection with Two Dengue Virus Serotypes

    Science.gov (United States)

    Díaz-Badillo, Alvaro; de Lourdes Muñoz, María; Perez-Ramirez, Gerardo; Altuzar, Victor; Burgueño, Juan; Mendoza-Alvarez, Julio G.; Martínez-Muñoz, Jorge P.; Cisneros, Alejandro; Navarrete-Espinosa, Joel; Sanchez-Sinencio, Feliciano

    2014-01-01

    Here; we have described and tested a microarray based-method for the screening of dengue virus (DENV) serotypes. This DNA microarray assay is specific and sensitive and can detect dual infections with two dengue virus serotypes and single-serotype infections. Other methodologies may underestimate samples containing more than one serotype. This technology can be used to discriminate between the four DENV serotypes. Single-stranded DNA targets were covalently attached to glass slides and hybridised with specific labelled probes. DENV isolates and dengue samples were used to evaluate microarray performance. Our results demonstrate that the probes hybridized specifically to DENV serotypes; with no detection of unspecific signals. This finding provides evidence that specific probes can effectively identify single and double infections in DENV samples. PMID:24776933

  1. A DNA Microarray-Based Assay to Detect Dual Infection with Two Dengue Virus Serotypes

    Directory of Open Access Journals (Sweden)

    Alvaro Díaz-Badillo

    2014-04-01

    Full Text Available Here; we have described and tested a microarray based-method for the screening of dengue virus (DENV serotypes. This DNA microarray assay is specific and sensitive and can detect dual infections with two dengue virus serotypes and single-serotype infections. Other methodologies may underestimate samples containing more than one serotype. This technology can be used to discriminate between the four DENV serotypes. Single-stranded DNA targets were covalently attached to glass slides and hybridised with specific labelled probes. DENV isolates and dengue samples were used to evaluate microarray performance. Our results demonstrate that the probes hybridized specifically to DENV serotypes; with no detection of unspecific signals. This finding provides evidence that specific probes can effectively identify single and double infections in DENV samples.

  2. The Use of Atomic Force Microscopy for 3D Analysis of Nucleic Acid Hybridization on Microarrays.

    Science.gov (United States)

    Dubrovin, E V; Presnova, G V; Rubtsova, M Yu; Egorov, A M; Grigorenko, V G; Yaminsky, I V

    2015-01-01

    Oligonucleotide microarrays are considered today to be one of the most efficient methods of gene diagnostics. The capability of atomic force microscopy (AFM) to characterize the three-dimensional morphology of single molecules on a surface allows one to use it as an effective tool for the 3D analysis of a microarray for the detection of nucleic acids. The high resolution of AFM offers ways to decrease the detection threshold of target DNA and increase the signal-to-noise ratio. In this work, we suggest an approach to the evaluation of the results of hybridization of gold nanoparticle-labeled nucleic acids on silicon microarrays based on an AFM analysis of the surface both in air and in liquid which takes into account of their three-dimensional structure. We suggest a quantitative measure of the hybridization results which is based on the fraction of the surface area occupied by the nanoparticles.

  3. How the RNA isolation method can affect microRNA microarray results

    DEFF Research Database (Denmark)

    Podolska, Agnieszka; Kaczkowski, Bogumil; Litman, Thomas

    2011-01-01

    microarray analysis on porcine brain tissue. One method is a phenol-guanidine isothiocyanate-based procedure that permits isolation of total RNA. The second method, miRVana™ microRNA isolation, is column based and recovers the small RNA fraction alone. We found that microarray analyses give different results......The quality of RNA is crucial in gene expression experiments. RNA degradation interferes in the measurement of gene expression, and in this context, microRNA quantification can lead to an incorrect estimation. In the present study, two different RNA isolation methods were used to perform microRNA...... that depend on the RNA fraction used, in particular because some microRNAs appear very sensitive to the RNA isolation method. We conclude that precautions need to be taken when comparing microarray studies based on RNA isolated with different methods....

  4. A Lateral Flow Protein Microarray for Rapid and Sensitive Antibody Assays

    Directory of Open Access Journals (Sweden)

    Helene Andersson-Svahn

    2011-11-01

    Full Text Available Protein microarrays are useful tools for highly multiplexed determination of presence or levels of clinically relevant biomarkers in human tissues and biofluids. However, such tools have thus far been restricted to laboratory environments. Here, we present a novel 384-plexed easy to use lateral flow protein microarray device capable of sensitive (< 30 ng/mL determination of antigen-specific antibodies in ten minutes of total assay time. Results were developed with gold nanobeads and could be recorded by a cell-phone camera or table top scanner. Excellent accuracy with an area under curve (AUC of 98% was achieved in comparison with an established glass microarray assay for 26 antigen-specific antibodies. We propose that the presented framework could find use in convenient and cost-efficient quality control of antibody production, as well as in providing a platform for multiplexed affinity-based assays in low-resource or mobile settings.

  5. Detecting Outlier Microarray Arrays by Correlation and Percentage of Outliers Spots

    Directory of Open Access Journals (Sweden)

    Song Yang

    2006-01-01

    Full Text Available We developed a quality assurance (QA tool, namely microarray outlier filter (MOF, and have applied it to our microarray datasets for the identification of problematic arrays. Our approach is based on the comparison of the arrays using the correlation coefficient and the number of outlier spots generated on each array to reveal outlier arrays. For a human universal reference (HUR dataset, which is used as a technical control in our standard hybridization procedure, 3 outlier arrays were identified out of 35 experiments. For a human blood dataset, 12 outlier arrays were identified from 185 experiments. In general, arrays from human blood samples displayed greater variation in their gene expression profiles than arrays from HUR samples. As a result, MOF identified two distinct patterns in the occurrence of outlier arrays. These results demonstrate that this methodology is a valuable QA practice to identify questionable microarray data prior to downstream analysis.

  6. A study of metaheuristic algorithms for high dimensional feature selection on microarray data

    Science.gov (United States)

    Dankolo, Muhammad Nasiru; Radzi, Nor Haizan Mohamed; Sallehuddin, Roselina; Mustaffa, Noorfa Haszlinna

    2017-11-01

    Microarray systems enable experts to examine gene profile at molecular level using machine learning algorithms. It increases the potentials of classification and diagnosis of many diseases at gene expression level. Though, numerous difficulties may affect the efficiency of machine learning algorithms which includes vast number of genes features comprised in the original data. Many of these features may be unrelated to the intended analysis. Therefore, feature selection is necessary to be performed in the data pre-processing. Many feature selection algorithms are developed and applied on microarray which including the metaheuristic optimization algorithms. This paper discusses the application of the metaheuristics algorithms for feature selection in microarray dataset. This study reveals that, the algorithms have yield an interesting result with limited resources thereby saving computational expenses of machine learning algorithms.

  7. Microarray-based genotyping of Salmonella: Inter-laboratory evaluation of reproducibility and standardization potential

    DEFF Research Database (Denmark)

    Grønlund, Hugo Ahlm; Riber, Leise; Vigre, Håkan

    2011-01-01

    Bacterial food-borne infections in humans caused by Salmonella spp. are considered a crucial food safety issue. Therefore, it is important for the risk assessments of Salmonella to consider the genomic variationamong different isolates in order to control pathogen-induced infections. Microarray...... critical methodology parameters that differed between the two labs were identified. These related to printing facilities, choice of hybridization buffer,wash buffers used following the hybridization and choice of procedure for purifying genomic DNA. Critical parameters were randomized in a four......DNA and different wash buffers. However, less agreement (Kappa=0.2–0.6) between microarray results were observed when using different hybridization buffers, indicating this parameter as being highly criticalwhen transferring a standard microarray assay between laboratories. In conclusion, this study indicates...

  8. An Emulsion Based Microarray Method to Detect the Toxin Genes of Toxin-Producing Organisms

    Directory of Open Access Journals (Sweden)

    Yunfei Bai

    2011-08-01

    Full Text Available Toxins produced by bacteria and fungi are one of the most important factors which may cause food contamination. The study of detection methods with high sensitivity and throughput is significant for the protection of food safety. In the present study, we coupled microarray with emulsion PCR and developed a high throughput detection method. Thirteen different gene sites which encode the common toxins of several bacteria and fungi were assayed in parallel in positive and maize samples. Conventional PCR assays were carried out for comparison. The results showed that the developed microarray method had high specificity and sensitivity. Two zearalenone-related genes were investigated in one of the ten maize samples obtained with this present method. The results indicated that the emulsion based microarray detection method was developed successfully and suggested its potential application in multiple gene site detection.

  9. Microfluidic extraction and microarray detection of biomarkers from cancer tissue slides

    Science.gov (United States)

    Nguyen, H. T.; Dupont, L. N.; Jean, A. M.; Géhin, T.; Chevolot, Y.; Laurenceau, E.; Gijs, M. A. M.

    2018-03-01

    We report here a new microfluidic method allowing for the quantification of human epidermal growth factor receptor 2 (HER2) expression levels from formalin-fixed breast cancer tissues. After partial extraction of proteins from the tissue slide, the extract is routed to an antibody (Ab) microarray for HER2 titration by fluorescence. Then the HER2-expressing cell area is evaluated by immunofluorescence (IF) staining of the tissue slide and used to normalize the fluorescent HER2 signal measured from the Ab microarray. The number of HER2 gene copies measured by fluorescence in situ hybridization (FISH) on an adjacent tissue slide is concordant with the normalized HER2 expression signal. This work is the first study implementing biomarker extraction and detection from cancer tissue slides using microfluidics in combination with a microarray system, paving the way for further developments towards multiplex and precise quantification of cancer biomarkers.

  10. Applications of nanotechnology, next generation sequencing and microarrays in biomedical research.

    Science.gov (United States)

    Elingaramil, Sauli; Li, Xiaolong; He, Nongyue

    2013-07-01

    Next-generation sequencing technologies, microarrays and advances in bio nanotechnology have had an enormous impact on research within a short time frame. This impact appears certain to increase further as many biomedical institutions are now acquiring these prevailing new technologies. Beyond conventional sampling of genome content, wide-ranging applications are rapidly evolving for next-generation sequencing, microarrays and nanotechnology. To date, these technologies have been applied in a variety of contexts, including whole-genome sequencing, targeted re sequencing and discovery of transcription factor binding sites, noncoding RNA expression profiling and molecular diagnostics. This paper thus discusses current applications of nanotechnology, next-generation sequencing technologies and microarrays in biomedical research and highlights the transforming potential these technologies offer.

  11. Prediction of Pectin Yield and Quality by FTIR and Carbohydrate Microarray Analysis

    DEFF Research Database (Denmark)

    Baum, Andreas; Dominiak, Malgorzata Maria; Vidal-Melgosa, Silvia

    2017-01-01

    and carbohydrate microarray analysis were performed directly on the crude lime peel extracts during the time course of the extractions. Multivariate analysis of the data was carried out to predict final pectin yields. Fourier transform infrared spectroscopy (FTIR) was found applicable for determining the optimal...... extraction time for the enzymatic and acidic extraction processes, respectively. The combined results of FTIR and carbohydrate microarray analysis suggested major differences in the crude pectin extracts obtained by enzymatic and acid extraction, respectively. Enzymatically extracted pectin, thus, showed......, and that FTIR and carbohydrate microarray analysis have potential to be developed into online process analysis tools for prediction of pectin extraction yields and pectin features from measurements on crude pectin extracts....

  12. Accurate Detection of Carcinoma Cells by Use of a Cell Microarray Chip

    Science.gov (United States)

    Yamamura, Shohei; Yatsushiro, Shouki; Yamaguchi, Yuka; Abe, Kaori; Shinohara, Yasuo; Tamiya, Eiichi; Baba, Yoshinobu; Kataoka, Masatoshi

    2012-01-01

    Background Accurate detection and analysis of circulating tumor cells plays an important role in the diagnosis and treatment of metastatic cancer treatment. Methods and Findings A cell microarray chip was used to detect spiked carcinoma cells among leukocytes. The chip, with 20,944 microchambers (105 µm width and 50 µm depth), was made from polystyrene; and the formation of monolayers of leukocytes in the microchambers was observed. Cultured human T lymphoblastoid leukemia (CCRF-CEM) cells were used to examine the potential of the cell microarray chip for the detection of spiked carcinoma cells. A T lymphoblastoid leukemia suspension was dispersed on the chip surface, followed by 15 min standing to allow the leukocytes to settle down into the microchambers. Approximately 29 leukocytes were found in each microchamber when about 600,000 leukocytes in total were dispersed onto a cell microarray chip. Similarly, when leukocytes isolated from human whole blood were used, approximately 89 leukocytes entered each microchamber when about 1,800,000 leukocytes in total were placed onto the cell microarray chip. After washing the chip surface, PE-labeled anti-cytokeratin monoclonal antibody and APC-labeled anti-CD326 (EpCAM) monoclonal antibody solution were dispersed onto the chip surface and allowed to react for 15 min; and then a microarray scanner was employed to detect any fluorescence-positive cells within 20 min. In the experiments using spiked carcinoma cells (NCI-H1650, 0.01 to 0.0001%), accurate detection of carcinoma cells was achieved with PE-labeled anti-cytokeratin monoclonal antibody. Furthermore, verification of carcinoma cells in the microchambers was performed by double staining with the above monoclonal antibodies. Conclusion The potential application of the cell microarray chip for the detection of CTCs was shown, thus demonstrating accurate detection by double staining for cytokeratin and EpCAM at the single carcinoma cell level. PMID:22396762

  13. Is the ISAC 112 Microarray Useful in the Diagnosis of Pollinosis in Spain?

    Science.gov (United States)

    García, B E; Martínez-Aranguren, R; Bernard Alonso, A; Gamboa, P; Feo Brito, F; Bartra, J; Blanca-López, N; Gómez, F; Alvarado, M I; Fernández, J; Alonso, M D; Gonzalez-Mancebo, E; Moya, C; Parra, A; Terrados, S; Sola, L; Goikoetxea, M J; Sanz, M L

    2016-01-01

    Multiple sensitization is frequent among pollen-allergic patients. The goal of this study was to determine the diagnostic accuracy of the ImmunoCAP ISAC 112 (ISAC112) microarray in allergy to pollen from several taxa and its clinical utility in a Spanish population. Specific IgE was determined in 390 pollen-allergic patients using the ISAC112 microarray. Diagnostic accuracy (sensitivity, specificity, predictive values, and area under the ROC curve) was calculated for the diagnosis of allergy to pollen from grass (n=49), cypress (n=75), olive tree (n=33), plane tree (n=63), and pellitory of the wall (n=17) and compared with that of the singleplex ImmunoCAP immunoassay. The sensitivity of the ISAC112 microarray ranged from 68.2% for allergy to plane tree pollen to 93.9% for allergy to grass pollen. The specificity was >90%. The AUC for the diagnosis of allergy to plane tree pollen was 0.798, whereas the AUC for the remaining cases was ≥0.876. The accuracy of ISAC112 was higher than that of ImmunoCAP for plane tree pollen and similar for the remaining pollens. The frequency of sensitization to most species-specific allergenic components and profilins varied between the different geographical regions studied. A total of 73% of pollen-allergic patients were sensitized to species-specific components of more than 1 pollen type. The ISAC112 microarray is an accurate tool for the diagnosis of allergy to pollen from grass, cypress, olive tree, plane tree, and pellitory of the wall. The features of the ISAC112 microarray are similar or superior (in the case of plane tree pollen) to those of ImmunoCAP. This microarray is particularly useful for the etiologic diagnosis of pollinosis in patients sensitized to multiple pollen species whose pollination periods overlap.

  14. Multi-Gene Detection and Identification of Mosquito-Borne RNA Viruses Using an Oligonucleotide Microarray

    Science.gov (United States)

    Grubaugh, Nathan D.; McMenamy, Scott S.; Turell, Michael J.; Lee, John S.

    2013-01-01

    Background Arthropod-borne viruses are important emerging pathogens world-wide. Viruses transmitted by mosquitoes, such as dengue, yellow fever, and Japanese encephalitis viruses, infect hundreds of millions of people and animals each year. Global surveillance of these viruses in mosquito vectors using molecular based assays is critical for prevention and control of the associated diseases. Here, we report an oligonucleotide DNA microarray design, termed ArboChip5.1, for multi-gene detection and identification of mosquito-borne RNA viruses from the genera Flavivirus (family Flaviviridae), Alphavirus (Togaviridae), Orthobunyavirus (Bunyaviridae), and Phlebovirus (Bunyaviridae). Methodology/Principal Findings The assay utilizes targeted PCR amplification of three genes from each virus genus for electrochemical detection on a portable, field-tested microarray platform. Fifty-two viruses propagated in cell-culture were used to evaluate the specificity of the PCR primer sets and the ArboChip5.1 microarray capture probes. The microarray detected all of the tested viruses and differentiated between many closely related viruses such as members of the dengue, Japanese encephalitis, and Semliki Forest virus clades. Laboratory infected mosquitoes were used to simulate field samples and to determine the limits of detection. Additionally, we identified dengue virus type 3, Japanese encephalitis virus, Tembusu virus, Culex flavivirus, and a Quang Binh-like virus from mosquitoes collected in Thailand in 2011 and 2012. Conclusions/Significance We demonstrated that the described assay can be utilized in a comprehensive field surveillance program by the broad-range amplification and specific identification of arboviruses from infected mosquitoes. Furthermore, the microarray platform can be deployed in the field and viral RNA extraction to data analysis can occur in as little as 12 h. The information derived from the ArboChip5.1 microarray can help to establish public health

  15. Immunohistochemistry - microarray analysis of patients with peritoneal metastases of appendiceal or colorectal origin.

    Science.gov (United States)

    Green, Danielle E; Jayakrishnan, Thejus T; Hwang, Michael; Pappas, Sam G; Gamblin, T Clark; Turaga, Kiran K

    2014-01-01

    The value of immunohistochemistry (IHC)-microarray analysis of pathological specimens in the management of patients is controversial, although preliminary data suggest potential benefit. We describe the characteristics of patients undergoing a commercially available IHC-microarray method in patients with peritoneal metastases (PM) and the feasibility of this technique in this population. We retrospectively analyzed consecutive patients with pathologically confirmed PM from appendiceal or colorectal primary who underwent Caris Molecular Intelligence(™) testing. IHC, microarray, FISH, and mutational analysis were included and stratified by Peritoneal Carcinomatosis Index (PCI) score, histology, and treatment characteristics. Statistical analysis was performed using non-parametric tests. Our study included 5 patients with appendiceal and 11 with colorectal PM. The median age of patients was 51 (IQR 39-65) years, with 11 (68%) female. The median PCI score of the patients was 17 (IQR 10-25). Hyperthermic intra-peritoneal chemoperfusion was performed in 4 (80%) patients with appendiceal primary tumors and 4 (36%) with colorectal primary. KRAS mutations were encountered in 40% of appendiceal vs. 30% colorectal tumors, while BRAF mutations were seen in 40% of colorectal PM and none of the patients with appendiceal PM (p = 0.06). IHC biomarker expression was not significantly different between the two primaries. Sufficient tumor for microarray analysis was found in 44% (n = 7) patients, which was not associated with previous use of chemotherapy (p > 0.20 for 5-FU/LV, Irinotecan and Oxaliplatin). In a small sample of patients with PM, the feasibility and results of IHC-microarray staining based on a commercially available test is reported. The apparent high incidence of the BRAF mutation in patients with PM may potentially offer opportunities for novel therapeutics and suggest that IHC-microarray is a method that can be used in this population.

  16. Improving FoRe: A New Inlet Design for Filtering Samples through Individual Microarray Spots.

    Science.gov (United States)

    de Lange, Victoria; Habegger, Marco; Schmidt, Marco; Vörös, János

    2017-03-24

    In this publication we present an improvement to our previously introduced vertical flow microarray, the FoRe array, which capitalizes on the fusion of immunofiltration and densely packed micron test sites. Filtering samples through individual microarray spots allows us to rapidly analyze dilute samples with high-throughput and high signal-to-noise. Unlike other flowthrough microarrays, in the FoRe design samples are injected into micron channels and sequentially exposed to different targets. This arrangement makes it possible to increase the sensitivity of the microarray by simply increasing the sample volume or to rapidly reconcentrate samples after preprocessing steps dilute the analyte. Here we present a new inlet system which allows us to increase the analyzed sample volume without compromising the micron spot size and dense layout. We combined this with a model assay to demonstrate that the device is sensitive to the amount of antigen, and as a result, sample volume directly correlates to sensitivity. We introduced a simple technique for analysis of blood, which previously clogged the nanometer-sized pores, requiring only microliter volumes expected from an infant heel prick. A drop of blood is mixed with buffer to separate the plasma before reconcentrating the sample on the microarray spot. We demonstrated the success of this procedure by spiking TNF-α into blood and achieved a limit of detection of 18 pM. Compared to traditional protein microarrays, the FoRe array is still inexpensive, customizable, and simple to use, and thanks to these improvements has a broad range of applications from small animal studies to environmental monitoring.

  17. Design, construction and validation of a Plasmodium vivax microarray for the transcriptome profiling of clinical isolates

    KAUST Repository

    Boopathi, Pon Arunachalam

    2016-10-09

    High density oligonucleotide microarrays have been used on Plasmodium vivax field isolates to estimate whole genome expression. However, no microarray platform has been experimentally optimized for studying the transcriptome of field isolates. In the present study, we adopted both bioinformatics and experimental testing approaches to select best optimized probes suitable for detecting parasite transcripts from field samples and included them in designing a custom 15K P. vivax microarray. This microarray has long oligonucleotide probes (60 mer) that were in-situ synthesized onto glass slides using Agilent SurePrint technology and has been developed into an 8X15K format (8 identical arrays on a single slide). Probes in this array were experimentally validated and represents 4180 P. vivax genes in sense orientation, of which 1219 genes have also probes in antisense orientation. Validation of the 15K array by using field samples (n =14) has shown 99% of parasite transcript detection from any of the samples. Correlation analysis between duplicate probes (n = 85) present in the arrays showed perfect correlation (r(2) = 0.98) indicating the reproducibility. Multiple probes representing the same gene exhibited similar kind of expression pattern across the samples (positive correlation, r >= 0.6). Comparison of hybridization data with the previous studies and quantitative real-time PCR experiments were performed to highlight the microarray validation procedure. This array is unique in its design, and results indicate that the array is sensitive and reproducible. Hence, this microarray could be a valuable functional genomics tool to generate reliable expression data from P. vivax field isolates. (C) 2016 Published by Elsevier B.V.

  18. Accurate detection of carcinoma cells by use of a cell microarray chip.

    Directory of Open Access Journals (Sweden)

    Shohei Yamamura

    Full Text Available BACKGROUND: Accurate detection and analysis of circulating tumor cells plays an important role in the diagnosis and treatment of metastatic cancer treatment. METHODS AND FINDINGS: A cell microarray chip was used to detect spiked carcinoma cells among leukocytes. The chip, with 20,944 microchambers (105 µm width and 50 µm depth, was made from polystyrene; and the formation of monolayers of leukocytes in the microchambers was observed. Cultured human T lymphoblastoid leukemia (CCRF-CEM cells were used to examine the potential of the cell microarray chip for the detection of spiked carcinoma cells. A T lymphoblastoid leukemia suspension was dispersed on the chip surface, followed by 15 min standing to allow the leukocytes to settle down into the microchambers. Approximately 29 leukocytes were found in each microchamber when about 600,000 leukocytes in total were dispersed onto a cell microarray chip. Similarly, when leukocytes isolated from human whole blood were used, approximately 89 leukocytes entered each microchamber when about 1,800,000 leukocytes in total were placed onto the cell microarray chip. After washing the chip surface, PE-labeled anti-cytokeratin monoclonal antibody and APC-labeled anti-CD326 (EpCAM monoclonal antibody solution were dispersed onto the chip surface and allowed to react for 15 min; and then a microarray scanner was employed to detect any fluorescence-positive cells within 20 min. In the experiments using spiked carcinoma cells (NCI-H1650, 0.01 to 0.0001%, accurate detection of carcinoma cells was achieved with PE-labeled anti-cytokeratin monoclonal antibody. Furthermore, verification of carcinoma cells in the microchambers was performed by double staining with the above monoclonal antibodies. CONCLUSION: The potential application of the cell microarray chip for the detection of CTCs was shown, thus demonstrating accurate detection by double staining for cytokeratin and EpCAM at the single carcinoma cell level.

  19. Multi-gene detection and identification of mosquito-borne RNA viruses using an oligonucleotide microarray.

    Directory of Open Access Journals (Sweden)

    Nathan D Grubaugh

    Full Text Available BACKGROUND: Arthropod-borne viruses are important emerging pathogens world-wide. Viruses transmitted by mosquitoes, such as dengue, yellow fever, and Japanese encephalitis viruses, infect hundreds of millions of people and animals each year. Global surveillance of these viruses in mosquito vectors using molecular based assays is critical for prevention and control of the associated diseases. Here, we report an oligonucleotide DNA microarray design, termed ArboChip5.1, for multi-gene detection and identification of mosquito-borne RNA viruses from the genera Flavivirus (family Flaviviridae, Alphavirus (Togaviridae, Orthobunyavirus (Bunyaviridae, and Phlebovirus (Bunyaviridae. METHODOLOGY/PRINCIPAL FINDINGS: The assay utilizes targeted PCR amplification of three genes from each virus genus for electrochemical detection on a portable, field-tested microarray platform. Fifty-two viruses propagated in cell-culture were used to evaluate the specificity of the PCR primer sets and the ArboChip5.1 microarray capture probes. The microarray detected all of the tested viruses and differentiated between many closely related viruses such as members of the dengue, Japanese encephalitis, and Semliki Forest virus clades. Laboratory infected mosquitoes were used to simulate field samples and to determine the limits of detection. Additionally, we identified dengue virus type 3, Japanese encephalitis virus, Tembusu virus, Culex flavivirus, and a Quang Binh-like virus from mosquitoes collected in Thailand in 2011 and 2012. CONCLUSIONS/SIGNIFICANCE: We demonstrated that the described assay can be utilized in a comprehensive field surveillance program by the broad-range amplification and specific identification of arboviruses from infected mosquitoes. Furthermore, the microarray platform can be deployed in the field and viral RNA extraction to data analysis can occur in as little as 12 h. The information derived from the ArboChip5.1 microarray can help to establish

  20. Rapid and highly sensitive detection of malaria-infected erythrocytes using a cell microarray chip.

    Directory of Open Access Journals (Sweden)

    Shouki Yatsushiro

    Full Text Available BACKGROUND: Malaria is one of the major human infectious diseases in many endemic countries. For prevention of the spread of malaria, it is necessary to develop an early, sensitive, accurate and conventional diagnosis system. METHODS AND FINDINGS: A cell microarray chip was used to detect for malaria-infected erythrocytes. The chip, with 20,944 microchambers (105 µm width and 50 µm depth, was made from polystyrene, and the formation of monolayers of erythrocytes in the microchambers was observed. Cultured Plasmodium falciparum strain 3D7 was used to examine the potential of the cell microarray chip for malaria diagnosis. An erythrocyte suspension in a nuclear staining dye, SYTO 59, was dispersed on the chip surface, followed by 10 min standing to allow the erythrocytes to settle down into the microchambers. About 130 erythrocytes were accommodated in each microchamber, there being over 2,700,000 erythrocytes in total on a chip. A microarray scanner was employed to detect any fluorescence-positive erythrocytes within 5 min, and 0.0001% parasitemia could be detected. To examine the contamination by leukocytes of purified erythrocytes from human blood, 20 µl of whole blood was mixed with 10 ml of RPMI 1640, and the mixture was passed through a leukocyte isolation filter. The eluted portion was centrifuged at 1,000×g for 2 min, and the pellet was dispersed in 1.0 ml of medium. SYTO 59 was added to the erythrocyte suspension, followed by analysis on a cell microarray chip. Similar accommodation of cells in the microchambers was observed. The number of contaminating leukocytes was less than 1 on a cell microarray chip. CONCLUSION: The potential of the cell microarray chip for the detection of malaria-infected erythrocytes was shown, it offering 10-100 times higher sensitivity than that of conventional light microscopy and easy operation in 15 min with purified erythrocytes.

  1. Exploring the use of internal and externalcontrols for assessing microarray technical performance

    Directory of Open Access Journals (Sweden)

    Game Laurence

    2010-12-01

    Full Text Available Abstract Background The maturing of gene expression microarray technology and interest in the use of microarray-based applications for clinical and diagnostic applications calls for quantitative measures of quality. This manuscript presents a retrospective study characterizing several approaches to assess technical performance of microarray data measured on the Affymetrix GeneChip platform, including whole-array metrics and information from a standard mixture of external spike-in and endogenous internal controls. Spike-in controls were found to carry the same information about technical performance as whole-array metrics and endogenous "housekeeping" genes. These results support the use of spike-in controls as general tools for performance assessment across time, experimenters and array batches, suggesting that they have potential for comparison of microarray data generated across species using different technologies. Results A layered PCA modeling methodology that uses data from a number of classes of controls (spike-in hybridization, spike-in polyA+, internal RNA degradation, endogenous or "housekeeping genes" was used for the assessment of microarray data quality. The controls provide information on multiple stages of the experimental protocol (e.g., hybridization, RNA amplification. External spike-in, hybridization and RNA labeling controls provide information related to both assay and hybridization performance whereas internal endogenous controls provide quality information on the biological sample. We find that the variance of the data generated from the external and internal controls carries critical information about technical performance; the PCA dissection of this variance is consistent with whole-array quality assessment based on a number of quality assurance/quality control (QA/QC metrics. Conclusions These results provide support for the use of both external and internal RNA control data to assess the technical quality of microarray

  2. Evaluation of a gene information summarization system by users during the analysis process of microarray datasets

    Directory of Open Access Journals (Sweden)

    Cohen Aaron

    2009-02-01

    Full Text Available Abstract Background Summarization of gene information in the literature has the potential to help genomics researchers translate basic research into clinical benefits. Gene expression microarrays have been used to study biomarkers for disease and discover novel types of therapeutics and the task of finding information in journal articles on sets of genes is common for translational researchers working with microarray data. However, manually searching and scanning the literature references returned from PubMed is a time-consuming task for scientists. We built and evaluated an automatic summarizer of information on genes studied in microarray experiments. The Gene Information Clustering and Summarization System (GICSS is a system that integrates two related steps of the microarray data analysis process: functional gene clustering and gene information gathering. The system evaluation was conducted during the process of genomic researchers analyzing their own experimental microarray datasets. Results The clusters generated by GICSS were validated by scientists during their microarray analysis process. In addition, presenting sentences in the abstract provided significantly more important information to the users than just showing the title in the default PubMed format. Conclusion The evaluation results suggest that GICSS can be useful for researchers in genomic area. In addition, the hybrid evaluation method, partway between intrinsic and extrinsic system evaluation, may enable researchers to gauge the true usefulness of the tool for the scientists in their natural analysis workflow and also elicit suggestions for future enhancements. Availability GICSS can be accessed online at: http://ir.ohsu.edu/jianji/index.html

  3. In silico design and performance of peptide microarrays for breast cancer tumour-auto-antibody testing

    Directory of Open Access Journals (Sweden)

    Andreas Weinhäusel

    2012-06-01

    Full Text Available The simplicity and potential of minimally invasive testing using sera from patients makes auto-antibody based biomarkers a very promising tool for use in cancer diagnostics. Protein microarrays have been used for the identification of such auto-antibody signatures. Because high throughput protein expression and purification is laborious, synthetic peptides might be a good alternative for microarray generation and multiplexed analyses. In this study, we designed 1185 antigenic peptides, deduced from proteins expressed by 642 cDNA expression clones found to be sero-reactive in both breast tumour patients and controls. The sero-reactive proteins and the corresponding peptides were used for the production of protein and peptide microarrays. Serum samples from females with benign and malignant breast tumours and healthy control sera (n=16 per group were then analysed. Correct classification of the serum samples on peptide microarrays were 78% for discrimination of ‘malignant versus healthy controls’, 72% for ‘benign versus malignant’ and 94% for ‘benign versus controls’. On protein arrays, correct classification for these contrasts was 69%, 59% and 59%, respectively. The over-representation analysis of the classifiers derived from class prediction showed enrichment of genes associated with ribosomes, spliceosomes, endocytosis and the pentose phosphate pathway. Sequence analyses of the peptides with the highest sero-reactivity demonstrated enrichment of the zinc-finger domain. Peptides’ sero-reactivities were found negatively correlated with hydrophobicity and positively correlated with positive charge, high inter-residue protein contact energies and a secondary structure propensity bias. This study hints at the possibility of using in silico designed antigenic peptide microarrays as an alternative to protein microarrays for the improvement of tumour auto-antibody based diagnostics.

  4. Screening microarrays of novel monoclonal antibodies for binding to T-, B- and myeloid leukaemia cells.

    Science.gov (United States)

    Belov, Larissa; Huang, Pauline; Chrisp, Jeremy S; Mulligan, Stephen P; Christopherson, Richard I

    2005-10-20

    We have developed a microarray (DotScan) that enables rapid immunophenotyping and classification of leukaemias and lymphomas by measuring the capture of cells by immobilized dots of 82 CD antibodies [Belov, L., de la Vega, O., dos Remedios, C.G., Mulligan, S.P., 2001. Immunophenotyping of leukemia using a cluster of differentiation antibody microarray. Cancer Res. 61, 4483; Belov, L., Huang, P., Barber, N., Mulligan, S.P., Christopherson, R.I., 2003. Identification of repertoires of surface antigens on leukemias using an antibody microarray. Proteomics 3, 2147]. The DotScan technology has been used to investigate the properties of 498 new antibodies submitted to the HLDA8 Workshop. These antibodies have been applied as 10 nl dots to a film of nitrocellulose on a microscope slide to make an HLDA8 microarray. After blocking the remaining nitrocellulose surface, individual arrays were incubated with each of 7 cell types from a human leukaemia cell panel consisting of three cell lines, CCRF-CEM (a T-cell acute lymphocytic leukaemia), MEC-1 (derived from B-cell chronic lymphocytic leukaemia) and HL-60 (a promyelocytic leukaemia), and four leukaemias from patients: a T-cell prolymphocytic leukaemia, a B-cell chronic lymphocytic leukaemia, and two acute myeloid leukaemias. Leukaemia cells were captured by those immobilized antibodies for which they expressed the corresponding surface molecule. Unbound cells were gently washed off, bound cells were fixed to the arrays and dot patterns were recorded using a DotScan array reader and quantified using DotScan data analysis software. The data obtained show the unique expression profiles of the 7 cell types in the leukaemia cell panel obtained with the DotScan microarray, and the differential capture patterns for these 7 cell types screened against the 498 antibodies in the HLDA8 microarray constructed for this study.

  5. ArrayQuest: a web resource for the analysis of DNA microarray data

    Directory of Open Access Journals (Sweden)

    Barth Jeremy L

    2005-12-01

    Full Text Available Abstract Background Numerous microarray analysis programs have been created through the efforts of Open Source software development projects. Providing browser-based interfaces that allow these programs to be executed over the Internet enhances the applicability and utility of these analytic software tools. Results Here we present ArrayQuest, a web-based DNA microarray analysis process controller. Key features of ArrayQuest are that (1 it is capable of executing numerous analysis programs such as those written in R, BioPerl and C++; (2 new analysis programs can be added to ArrayQuest Methods Library at the request of users or developers; (3 input DNA microarray data can be selected from public databases (i.e., the Medical University of South Carolina (MUSC DNA Microarray Database or Gene Expression Omnibus (GEO or it can be uploaded to the ArrayQuest center-point web server into a password-protected area; and (4 analysis jobs are distributed across computers configured in a backend cluster. To demonstrate the utility of ArrayQuest we have populated the methods library with methods for analysis of Affymetrix DNA microarray data. Conclusion ArrayQuest enables browser-based implementation of DNA microarray data analysis programs that can be executed on a Linux-based platform. Importantly, ArrayQuest is a platform that will facilitate the distribution and implementation of new analysis algorithms and is therefore of use to both developers of analysis applications as well as users. ArrayQuest is freely available for use at http://proteogenomics.musc.edu/arrayquest.html.

  6. FiGS: a filter-based gene selection workbench for microarray data

    Directory of Open Access Journals (Sweden)

    Yun Taegyun

    2010-01-01

    Full Text Available Abstract Background The selection of genes that discriminate disease classes from microarray data is widely used for the identification of diagnostic biomarkers. Although various gene selection methods are currently available and some of them have shown excellent performance, no single method can retain the best performance for all types of microarray datasets. It is desirable to use a comparative approach to find the best gene selection result after rigorous test of different methodological strategies for a given microarray dataset. Results FiGS is a web-based workbench that automatically compares various gene selection procedures and provides the optimal gene selection result for an input microarray dataset. FiGS builds up diverse gene selection procedures by aligning different feature selection techniques and classifiers. In addition to the highly reputed techniques, FiGS diversifies the gene selection procedures by incorporating gene clustering options in the feature selection step and different data pre-processing options in classifier training step. All candidate gene selection procedures are evaluated by the .632+ bootstrap errors and listed with their classification accuracies and selected gene sets. FiGS runs on parallelized computing nodes that capacitate heavy computations. FiGS is freely accessible at http://gexp.kaist.ac.kr/figs. Conclusion FiGS is an web-based application that automates an extensive search for the optimized gene selection analysis for a microarray dataset in a parallel computing environment. FiGS will provide both an efficient and comprehensive means of acquiring optimal gene sets that discriminate disease states from microarray datasets.

  7. Evaluation of artificial time series microarray data for dynamic gene regulatory network inference.

    Science.gov (United States)

    Xenitidis, P; Seimenis, I; Kakolyris, S; Adamopoulos, A

    2017-08-07

    High-throughput technology like microarrays is widely used in the inference of gene regulatory networks (GRNs). We focused on time series data since we are interested in the dynamics of GRNs and the identification of dynamic networks. We evaluated the amount of information that exists in artificial time series microarray data and the ability of an inference process to produce accurate models based on them. We used dynamic artificial gene regulatory networks in order to create artificial microarray data. Key features that characterize microarray data such as the time separation of directly triggered genes, the percentage of directly triggered genes and the triggering function type were altered in order to reveal the limits that are imposed by the nature of microarray data on the inference process. We examined the effect of various factors on the inference performance such as the network size, the presence of noise in microarray data, and the network sparseness. We used a system theory approach and examined the relationship between the pole placement of the inferred system and the inference performance. We examined the relationship between the inference performance in the time domain and the true system parameter identification. Simulation results indicated that time separation and the percentage of directly triggered genes are crucial factors. Also, network sparseness, the triggering function type and noise in input data affect the inference performance. When two factors were simultaneously varied, it was found that variation of one parameter significantly affects the dynamic response of the other. Crucial factors were also examined using a real GRN and acquired results confirmed simulation findings with artificial data. Different initial conditions were also used as an alternative triggering approach. Relevant results confirmed that the number of datasets constitutes the most significant parameter with regard to the inference performance. Copyright © 2017 Elsevier

  8. Comparison of Alexa Fluor and CyDye for practical DNA microarray use.

    Science.gov (United States)

    Ballard, Joanne L; Peeva, Violet K; deSilva, Christopher J S; Lynch, Jessica L; Swanson, Nigel R

    2007-07-01

    Microarrays are a powerful tool for comparison and understanding of gene expression levels in healthy and diseased states. The method relies upon the assumption that signals from microarray features are a reflection of relative gene expression levels of the cell types under investigation. It has previously been reported that the classical fluorescent dyes used for microarray technology, Cy3 and Cy5, are not ideal due to the decreased stability and fluorescence intensity of the Cy5 dye relative to the Cy3, such that dye bias is an accepted phenomena necessitating dye swap experimental protocols and analysis of differential dye affects. The incentive to find new fluorophores is based on alleviating the problem of dye bias through synonymous performance between counterpart dyes. Alexa Fluor 555 and Alexa Fluor 647 are increasingly promoted as replacements for CyDye in microarray experiments. Performance relates to the molecular and steric similarities, which will vary for each new pair of dyes as well as the spectral integrity for the specific application required. Comparative analysis of the performance of these two competitive dye pairs in practical microarray applications is warranted towards this end. The findings of our study showed that both dye pairs were comparable but that conventional CyDye resulted in significantly higher signal intensities (P 0.05). This translated to greater levels of differential gene expression with CyDye than with the Alexa Fluor counterparts. However, CyDye fluorophores and in particular Cy5, were found to be less photostable over time and following repeated scans in microarray experiments. These results suggest that precautions against potential dye affects will continue to be necessary and that no one dye pair negates this need.

  9. Serious limitations of the QTL/Microarray approach for QTL gene discovery

    Directory of Open Access Journals (Sweden)

    Warden Craig H

    2010-07-01

    Full Text Available Abstract Background It has been proposed that the use of gene expression microarrays in nonrecombinant parental or congenic strains can accelerate the process of isolating individual genes underlying quantitative trait loci (QTL. However, the effectiveness of this approach has not been assessed. Results Thirty-seven studies that have implemented the QTL/microarray approach in rodents were reviewed. About 30% of studies showed enrichment for QTL candidates, mostly in comparisons between congenic and background strains. Three studies led to the identification of an underlying QTL gene. To complement the literature results, a microarray experiment was performed using three mouse congenic strains isolating the effects of at least 25 biometric QTL. Results show that genes in the congenic donor regions were preferentially selected. However, within donor regions, the distribution of differentially expressed genes was homogeneous once gene density was accounted for. Genes within identical-by-descent (IBD regions were less likely to be differentially expressed in chromosome 2, but not in chromosomes 11 and 17. Furthermore, expression of QTL regulated in cis (cis eQTL showed higher expression in the background genotype, which was partially explained by the presence of single nucleotide polymorphisms (SNP. Conclusions The literature shows limited successes from the QTL/microarray approach to identify QTL genes. Our own results from microarray profiling of three congenic strains revealed a strong tendency to select cis-eQTL over trans-eQTL. IBD regions had little effect on rate of differential expression, and we provide several reasons why IBD should not be used to discard eQTL candidates. In addition, mismatch probes produced false cis-eQTL that could not be completely removed with the current strains genotypes and low probe density microarrays. The reviewed studies did not account for lack of coverage from the platforms used and therefore removed genes

  10. ArrayWiki: an enabling technology for sharing public microarray data repositories and meta-analyses.

    Science.gov (United States)

    Stokes, Todd H; Torrance, J T; Li, Henry; Wang, May D

    2008-05-28

    A survey of microarray databases reveals that most of the repository contents and data models are heterogeneous (i.e., data obtained from different chip manufacturers), and that the repositories provide only basic biological keywords linking to PubMed. As a result, it is difficult to find datasets using research context or analysis parameters information beyond a few keywords. For example, to reduce the "curse-of-dimension" problem in microarray analysis, the number of samples is often increased by merging array data from different datasets. Knowing chip data parameters such as pre-processing steps (e.g., normalization, artefact removal, etc), and knowing any previous biological validation of the dataset is essential due to the heterogeneity of the data. However, most of the microarray repositories do not have meta-data information in the first place, and do not have a a mechanism to add or insert this information. Thus, there is a critical need to create "intelligent" microarray repositories that (1) enable update of meta-data with the raw array data, and (2) provide standardized archiving protocols to minimize bias from the raw data sources. To address the problems discussed, we have developed a community maintained system called ArrayWiki that unites disparate meta-data of microarray meta-experiments from multiple primary sources with four key features. First, ArrayWiki provides a user-friendly knowledge management interface in addition to a programmable interface using standards developed by Wikipedia. Second, ArrayWiki includes automated quality control processes (caCORRECT) and novel visualization methods (BioPNG, Gel Plots), which provide extra information about data quality unavailable in other microarray repositories. Third, it provides a user-curation capability through the familiar Wiki interface. Fourth, ArrayWiki provides users with simple text-based searches across all experiment meta-data, and exposes data to search engine crawlers (Semantic Agents

  11. A pilot study of transcription unit analysis in rice using oligonucleotide tiling-path microarray

    DEFF Research Database (Denmark)

    Stolc, Viktor; Li, Lei; Wang, Xiangfeng

    2005-01-01

    As the international efforts to sequence the rice genome are completed, an immediate challenge and opportunity is to comprehensively and accurately define all transcription units in the rice genome. Here we describe a strategy of using high-density oligonucleotide tiling-path microarrays to map...... gene models in a mixture of four RNA populations. Moreover, significant transcriptional activities were found in many of the previously annotated intergenic regions. These preliminary results demonstrate the utility of genome tiling microarrays in evaluating annotated rice gene models...

  12. Functional profiling of microarray experiments using text-mining derived bioentities.

    Science.gov (United States)

    Minguez, Pablo; Al-Shahrour, Fátima; Montaner, David; Dopazo, Joaquín

    2007-11-15

    The increasing use of microarray technologies brought about a parallel demand in methods for the functional interpretation of the results. Beyond the conventional functional annotations for genes, such as gene ontology, pathways, etc. other sources of information are still to be exploited. Text-mining methods allow extracting informative terms (bioentities) with different functional, chemical, clinical, etc. meanings, that can be associated to genes. We show how to use these associations within an appropriate statistical framework and how to apply them through easy-to-use, web-based environments to the functional interpretation of microarray experiments. Functional enrichment and gene set enrichment tests using bioentities are presented.

  13. Synthesis of O-glycopeptides and construction of glycopeptide microarrays

    DEFF Research Database (Denmark)

    Blixt, Klas Ola; Cló, Emiliano

    2013-01-01

    O-glycosylation of proteins is an important modification which affects biological function and immunity. In this chapter, we provide protocols for efficient solid-phase O-glycopeptide synthesis (SPGPS) and protocols for the construction of glycopeptide microarray chips for screening applications....... This will be exemplified for mucin-type glycopeptides and the construction of glycopeptide microarrays. To this end, the protocols provided are particularly suited for small-scale robotic parallel synthesis. N-Terminal amine capping of deletion peptides during synthesis stands out as vital to this strategy. It allows...

  14. A Tool for Sheep Product Quality: Custom Microarrays from Public Databases

    Directory of Open Access Journals (Sweden)

    Lorraine Pariset

    2009-12-01

    Full Text Available Milk and dairy products are an essential food and an economic resource in many countries. Milk component synthesis and secretion by the mammary gland involve expression of a large number of genes whose nutritional regulation remains poorly defined. The purpose of this study was to gain an understanding of the genomic influence on milk quality and synthesis by comparing two sheep breeds with different milking attitude (Sarda and Gentile di Puglia using sheep-specific microarray technology. From sheep ESTs deposited at NCBI, we have generated the first annotated microarray developed for sheep with a coverage of most of the genome.

  15. An oligonucleotide-tagged microarray for routine diagnostics of colon cancer by genotyping KRAS mutations

    DEFF Research Database (Denmark)

    Liu, Yuliang; Guðnason, Haukur; Li, Yiping

    2014-01-01

    mutations at codon 12 of KRAS derived from cancer cells and clinical samples could be unambiguously detected. KRAS mutations were accurately detected when the mutant DNA was present only in 10% of the starting mixed materials including wild-type genomic DNA, which was isolated from either cancer cells...... or spiked fecal samples. The immobilized tag-probes were stable under multiple thermal cycling treatments, allowing re-use of the tag-microarray and further optimization to solid PCR. Our results demonstrated that a novel oligonucleotide-tagged microarray system has been developed which would be suitable...

  16. Ontology-based retrieval of bio-medical information based on microarray text corpora

    DEFF Research Database (Denmark)

    Hansen, Kim Allan; Zambach, Sine; Have, Christian Theil

    Microarray technology is often used in gene expression exper- iments. Information retrieval in the context of microarrays has mainly been concerned with the analysis of the numeric data produced; how- ever, the experiments are often annotated with textual metadata. Al- though biomedical resources...... are exponentially growing, the text corpora are sparse and inconsistent in spite of attempts to standardize the format. Ordinary keyword search may in some cases be insucient to nd rele- vant information and the potential benet of using a semantic approach in this context has only been investigated to a limited...

  17. Goober: A fully integrated and user-friendly microarray data management and analysis solution for core labs and bench biologists

    Directory of Open Access Journals (Sweden)

    Luo Wen

    2009-03-01

    Full Text Available Despite the large number of software tools developed to address different areas of microarray data analysis, very few offer an all-in-one solution with little learning curve. For microarray core labs, there are even fewer software packages available to help with their routine but critical tasks, such as data quality control (QC and inventory management. We have developed a simple-to-use web portal to allow bench biologists to analyze and query complicated microarray data and related biological pathways without prior training. Both experiment-based and gene-based analysis can be easily performed, even for the first-time user, through the intuitive multi-layer design and interactive graphic links. While being friendly to inexperienced users, most parameters in Goober can be easily adjusted via drop-down menus to allow advanced users to tailor their needs and perform more complicated analysis. Moreover, we have integrated graphic pathway analysis into the website to help users examine microarray data within the relevant biological content. Goober also contains features that cover most of the common tasks in microarray core labs, such as real time array QC, data loading, array usage and inventory tracking. Overall, Goober is a complete microarray solution to help biologists instantly discover valuable information from a microarray experiment and enhance the quality and productivity of microarray core labs. The whole package is freely available at http://sourceforge.net/projects/goober. A demo web server is available at http://www.goober-array.org.

  18. A rapid automatic processing platform for bead label-assisted microarray analysis: application for genetic hearing-loss mutation detection.

    Science.gov (United States)

    Zhu, Jiang; Song, Xiumei; Xiang, Guangxin; Feng, Zhengde; Guo, Hongju; Mei, Danyang; Zhang, Guohao; Wang, Dong; Mitchelson, Keith; Xing, Wanli; Cheng, Jing

    2014-04-01

    Molecular diagnostics using microarrays are increasingly being used in clinical diagnosis because of their high throughput, sensitivity, and accuracy. However, standard microarray processing takes several hours and involves manual steps during hybridization, slide clean up, and imaging. Here we describe the development of an integrated platform that automates these individual steps as well as significantly shortens the processing time and improves reproducibility. The platform integrates such key elements as a microfluidic chip, flow control system, temperature control system, imaging system, and automated analysis of clinical results. Bead labeling of microarray signals required a simple imaging system and allowed continuous monitoring of the microarray processing. To demonstrate utility, the automated platform was used to genotype hereditary hearing-loss gene mutations. Compared with conventional microarray processing procedures, the platform increases the efficiency and reproducibility of hybridization, speeding microarray processing through to result analysis. The platform also continuously monitors the microarray signals, which can be used to facilitate optimization of microarray processing conditions. In addition, the modular design of the platform lends itself to development of simultaneous processing of multiple microfluidic chips. We believe the novel features of the platform will benefit its use in clinical settings in which fast, low-complexity molecular genetic testing is required.

  19. Electron detector

    International Nuclear Information System (INIS)

    Hashimoto, H.; Mogami, A.

    1975-01-01

    A device for measuring electron densities at a given energy level in an electron beam or the like having strong background noise, for example, in the detection of Auger electric energy spectrums is described. An electron analyzer passes electrons at the given energy level and at the same time electrons of at least one adjacent energy level. Detecting means associated therewith produce signals indicative of the densities of the electrons at each energy level and combine these signals to produce a signal indicative of the density of the electrons of the given energy level absent background noise

  20. Discrimination of phytoplasmas using an oligonucleotide microarray targeting rps3, rpl22, and rps19 genes

    Czech Academy of Sciences Publication Activity Database

    Lenz, Ondřej; Marková, J.; Sarkisova, Tatiana; Fránová, Jana; Přibylová, Jaroslava

    2015-01-01

    Roč. 70, January 2015 (2015), s. 47-52 ISSN 0261-2194 Institutional support: RVO:60077344 Keywords : DNA microarray * rpl22 gene * rps19 gene * rps3 gene Subject RIV: EE - Microbiology, Virology Impact factor: 1.652, year: 2015

  1. Gene expression profiling by DNA microarrays and its application to dental research.

    Science.gov (United States)

    Kuo, Winston Patrick; Whipple, Mark E; Sonis, Stephen T; Ohno-Machado, Lucila; Jenssen, Tor-Kristian

    2002-10-01

    DNA microarray technology has been used for genome-wide gene expression studies that incorporate molecular genetics and computer science skills on massive levels. The technology permits the simultaneous analysis of tens of thousands of genes for the purposes of gene discovery, disease diagnosis. improved drug development, and therapeutics tailored to specific disease processes. In this review, the two most common microarray technologies and their potential application to dental research will be discussed. The authors review current articles pertaining to the technologies and analysis of mRNA expression using DNA micro-arrays and its application to dental research. Since many genes contribute to normal functioning, research efforts are moving from the search for a disease specific gene to the understanding of the biochemical and molecular functioning of a variety of genes and how complicated networks of interaction can lead to a disease state, such as oral cancer. With the incorporation of DNA micro-array based research, we can look forward to more accurate diagnosis and surgical treatment/drug-delivery therapy based on an individual patient's genetic profile.

  2. Generation of EST and Microarray Resources for Functional Genomic Studies on Chicken Intestinal Health

    NARCIS (Netherlands)

    Hemert, van S.; Ebbelaar, B.H.; Smits, M.A.; Rebel, J.M.J.

    2003-01-01

    Expressed sequenced tags (ESTs) and microarray resources have a great impact on the ability to study host response in mice and humans. Unfortunately, these resources are not yet available for domestic farm animals. The aim of this study was to provide genomic resources to study chicken intestinal

  3. GPR-Analyzer: a simple tool for quantitative analysis of hierarchical multispecies microarrays.

    Science.gov (United States)

    Dittami, Simon M; Edvardsen, Bente

    2013-10-01

    Monitoring of marine microalgae is important to predict and manage harmful algae blooms. It currently relies mainly on light-microscopic identification and enumeration of algal cells, yet several molecular tools are currently being developed to complement traditional methods. MIcroarray Detection of Toxic ALgae (MIDTAL) is an FP7-funded EU project aiming to establish a hierarchical multispecies microarray as one of these tools. Prototype arrays are currently being tested with field samples, yet the analysis of the large quantities of data generated by these arrays presents a challenge as suitable analysis tools or protocols are scarce. This paper proposes a two-part protocol for the analysis of the MIDTAL and other hierarchical multispecies arrays: Signal-to-noise ratios can be used to determine the presence or absence of signals and to identify potential false-positives considering parallel and hierarchical probes. In addition, normalized total signal intensities are recommended for comparisons between microarrays and in order to relate signals for specific probes to cell concentrations using external calibration curves. Hybridization- and probe-specific detection limits can be calculated to help evaluate negative results. The suggested analyses were implemented in "GPR-Analyzer", a platform-independent and graphical user interface-based application, enabling non-specialist users to quickly and quantitatively analyze hierarchical multispecies microarrays. It is available online at http://folk.uio.no/edvardse/gpranalyzer .

  4. Functional microarray analysis of nitrogen and carbon cycling genes across an Antarctic latitudinal transect.

    NARCIS (Netherlands)

    Yergeau, E.; Kang, S.; He, Z.; Zhou, J.; Kowalchuk, G.A.

    2007-01-01

    Soil-borne microbial communities were examined via a functional gene microarray approach across a southern polar latitudinal gradient to gain insight into the environmental factors steering soil N- and C-cycling in terrestrial Antarctic ecosystems. The abundance and diversity of functional gene

  5. Peptide Microarray Analysis of the Cross-talk Between O-GlcNAcylation and Tyrosine Phosphorylation

    NARCIS (Netherlands)

    Shi, Jie; Tomašič, Tihomir; Sharif, Suhela; Brouwer, Arwin J; Anderluh, Marko; Ruijtenbeek, Rob; Pieters, Roland J

    2017-01-01

    O-GlcNAcylation of proteins regulates important cellular processes. A few reports noted that O-GlcNAcylation exhibits cross-talk with tyrosine phosphorylation. With an activity-based microarray analysis of 256 tyrosine kinase peptide substrates, we found that phosphorylation of 6 peptides by Jak2

  6. Validation of tissue microarray technology in squamous cell carcinoma of the esophagus

    NARCIS (Netherlands)

    Boone, Judith; van Hillegersberg, Richard; van Diest, Paul J.; Offerhaus, G. Johan A.; Borel Rinkes, Inne H. M.; ten Kate, Fiebo J. W.

    2008-01-01

    Tissue microarray (TMA) technology has been developed to facilitate high-throughput immunohistochemical and in situ hybridization analysis of tissues by inserting small tissue biopsy cores into a single paraffin block. Several studies have revealed novel prognostic biomarkers in esophageal squamous

  7. Protein microarray analysis reveals BAFF-binding autoantibodies in systemic lupus erythematosus

    Science.gov (United States)

    Price, Jordan V.; Haddon, David J.; Kemmer, Dodge; Delepine, Guillaume; Mandelbaum, Gil; Jarrell, Justin A.; Gupta, Rohit; Balboni, Imelda; Chakravarty, Eliza F.; Sokolove, Jeremy; Shum, Anthony K.; Anderson, Mark S.; Cheng, Mickie H.; Robinson, William H.; Browne, Sarah K.; Holland, Steven M.; Baechler, Emily C.; Utz, Paul J.

    2013-01-01

    Autoantibodies against cytokines, chemokines, and growth factors inhibit normal immunity and are implicated in inflammatory autoimmune disease and diseases of immune deficiency. In an effort to evaluate serum from autoimmune and immunodeficient patients for Abs against cytokines, chemokines, and growth factors in a high-throughput and unbiased manner, we constructed a multiplex protein microarray for detection of serum factor–binding Abs and used the microarray to detect autoantibody targets in SLE. We designed a nitrocellulose-surface microarray containing human cytokines, chemokines, and other circulating proteins and demonstrated that the array permitted specific detection of serum factor–binding probes. We used the arrays to detect previously described autoantibodies against cytokines in samples from individuals with autoimmune polyendocrine syndrome type 1 and chronic mycobacterial infection. Serum profiling from individuals with SLE revealed that among several targets, elevated IgG autoantibody reactivity to B cell–activating factor (BAFF) was associated with SLE compared with control samples. BAFF reactivity correlated with the severity of disease-associated features, including IFN-α–driven SLE pathology. Our results showed that serum factor protein microarrays facilitate detection of autoantibody reactivity to serum factors in human samples and that BAFF-reactive autoantibodies may be associated with an elevated inflammatory disease state within the spectrum of SLE. PMID:24270423

  8. Microarray Expression Profiles of 20.000 Genes across 23 Healthy Porcine Tissues

    DEFF Research Database (Denmark)

    Hornshøj, Henrik; Conley, Lene Nagstrup; Hedegaard, Jakob

    2007-01-01

    Gene expression microarrays have been intensively applied to screen for genes involved in specific biological processes of interest such as diseases or responses to environmental stimuli. For mammalian species, cataloging of the global gene expression profiles in large tissue collections under...

  9. Cloud-Scale Genomic Signals Processing for Robust Large-Scale Cancer Genomic Microarray Data Analysis.

    Science.gov (United States)

    Harvey, Benjamin Simeon; Ji, Soo-Yeon

    2017-01-01

    As microarray data available to scientists continues to increase in size and complexity, it has become overwhelmingly important to find multiple ways to bring forth oncological inference to the bioinformatics community through the analysis of large-scale cancer genomic (LSCG) DNA and mRNA microarray data that is useful to scientists. Though there have been many attempts to elucidate the issue of bringing forth biological interpretation by means of wavelet preprocessing and classification, there has not been a research effort that focuses on a cloud-scale distributed parallel (CSDP) separable 1-D wavelet decomposition technique for denoising through differential expression thresholding and classification of LSCG microarray data. This research presents a novel methodology that utilizes a CSDP separable 1-D method for wavelet-based transformation in order to initialize a threshold which will retain significantly expressed genes through the denoising process for robust classification of cancer patients. Additionally, the overall study was implemented and encompassed within CSDP environment. The utilization of cloud computing and wavelet-based thresholding for denoising was used for the classification of samples within the Global Cancer Map, Cancer Cell Line Encyclopedia, and The Cancer Genome Atlas. The results proved that separable 1-D parallel distributed wavelet denoising in the cloud and differential expression thresholding increased the computational performance and enabled the generation of higher quality LSCG microarray datasets, which led to more accurate classification results.

  10. Carbohydrate Microarray on Glass: a Tool for Carbohydrate-Lectin Interactions

    NARCIS (Netherlands)

    Tetala, K.K.R.; Giesbers, M.; Visser, G.M.; Sudhölter, E.J.R.; Beek, van T.A.

    2007-01-01

    A simple method to immobilize carbohydrates on a glass surface to obtain a carbohydrate microarray is described. The array was used to study carbohydrate-lectin interactions. The glass surface was modified with aldehyde terminated linker groups of various chain lengths. Coupling of carbohydrates

  11. Functional interaction analysis of GM1-related carbohydrates and Vibrio cholerae toxins using carbohydrate microarray.

    Science.gov (United States)

    Kim, Chang Sup; Seo, Jeong Hyun; Cha, Hyung Joon

    2012-08-07

    The development of analytical tools is important for understanding the infection mechanisms of pathogenic bacteria or viruses. In the present work, a functional carbohydrate microarray combined with a fluorescence immunoassay was developed to analyze the interactions of Vibrio cholerae toxin (ctx) proteins and GM1-related carbohydrates. Ctx proteins were loaded onto the surface-immobilized GM1 pentasaccharide and six related carbohydrates, and their binding affinities were detected immunologically. The analysis of the ctx-carbohydrate interactions revealed that the intrinsic selectivity of ctx was GM1 pentasaccharide ≫ GM2 tetrasaccharide > asialo GM1 tetrasaccharide ≥ GM3trisaccharide, indicating that a two-finger grip formation and the terminal monosaccharides play important roles in the ctx-GM1 interaction. In addition, whole cholera toxin (ctxAB(5)) had a stricter substrate specificity and a stronger binding affinity than only the cholera toxin B subunit (ctxB). On the basis of the quantitative analysis, the carbohydrate microarray showed the sensitivity of detection of the ctxAB(5)-GM1 interaction with a limit-of-detection (LOD) of 2 ng mL(-1) (23 pM), which is comparable to other reported high sensitivity assay tools. In addition, the carbohydrate microarray successfully detected the actual toxin directly secreted from V. cholerae, without showing cross-reactivity to other bacteria. Collectively, these results demonstrate that the functional carbohydrate microarray is suitable for analyzing toxin protein-carbohydrate interactions and can be applied as a biosensor for toxin detection.

  12. Screening for candidate genes related to breast cancer with cDNA microarray analysis

    Directory of Open Access Journals (Sweden)

    Yu-Juan Xiang

    2015-06-01

    Full Text Available Objective: The aim of this study was to reveal the exact changes during the occurrence of breast cancer to explore significant new and promising genes or factors related to this disease. Methods: We compared the gene expression profiles of breast cancer tissues with its uninvolved normal breast tissues as controls using the cDNA microarray analysis in seven breast cancer patients. Further, one representative gene, named IFI30, was quantitatively analyzed by real-time PCR to confirm the result of the cDNA microarray analysis. Results: A total of 427 genes were identified with significantly differential expression, 221 genes were up-regulated and 206 genes were down-regulated. And the result of cDNA microarray analysis was validated by detection of IFI30 mRNA level changes by real-time PCR. Genes for cell proliferation, cell cycle, cell division, mitosis, apoptosis, and immune response were enriched in the up-regulated genes, while genes for cell adhesion, proteolysis, and transport were significantly enriched in the down-regulated genes in breast cancer tissues compared with normal breast tissues by a gene ontology analysis. Conclusion: Our present study revealed a range of differentially expressed genes between breast cancer tissues and normal breast tissues, and provide candidate genes for further study focusing on the pathogenesis and new biomarkers for breast cancer. Keywords: Breast neoplasms, Candidate genes, Microarray

  13. Observation of intermittency in gene expression on cDNA microarrays

    CERN Document Server

    Peterson, L E

    2002-01-01

    We used scaled factorial moments to search for intermittency in the log expression ratios (LERs) for thousands of genes spotted on cDNA microarrays (gene chips). Results indicate varying levels of intermittency in gene expression. The observation of intermittency in the data analyzed provides a complimentary handle on moderately expressed genes, generally not tackled by conventional techniques.

  14. Microarray as a First Genetic Test in Global Developmental Delay: A Cost-Effectiveness Analysis

    Science.gov (United States)

    Trakadis, Yannis; Shevell, Michael

    2011-01-01

    Aim: Microarray technology has a significantly higher clinical yield than karyotyping in individuals with global developmental delay (GDD). Despite this, it has not yet been routinely implemented as a screening test owing to the perception that this approach is more expensive. We aimed to evaluate the effect that replacing karyotype with…

  15. Prenatal chromosomal microarray analysis in fetuses with congenital heart disease: a prospective cohort study.

    Science.gov (United States)

    Wang, Yan; Cao, Li; Liang, Dong; Meng, Lulu; Wu, Yun; Qiao, Fengchang; Ji, Xiuqing; Luo, Chunyu; Zhang, Jingjing; Xu, Tianhui; Yu, Bin; Wang, Leilei; Wang, Ting; Pan, Qiong; Ma, Dingyuan; Hu, Ping; Xu, Zhengfeng

    2018-02-01

    Currently, chromosomal microarray analysis is considered the first-tier test in pediatric care and prenatal diagnosis. However, the diagnostic yield of chromosomal microarray analysis for prenatal diagnosis of congenital heart disease has not been evaluated based on a large cohort. Our aim was to evaluate the clinical utility of chromosomal microarray as the first-tier test for chromosomal abnormalities in fetuses with congenital heart disease. In this prospective study, 602 prenatal cases of congenital heart disease were investigated using single nucleotide polymorphism array over a 5-year period. Overall, pathogenic chromosomal abnormalities were identified in 125 (20.8%) of 602 prenatal cases of congenital heart disease, with 52.0% of them being numerical chromosomal abnormalities. The detection rates of likely pathogenic copy number variations and variants of uncertain significance were 1.3% and 6.0%, respectively. The detection rate of pathogenic chromosomal abnormalities in congenital heart disease plus additional structural anomalies (48.9% vs 14.3%, P microarray analysis is a reliable and high-resolution technology and should be used as the first-tier test for prenatal diagnosis of congenital heart disease in clinical practice. Copyright © 2017 Elsevier Inc. All rights reserved.

  16. Parents' Perceptions of the Usefulness of Chromosomal Microarray Analysis for Children with Autism Spectrum Disorders

    Science.gov (United States)

    Reiff, Marian; Giarelli, Ellen; Bernhardt, Barbara A.; Easley, Ebony; Spinner, Nancy B.; Sankar, Pamela L.; Mulchandani, Surabhi

    2015-01-01

    Clinical guidelines recommend chromosomal microarray analysis (CMA) for all children with autism spectrum disorders (ASDs). We explored the test's perceived usefulness among parents of children with ASD who had undergone CMA, and received a result categorized as pathogenic, variant of uncertain significance, or negative. Fifty-seven parents…

  17. A Comparative Transcriptomics Workflow for Analyzing Microarray Data From CHO Cell Cultures.

    Science.gov (United States)

    Chen, Chun; Le, Huong; Follstad, Brian; Goudar, Chetan T

    2018-03-01

    Microarray-based comparative transcriptomics analysis is a powerful tool to understand therapeutic protein producing mammalian cell lines at the gene expression level. However, an integrated analysis workflow specifically designed for end-to-end analysis of microarray data for CHO cells, the most prevalent host for commercial recombinant protein production, is lacking. To address this gap, an automated data analysis workflow in R that leverages public domain analysis modules is developed to analyze microarray based gene expression data. In addition to testing the global transcriptome differences of CHO cells at different conditions, the workflow identifies differentially expressed genes and pathways with intuitive visualizations as the outputs. The utility of this automated workflow is demonstrated by comparing the transcriptomic profiles of recombinant protein expressing CHO cells with and without a temperature shift. Statistically significant differential expression at the gene, pathway, and global transcriptome levels are identified and visualized. An automated workflow like the one developed in this study will enable rapid translation of CHO culture microarray data into biologically relevant information for mechanism-driven cell line optimization and bioprocess development. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. A high-throughput, precipitating colorimetric sandwich ELISA microarray for shiga toxins

    Science.gov (United States)

    Shiga toxins 1 and 2 (Stx1 and Stx2) from Shiga toxin-producing E. coli (STEC) bacteria were simultaneously detected with a newly developed, high-throughput antibody microarray platform. The proteinaceous toxins were immobilized and sandwiched between biorecognition elements (monoclonal antibodies)...

  19. Diagnostic Yield of Chromosomal Microarray Analysis in an Autism Primary Care Practice: Which Guidelines to Implement?

    Science.gov (United States)

    McGrew, Susan G.; Peters, Brittany R.; Crittendon, Julie A.; Veenstra-VanderWeele, Jeremy

    2012-01-01

    Genetic testing is recommended for patients with ASD; however specific recommendations vary by specialty. American Academy of Pediatrics and American Academy of Neurology guidelines recommend G-banded karyotype and Fragile X DNA. The American College of Medical Genetics recommends Chromosomal Microarray Analysis (CMA). We determined the yield of…

  20. Functionalization of Poly- (methyl methacrylate) (PMMA) as a substrate for DNA microarrays

    DEFF Research Database (Denmark)

    Fixe, A.F.; Dufva, Hans Martin; Telleman, Pieter

    2004-01-01

    A chemical procedure was developed to functionalize poly(methyl methacrylate) (PMMA) substrates. PMMA is reacted with hexamethylene diamine to yield an aminated surface for immobilizing DNA in microarrays. The density of primary NH2 groups was 0.29 nmol/cm(2). The availability of these primary...

  1. Expression analysis of multiple myeloma CD138 negative progenitor cells using single molecule microarray readout

    Science.gov (United States)

    Jacak, Jaroslaw; Schnidar, Harald; Muresan, Leila; Regl, Gerhard; Frischauf, Annemarie; Aberger, Fritz; Schütz, Gerhard J.; Hesse, Jan

    2013-01-01

    We present a highly sensitive bioanalytical microarray assay that enables the analysis of small genomic sample material. By combining an optimized cDNA purification step with single molecule cDNA detection on the microarray, the platform has improved sensitivity compared to conventional systems, allowing amplification-free determination of expression profiles with as little as 600 ng total RNA. Total RNA from cells was reverse transcribed into fluorescently labeled cDNA and purified employing a precipitation method that minimizes loss of cDNA material. The microarray was scanned on a fluorescence chip-reader with single molecule sensitivity. Using the newly developed platform we were able to analyze the RNA expression profile of a subpopulation of rare multiple myeloma CD138 negative progenitor (MM CD138neg) cells. The high-sensitivity microarray approach led to the identification of a set of 20 genes differentially expressed in MM CD138neg cells. Our work demonstrates the applicability of a straight-forward single-molecule DNA array technology to current topics of molecular and cellular cancer research, which are otherwise difficult to address due to the limited amount of sample material. PMID:23416329

  2. NMD Microarray Analysis for Rapid Genome-Wide Screen of Mutated Genes in Cancer

    Directory of Open Access Journals (Sweden)

    Maija Wolf

    2005-01-01

    Full Text Available Gene mutations play a critical role in cancer development and progression, and their identification offers possibilities for accurate diagnostics and therapeutic targeting. Finding genes undergoing mutations is challenging and slow, even in the post-genomic era. A new approach was recently developed by Noensie and Dietz to prioritize and focus the search, making use of nonsense-mediated mRNA decay (NMD inhibition and microarray analysis (NMD microarrays in the identification of transcripts containing nonsense mutations. We combined NMD microarrays with array-based CGH (comparative genomic hybridization in order to identify inactivation of tumor suppressor genes in cancer. Such a “mutatomics” screening of prostate cancer cell lines led to the identification of inactivating mutations in the EPHB2 gene. Up to 8% of metastatic uncultured prostate cancers also showed mutations of this gene whose loss of function may confer loss of tissue architecture. NMD microarray analysis could turn out to be a powerful research method to identify novel mutated genes in cancer cell lines, providing targets that could then be further investigated for their clinical relevance and therapeutic potential.

  3. MIDClass: microarray data classification by association rules and gene expression intervals.

    Directory of Open Access Journals (Sweden)

    Rosalba Giugno

    Full Text Available We present a new classification method for expression profiling data, called MIDClass (Microarray Interval Discriminant CLASSifier, based on association rules. It classifies expressions profiles exploiting the idea that the transcript expression intervals better discriminate subtypes in the same class. A wide experimental analysis shows the effectiveness of MIDClass compared to the most prominent classification approaches.

  4. MIDClass: microarray data classification by association rules and gene expression intervals.

    Science.gov (United States)

    Giugno, Rosalba; Pulvirenti, Alfredo; Cascione, Luciano; Pigola, Giuseppe; Ferro, Alfredo

    2013-01-01

    We present a new classification method for expression profiling data, called MIDClass (Microarray Interval Discriminant CLASSifier), based on association rules. It classifies expressions profiles exploiting the idea that the transcript expression intervals better discriminate subtypes in the same class. A wide experimental analysis shows the effectiveness of MIDClass compared to the most prominent classification approaches.

  5. Microarray analysis of gender- and parasite-specific gene transcription in Strongyloides ratti

    NARCIS (Netherlands)

    Evans, Helen; Mello, Luciane V.; Fang, Yongxiang; Wit, Ernst; Thompson, Fiona J.; Viney, Mark E.; Paterson, Steve

    2008-01-01

    The molecular mechanisms by which parasitic nematodes reproduce and have adapted to life within a host are unclear. In the present study, microarray analysis was used to explore differential transcription among the different stages and sexes of Strongyloides ratti, a parasitic nematode of brown

  6. Robust multi-scale clustering of large DNA microarray datasets with the consensus algorithm

    DEFF Research Database (Denmark)

    Grotkjær, Thomas; Winther, Ole; Regenberg, Birgitte

    2006-01-01

    Motivation: Hierarchical and relocation clustering (e.g. K-means and self-organizing maps) have been successful tools in the display and analysis of whole genome DNA microarray expression data. However, the results of hierarchical clustering are sensitive to outliers, and most relocation methods...

  7. Ontology-based, Tissue MicroArray oriented, image centered tissue bank

    Directory of Open Access Journals (Sweden)

    Viti Federica

    2008-04-01

    Full Text Available Abstract Background Tissue MicroArray technique is becoming increasingly important in pathology for the validation of experimental data from transcriptomic analysis. This approach produces many images which need to be properly managed, if possible with an infrastructure able to support tissue sharing between institutes. Moreover, the available frameworks oriented to Tissue MicroArray provide good storage for clinical patient, sample treatment and block construction information, but their utility is limited by the lack of data integration with biomolecular information. Results In this work we propose a Tissue MicroArray web oriented system to support researchers in managing bio-samples and, through the use of ontologies, enables tissue sharing aimed at the design of Tissue MicroArray experiments and results evaluation. Indeed, our system provides ontological description both for pre-analysis tissue images and for post-process analysis image results, which is crucial for information exchange. Moreover, working on well-defined terms it is then possible to query web resources for literature articles to integrate both pathology and bioinformatics data. Conclusions Using this system, users associate an ontology-based description to each image uploaded into the database and also integrate results with the ontological description of biosequences identified in every tissue. Moreover, it is possible to integrate the ontological description provided by the user with a full compliant gene ontology definition, enabling statistical studies about correlation between the analyzed pathology and the most commonly related biological processes.

  8. Troubleshooting methods for microarray gene expression analysis in the onset of diabetic kidney disease

    NARCIS (Netherlands)

    Mazagova, Magdalena; Henning, Robert H.; Duin, Marry; van Buiten, Azuwerus; Buikema, Hendrik; Deelman, Leo E.

    2013-01-01

    Introduction: Microarrays have become the standard technique for discovering new genes involved in the development of (kidney) disease. Diabetic nephropathy is a frequent complication of diabetes and is characterized by renal fibrosis. As the pathways leading to fibrosis are initiated early in

  9. Microarray analysis of genes associated with cell surface NIS protein levels in breast cancer.

    Science.gov (United States)

    Beyer, Sasha J; Zhang, Xiaoli; Jimenez, Rafael E; Lee, Mei-Ling T; Richardson, Andrea L; Huang, Kun; Jhiang, Sissy M

    2011-10-11

    Na+/I- symporter (NIS)-mediated iodide uptake allows radioiodine therapy for thyroid cancer. NIS is also expressed in breast tumors, raising potential for radionuclide therapy of breast cancer. However, NIS expression in most breast cancers is low and may not be sufficient for radionuclide therapy. We aimed to identify biomarkers associated with NIS expression such that mechanisms underlying NIS modulation in human breast tumors may be elucidated. Published oligonucleotide microarray data within the National Center for Biotechnology Information Gene Expression Omnibus database were analyzed to identify gene expression tightly correlated with NIS mRNA level among human breast tumors. NIS immunostaining was performed in a tissue microarray composed of 28 human breast tumors which had corresponding oligonucleotide microarray data available for each tumor such that gene expression associated with cell surface NIS protein level could be identified. NIS mRNA levels do not vary among breast tumors or when compared to normal breast tissues when detected by Affymetrix oligonucleotide microarray platforms. Cell surface NIS protein levels are much more variable than their corresponding NIS mRNA levels. Despite a limited number of breast tumors examined, our analysis identified cysteinyl-tRNA synthetase as a biomarker that is highly associated with cell surface NIS protein levels in the ER-positive breast cancer subtype. Further investigation on genes associated with cell surface NIS protein levels within each breast cancer molecular subtype may lead to novel targets for selectively increasing NIS expression/function in a subset of breast cancers patients.

  10. Microarray-based identification of clinically relevant vaginal bacteria in relation to bacterial vaginosis

    NARCIS (Netherlands)

    Dols, Joke A M; Smit, Pieter W; Kort, Remco; Reid, Gregor; Schuren, Frank H J; Tempelman, Hugo; Bontekoe, Tj Romke; Korporaal, Hans; Boon, Mathilde E

    OBJECTIVE: The objective was to examine the use of a tailor-made DNA microarray containing probes representing the vaginal microbiota to examine bacterial vaginosis. STUDY DESIGN: One hundred one women attending a health center for HIV testing in South Africa were enrolled. Stained, liquid-based

  11. MULTI-K: accurate classification of microarray subtypes using ensemble k-means clustering

    Directory of Open Access Journals (Sweden)

    Ashlock Daniel

    2009-08-01

    Full Text Available Abstract Background Uncovering subtypes of disease from microarray samples has important clinical implications such as survival time and sensitivity of individual patients to specific therapies. Unsupervised clustering methods have been used to classify this type of data. However, most existing methods focus on clusters with compact shapes and do not reflect the geometric complexity of the high dimensional microarray clusters, which limits their performance. Results We present a cluster-number-based ensemble clustering algorithm, called MULTI-K, for microarray sample classification, which demonstrates remarkable accuracy. The method amalgamates multiple k-means runs by varying the number of clusters and identifies clusters that manifest the most robust co-memberships of elements. In addition to the original algorithm, we newly devised the entropy-plot to control the separation of singletons or small clusters. MULTI-K, unlike the simple k-means or other widely used methods, was able to capture clusters with complex and high-dimensional structures accurately. MULTI-K outperformed other methods including a recently developed ensemble clustering algorithm in tests with five simulated and eight real gene-expression data sets. Conclusion The geometric complexity of clusters should be taken into account for accurate classification of microarray data, and ensemble clustering applied to the number of clusters tackles the problem very well. The C++ code and the data sets tested are available from the authors.

  12. MULTI-K: accurate classification of microarray subtypes using ensemble k-means clustering.

    Science.gov (United States)

    Kim, Eun-Youn; Kim, Seon-Young; Ashlock, Daniel; Nam, Dougu

    2009-08-22

    Uncovering subtypes of disease from microarray samples has important clinical implications such as survival time and sensitivity of individual patients to specific therapies. Unsupervised clustering methods have been used to classify this type of data. However, most existing methods focus on clusters with compact shapes and do not reflect the geometric complexity of the high dimensional microarray clusters, which limits their performance. We present a cluster-number-based ensemble clustering algorithm, called MULTI-K, for microarray sample classification, which demonstrates remarkable accuracy. The method amalgamates multiple k-means runs by varying the number of clusters and identifies clusters that manifest the most robust co-memberships of elements. In addition to the original algorithm, we newly devised the entropy-plot to control the separation of singletons or small clusters. MULTI-K, unlike the simple k-means or other widely used methods, was able to capture clusters with complex and high-dimensional structures accurately. MULTI-K outperformed other methods including a recently developed ensemble clustering algorithm in tests with five simulated and eight real gene-expression data sets. The geometric complexity of clusters should be taken into account for accurate classification of microarray data, and ensemble clustering applied to the number of clusters tackles the problem very well. The C++ code and the data sets tested are available from the authors.

  13. Quantitative miRNA expression analysis: comparing microarrays with next-generation sequencing

    DEFF Research Database (Denmark)

    Willenbrock, Hanni; Salomon, Jesper; Søkilde, Rolf

    2009-01-01

    Recently, next-generation sequencing has been introduced as a promising, new platform for assessing the copy number of transcripts, while the existing microarray technology is considered less reliable for absolute, quantitative expression measurements. Nonetheless, so far, results from the two te...

  14. Chromosomal microarrays testing in children with developmental disabilities and congenital anomalies

    Directory of Open Access Journals (Sweden)

    Guillermo Lay-Son

    2015-04-01

    Full Text Available OBJECTIVES: Clinical use of microarray-based techniques for the analysis of many developmental disorders has emerged during the last decade. Thus, chromosomal microarray has been positioned as a first-tier test. This study reports the first experience in a Chilean cohort. METHODS: Chilean patients with developmental disabilities and congenital anomalies were studied with a high-density microarray (CytoScan(tm HD Array, Affymetrix, Inc., Santa Clara, CA, USA. Patients had previous cytogenetic studies with either a normal result or a poorly characterized anomaly. RESULTS: This study tested 40 patients selected by two or more criteria, including: major congenital anomalies, facial dysmorphism, developmental delay, and intellectual disability. Copy number variants (CNVs were found in 72.5% of patients, while a pathogenic CNV was found in 25% of patients and a CNV of uncertain clinical significance was found in 2.5% of patients. CONCLUSION: Chromosomal microarray analysis is a useful and powerful tool for diagnosis of developmental diseases, by allowing accurate diagnosis, improving the diagnosis rate, and discovering new etiologies. The higher cost is a limitation for widespread use in this setting.

  15. Microarray Analysis of Late Response to Boron Toxicity in Barley (Hordeum vulgare L.) Leaves

    NARCIS (Netherlands)

    Oz, M.T.; Yilmaz, R.; Eyidogan, F.; Graaff, de L.H.; Yucel, M.; Oktem, H.A.

    2009-01-01

    DNA microarrays, being high-density and high-throughput, allow quantitative analyses of thousands of genes and their expression patterns in parallel. In this study, Barley1 GereChip was used to investigate transcriptome changes associated with boron (B) toxicity in a sensitive barley cultivar

  16. Validation of the performance of a GMO multiplex screening assay based on microarray detection

    NARCIS (Netherlands)

    Leimanis, S.; Hamels, S.; Naze, F.; Mbongolo, G.; Sneyers, M.; Hochegger, R.; Broll, H.; Roth, L.; Dallmann, K.; Micsinai, A.; Dijk, van J.P.; Kok, E.J.

    2008-01-01

    A new screening method for the detection and identification of GMO, based on the use of multiplex PCR followed by microarray, has been developed and is presented. The technology is based on the identification of quite ubiquitous GMO genetic target elements first amplified by PCR, followed by direct

  17. The Utility of Chromosomal Microarray Analysis in Developmental and Behavioral Pediatrics

    Science.gov (United States)

    Beaudet, Arthur L.

    2013-01-01

    Chromosomal microarray analysis (CMA) has emerged as a powerful new tool to identify genomic abnormalities associated with a wide range of developmental disabilities including congenital malformations, cognitive impairment, and behavioral abnormalities. CMA includes array comparative genomic hybridization (CGH) and single nucleotide polymorphism…

  18. Overview of Microarray Analysis of Gene Expression and its Applications to Cervical Cancer Investigation

    Directory of Open Access Journals (Sweden)

    Angel Chao

    2007-12-01

    Full Text Available Cervical cancer is one of the leading female cancers in Taiwan and ranks as the fifth cause of cancer death in the female population. Human papillomavirus has been established as the causative agent for cervical neoplasia and cervical cancer. However, the tumor biology involved in the prognoses of different cell types in early cancers and tumor responses to radiation in advanced cancers remain largely unknown. The introduction of microarray technologies in the 1990s has provided genome-wide strategies for searching tens of thousands of genes simultaneously. In this review, we first summarize the two types of microarrays: oligonucleotides microarray and cDNA microarray. Then, we review the studies of functional genomics in cervical cancer. Gene expression studies that involved cervical cancer cell lines, cervical cells of cancer versus normal ectocervix, cancer tissues of different histology, radioresistant versus radiosensitive patients, and the combinatorial gene expression associated with chromosomal amplifications are discussed. In particular, CEACAM5, TACSTD1, S100P, and MSLN have shown to be upregulated in adenocarcinoma, and increased expression levels of CEACAM5 and TACSTD1 were significantly correlated with poorer patient outcomes. On the other hand, 35 genes, including apoptotic genes (e.g. BIK, TEGT, SSI-3, hypoxia-inducible genes (e.g. HIF1A, CA12, and tumor cell invasion and metastasis genes (e.g. CTSL, CTSB, PLAU, CD44, have been noted to echo the hypothesis that increased tumor hypoxia leads to radiation resistance in cervical cancer during radiation.

  19. Robust Feature Selection from Microarray Data Based on Cooperative Game Theory and Qualitative Mutual Information

    Directory of Open Access Journals (Sweden)

    Atiyeh Mortazavi

    2016-01-01

    Full Text Available High dimensionality of microarray data sets may lead to low efficiency and overfitting. In this paper, a multiphase cooperative game theoretic feature selection approach is proposed for microarray data classification. In the first phase, due to high dimension of microarray data sets, the features are reduced using one of the two filter-based feature selection methods, namely, mutual information and Fisher ratio. In the second phase, Shapley index is used to evaluate the power of each feature. The main innovation of the proposed approach is to employ Qualitative Mutual Information (QMI for this purpose. The idea of Qualitative Mutual Information causes the selected features to have more stability and this stability helps to deal with the problem of data imbalance and scarcity. In the third phase, a forward selection scheme is applied which uses a scoring function to weight each feature. The performance of the proposed method is compared with other popular feature selection algorithms such as Fisher ratio, minimum redundancy maximum relevance, and previous works on cooperative game based feature selection. The average classification accuracy on eleven microarray data sets shows that the proposed method improves both average accuracy and average stability compared to other approaches.

  20. Evaluation of Microarray Preprocessing Algorithms Based on Concordance with RT-PCR in Clinical Samples

    DEFF Research Database (Denmark)

    Hansen, Kasper Lage; Szallasi, Zoltan Imre; Eklund, Aron Charles

    2009-01-01

    performed. METHODOLOGY/PRINCIPAL FINDINGS: We used TaqMan RT-PCR arrays as a reference to evaluate the accuracy of expression values from Affymetrix microarrays in two experimental data sets: one comprising 84 genes in 36 colon biopsies, and the other comprising 75 genes in 29 cancer cell lines. We...

  1. A visual analytics approach for understanding biclustering results from microarray data

    Directory of Open Access Journals (Sweden)

    Quintales Luis

    2008-05-01

    Full Text Available Abstract Background Microarray analysis is an important area of bioinformatics. In the last few years, biclustering has become one of the most popular methods for classifying data from microarrays. Although biclustering can be used in any kind of classification problem, nowadays it is mostly used for microarray data classification. A large number of biclustering algorithms have been developed over the years, however little effort has been devoted to the representation of the results. Results We present an interactive framework that helps to infer differences or similarities between biclustering results, to unravel trends and to highlight robust groupings of genes and conditions. These linked representations of biclusters can complement biological analysis and reduce the time spent by specialists on interpreting the results. Within the framework, besides other standard representations, a visualization technique is presented which is based on a force-directed graph where biclusters are represented as flexible overlapped groups of genes and conditions. This microarray analysis framework (BicOverlapper, is available at http://vis.usal.es/bicoverlapper Conclusion The main visualization technique, tested with different biclustering results on a real dataset, allows researchers to extract interesting features of the biclustering results, especially the highlighting of overlapping zones that usually represent robust groups of genes and/or conditions. The visual analytics methodology will permit biology experts to study biclustering results without inspecting an overwhelming number of biclusters individually.

  2. High-resolution genomic microarrays for X-linked mental retardation.

    NARCIS (Netherlands)

    Lugtenberg, D.; Veltman, J.A.; Bokhoven, J.H.L.M. van

    2007-01-01

    Developments in genomic microarray technology have revolutionized the study of human genomic copy number variation. This has significantly affected many areas in human genetics, including the field of X-linked mental retardation (XLMR). Chromosome X-specific bacterial artificial chromosomes

  3. Easy and fast detection and genotyping of high-risk human papillomavirus by dedicated DNA microarrays.

    Science.gov (United States)

    Albrecht, Valérie; Chevallier, Anne; Magnone, Virginie; Barbry, Pascal; Vandenbos, Fanny; Bongain, André; Lefebvre, Jean-Claude; Giordanengo, Valérie

    2006-11-01

    Persistent cervical high-risk human papillomavirus (HPV) infection is correlated with an increased risk of developing a high-grade cervical intraepithelial lesion. A two-step method was developed for detection and genotyping of high-risk HPV. DNA was firstly amplified by asymmetrical PCR in the presence of Cy3-labelled primers and dUTP. Labelled DNA was then genotyped using DNA microarray hybridization. The current study evaluated the technical efficacy of laboratory-designed HPV DNA microarrays for high-risk HPV genotyping on 57 malignant and non-malignant cervical smears. The approach was evaluated for a broad range of cytological samples: high-grade squamous intraepithelial lesions (HSIL), low-grade squamous intraepithelial lesions (LSIL) and atypical squamous cells of high-grade (ASC-H). High-risk HPV was also detected in six atypical squamous cells of undetermined significance (ASC-US) samples; among them only one cervical specimen was found uninfected, associated with no histological lesion. The HPV oligonucleotide DNA microarray genotyping detected 36 infections with a single high-risk HPV type and 5 multiple infections with several high-risk types. Taken together, these results demonstrate the sensitivity and specificity of the HPV DNA microarray approach. This approach could improve clinical management of patients with cervical cytological abnormalities.

  4. High-throughput mapping of cell-wall polymers within and between plants using novel microarrays

    DEFF Research Database (Denmark)

    Moller, Isabel Eva; Sørensen, Iben; Bernal Giraldo, Adriana Jimena

    2007-01-01

    We describe here a methodology that enables the occurrence of cell-wall glycans to be systematically mapped throughout plants in a semi-quantitative high-throughput fashion. The technique (comprehensive microarray polymer profiling, or CoMPP) integrates the sequential extraction of glycans from...

  5. Enhancing Interdisciplinary Mathematics and Biology Education: A Microarray Data Analysis Course Bridging These Disciplines

    Science.gov (United States)

    Tra, Yolande V.; Evans, Irene M.

    2010-01-01

    "BIO2010" put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on…

  6. DNA microarrays on ultraviolet-modified surfaces for speciation of bacteria.

    Science.gov (United States)

    Liu, Yanyang; He, Jianzhong; Yang, Kun-Lin

    2014-02-15

    In this study, we report an approach to activate inert hydrocarbon monolayers with ultraviolet (UV) light to fabricate DNA microarrays. Unlike traditional microarrays that require reactive functional groups on the surface, our DNA microarray is built on an inert layer of N,N-dimethyl-N-octadecyl(3-aminopropyl)trimethoxysilyl chloride silane (DMOAP). This layer is activated by UV (254 nm) just prior to the immobilization of oligonucleotide probes. Our X-ray photoelectron spectroscopy (XPS) results show that new functional groups such as alcohol (C--O), aldehyde (C=O), and carboxylic acid (O--C=O) form on the surface after the UV exposure. Among them, aldehyde groups are responsible for the immobilization of amine-label oligonucleotides. By using this approach, we further optimize UV exposure time and oligonucleotide concentration and also reduce agent concentration to achieve a high density of immobilized oligonucleotides up to 0.16 pmol/mm². As a proof of concept, we demonstrate that this microarray can be used for differentiation of different Clostridium species such as Clostridium acetobutylicum, Clostridium butylicum, and Clostridium beijerinkii. Copyright © 2013 Elsevier Inc. All rights reserved.

  7. Optimal Design of Genetic Studies of Gene Expression With Two-Color Microarrays in Outbred Crosses

    NARCIS (Netherlands)

    Lam, Alex C.; Fu, Jingyuan; Jansen, Ritsert C.; Haley, Chris S.; de Koning, Dirk-Jan

    2008-01-01

    Combining global gene-expression profiling and genetic analysis of natural allelic variation (genetical genomics) has great potential in dissecting the genetic pathways underlying complex phenotypes. Efficient use of microarrays is paramount in experimental design as the cost. of conducting this

  8. Chromosomal Localization of DNA Amplifications in Neuroblastoma Tumors Using cDNA Microarray Comparative Genomic Hybridization

    Directory of Open Access Journals (Sweden)

    Ben Beheshti

    2003-01-01

    Full Text Available Conventional comparative genomic hybridization (CGH profiling of neuroblastomas has identified many genomic aberrations, although the limited resolution has precluded a precise localization of sequences of interest within amplicons. To map high copy number genomic gains in clinically matched stage IV neuroblastomas, CGH analysis using a 19,200-feature cDNA microarray was used. A dedicated (freely available algorithm was developed for rapid in silico determination of chromosomal localizations of microarray cDNA targets, and for generation of an ideogram-type profile of copy number changes. Using these methodologies, novel gene amplifications undetectable by chromosome CGH were identified, and larger MYCN amplicon sizes (in one tumor up to 6 Mb than those previously reported in neuroblastoma were identified. The genes HPCAL1, LPIN1/KIAA0188, NAG, and NSE1/LOC151354 were found to be coamplified with MYCN. To determine whether stage IV primary tumors could be further subclassified based on their genomic copy number profiles, hierarchical clustering was performed. Cluster analysis of microarray CGH data identified three groups: 1 no amplifications evident, 2 a small MYCN amplicon as the only detectable imbalance, and 3 a large MYCN amplicon with additional gene amplifications. Application of CGH to cDNA microarray targets will help to determine both the variation of amplicon size and help better define amplification-dependent and independent pathways of progression in neuroblastoma.

  9. Gene microarray data analysis using parallel point-symmetry-based clustering.

    Science.gov (United States)

    Sarkar, Anasua; Maulik, Ujjwal

    2015-01-01

    Identification of co-expressed genes is the central goal in microarray gene expression analysis. Point-symmetry-based clustering is an important unsupervised learning technique for recognising symmetrical convex- or non-convex-shaped clusters. To enable fast clustering of large microarray data, we propose a distributed time-efficient scalable approach for point-symmetry-based K-Means algorithm. A natural basis for analysing gene expression data using symmetry-based algorithm is to group together genes with similar symmetrical expression patterns. This new parallel implementation also satisfies linear speedup in timing without sacrificing the quality of clustering solution on large microarray data sets. The parallel point-symmetry-based K-Means algorithm is compared with another new parallel symmetry-based K-Means and existing parallel K-Means over eight artificial and benchmark microarray data sets, to demonstrate its superiority, in both timing and validity. The statistical analysis is also performed to establish the significance of this message-passing-interface based point-symmetry K-Means implementation. We also analysed the biological relevance of clustering solutions.

  10. Use of the cDNA microarray technology in thesafety assessment of GM food plants

    DEFF Research Database (Denmark)

    Pedersen, Jan W.; Knudsen, Ib; Eriksen, Folmer Damsted

    This report focuses on new analytical approaches that might give more insight into possible changes in a genetically modified plant. Primarily the focus is on the new DNA microarray technique but also proteomics and metabolomics are discussed.The report describes the new techniques and evaluates ...

  11. Fluorescent labeling of NASBA amplified tmRNA molecules for microarray applications.

    Science.gov (United States)

    Scheler, Ott; Glynn, Barry; Parkel, Sven; Palta, Priit; Toome, Kadri; Kaplinski, Lauris; Remm, Maido; Maher, Majella; Kurg, Ants

    2009-05-15

    Here we present a novel promising microbial diagnostic method that combines the sensitivity of Nucleic Acid Sequence Based Amplification (NASBA) with the high information content of microarray technology for the detection of bacterial tmRNA molecules. The NASBA protocol was modified to include aminoallyl-UTP (aaUTP) molecules that were incorporated into nascent RNA during the NASBA reaction. Post-amplification labeling with fluorescent dye was carried out subsequently and tmRNA hybridization signal intensities were measured using microarray technology. Significant optimization of the labeled NASBA protocol was required to maintain the required sensitivity of the reactions. Two different aaUTP salts were evaluated and optimum final concentrations were identified for both. The final 2 mM concentration of aaUTP Li-salt in NASBA reaction resulted in highest microarray signals overall, being twice as high as the strongest signals with 1 mM aaUTP Na-salt. We have successfully demonstrated efficient combination of NASBA amplification technology with microarray based hybridization detection. The method is applicative for many different areas of microbial diagnostics including environmental monitoring, bio threat detection, industrial process monitoring and clinical microbiology.

  12. Fluorescent labeling of NASBA amplified tmRNA molecules for microarray applications

    Directory of Open Access Journals (Sweden)

    Kaplinski Lauris

    2009-05-01

    Full Text Available Abstract Background Here we present a novel promising microbial diagnostic method that combines the sensitivity of Nucleic Acid Sequence Based Amplification (NASBA with the high information content of microarray technology for the detection of bacterial tmRNA molecules. The NASBA protocol was modified to include aminoallyl-UTP (aaUTP molecules that were incorporated into nascent RNA during the NASBA reaction. Post-amplification labeling with fluorescent dye was carried out subsequently and tmRNA hybridization signal intensities were measured using microarray technology. Significant optimization of the labeled NASBA protocol was required to maintain the required sensitivity of the reactions. Results Two different aaUTP salts were evaluated and optimum final concentrations were identified for both. The final 2 mM concentration of aaUTP Li-salt in NASBA reaction resulted in highest microarray signals overall, being twice as high as the strongest signals with 1 mM aaUTP Na-salt. Conclusion We have successfully demonstrated efficient combination of NASBA amplification technology with microarray based hybridization detection. The method is applicative for many different areas of microbial diagnostics including environmental monitoring, bio threat detection, industrial process monitoring and clinical microbiology.

  13. A 588-gene microarray analysis of the peripheral blood mononuclear cells of spondyloarthropathy patients

    NARCIS (Netherlands)

    Gu, J.; Märker-Hermann, E.; Baeten, D.; Tsai, W. C.; Gladman, D.; Xiong, M.; Deister, H.; Kuipers, J. G.; Huang, F.; Song, Y. W.; Maksymowych, W.; Kalsi, J.; Bannai, M.; Seta, N.; Rihl, M.; Crofford, L. J.; Veys, E.; de Keyser, F.; Yu, D. T. Y.

    2002-01-01

    OBJECTIVES: To identify genes which are more highly expressed in the peripheral blood mononuclear cells (PBMC) of patients with spondyloarthropathy (SpA), rheumatoid arthritis (RA) and psoriatic arthritis (PsA), in comparison to normal subjects. METHODS: A 588-gene microarray was used as a screening

  14. Direct detection of Staphylococcus aureus mRNA using a flow through microarray

    NARCIS (Netherlands)

    Anthony, R. M.; Schuitema, A. R. J.; Oskam, L.; Klatser, P. R.

    2005-01-01

    The direct detection of mRNAs from bacterial cultures on a DNA array without amplification and labelling would greatly extend the range of applications suitable for microarray analysis. Here we describe the direct detection of 23S rRNA and seven mRNA species from total Staphylococcus aureus RNA

  15. Simultaneous Detection of Multiple Fish Pathogens Using a Naked-Eye Readable DNA Microarray

    Directory of Open Access Journals (Sweden)

    King-Jung Lin

    2012-02-01

    Full Text Available We coupled 16S rDNA PCR and DNA hybridization technology to construct a microarray for simultaneous detection and discrimination of eight fish pathogens (Aeromonas hydrophila, Edwardsiella tarda, Flavobacterium columnare, Lactococcus garvieae, Photobacterium damselae, Pseudomonas anguilliseptica, Streptococcus iniae and Vibrio anguillarum commonly encountered in aquaculture. The array comprised short oligonucleotide probes (30 mer complementary to the polymorphic regions of 16S rRNA genes for the target pathogens. Targets annealed to the microarray probes were reacted with streptavidin-conjugated alkaline phosphatase and nitro blue tetrazolium/5-bromo-4-chloro-3′-indolylphosphate, p-toluidine salt (NBT/BCIP, resulting in blue spots that are easily visualized by the naked eye. Testing was performed against a total of 168 bacterial strains, i.e., 26 representative collection strains, 81 isolates of target fish pathogens, and 61 ecologically or phylogenetically related strains. The results showed that each probe consistently identified its corresponding target strain with 100% specificity. The detection limit of the microarray was estimated to be in the range of 1 pg for genomic DNA and 103 CFU/mL for pure pathogen cultures. These high specificity and sensitivity results demonstrate the feasibility of using DNA microarrays in the diagnostic detection of fish pathogens.

  16. Simultaneous Detection of Escherichia coli, Salmonella enterica, Listeria monocytegenes and Bacillus cereus by Oligonucleotide Microarray

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    Meysam Sarshar

    2015-11-01

    Full Text Available Background: Traditional laboratory methods to detect pathogenic bacteria are time consuming and laborious. Therefore, it is essential to use powerful and reliable molecular methods for quick and simultaneous detection of microbial pathogens. Objectives: The current study aimed to evaluate the capability and efficiency of 23S rDNA sequence for rapid and simultaneous detection of four important food-borne pathogens by an oligonucleotide microarray technique. Materials and Methods: The 23S rDNA sequences of Escherichia coli, Salmonella enterica, Listeria monocytogenes and Bacillus cereus were obtained from GenBank databases and used to design the oligonucleotide probes and primers by Vector NTI software. Oligonucleotide probes were placed on a nylon membrane and hybridization was performed between probes and 23S rDNA digoxigenin-labeled polymerase chain reaction (PCR products. Hybridization signals were visualized by NBT/BCIP color development. Results: Positive hybridization color was produced for Escherichia coli, Salmonella enterica, Listeria monocytogenes and Bacillus cereus. The oligonucleotide microarray detected all bacterial strains in a single reaction in less than five hours. The sensitivity of the performed microarray assay was 103 cfu/mL for each species of pathogen. No cross reaction was found between the tested bacterial species. Conclusions: The obtained results indicated that amplification of 23S rDNA gene followed by oligonucleotide microarray hybridization is a rapid and reliable method to identify and discriminate foodborne pathogens tested under the study.

  17. GENE EXPRESSION IN THE TESTES OF NORMOSPERMIC VERSUS TERATOSPERMIC DOMESTIC CATS USING HUMAN CDNA MICROARRAY ANALYSES

    Science.gov (United States)

    GENE EXPRESSION IN THE TESTES OF NORMOSPERMIC VERSUS TERATOSPERMIC DOMESTIC CATS USING HUMAN cDNA MICROARRAY ANALYSESB.S. Pukazhenthi1, J. C. Rockett2, M. Ouyang3, D.J. Dix2, J.G. Howard1, P. Georgopoulos4, W.J. J. Welsh3 and D. E. Wildt11Department of Reproductiv...

  18. Expression Profiler : next generation-an online platform for analysis of microarray data

    NARCIS (Netherlands)

    Kapushesky, M; Kemmeren, P; Culhane, AC; Durinck, S; Ihmels, J; Korner, C; Kull, M; Torrente, A; Sarkans, U; Vilo, J; Brazma, A

    2004-01-01

    Expression Profiler (EP, http://www.ebi.ac.uk/expressionprofiler) is a web-based platform for microarray gene expression and other functional genomics-related data analysis. The new architecture, Expression Profiler: next generation (EP:NG), modularizes the original design and allows individual

  19. Multi-task feature selection in microarray data by binary integer programming.

    Science.gov (United States)

    Lan, Liang; Vucetic, Slobodan

    2013-12-20

    A major challenge in microarray classification is that the number of features is typically orders of magnitude larger than the number of examples. In this paper, we propose a novel feature filter algorithm to select the feature subset with maximal discriminative power and minimal redundancy by solving a quadratic objective function with binary integer constraints. To improve the computational efficiency, the binary integer constraints are relaxed and a low-rank approximation to the quadratic term is applied. The proposed feature selection algorithm was extended to solve multi-task microarray classification problems. We compared the single-task version of the proposed feature selection algorithm with 9 existing feature selection methods on 4 benchmark microarray data sets. The empirical results show that the proposed method achieved the most accurate predictions overall. We also evaluated the multi-task version of the proposed algorithm on 8 multi-task microarray datasets. The multi-task feature selection algorithm resulted in significantly higher accuracy than when using the single-task feature selection methods.

  20. A novel parametric approach to mine gene regulatory relationship from microarray datasets

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    Zhu Yunping

    2010-12-01

    Full Text Available Abstract Background Microarray has been widely used to measure the gene expression level on the genome scale in the current decade. Many algorithms have been developed to reconstruct gene regulatory networks based on microarray data. Unfortunately, most of these models and algorithms focus on global properties of the expression of genes in regulatory networks. And few of them are able to offer intuitive parameters. We wonder whether some simple but basic characteristics of microarray datasets can be found to identify the potential gene regulatory relationship. Results Based on expression correlation, expression level variation and vectors derived from microarray expression levels, we first introduced several novel parameters to measure the characters of regulating gene pairs. Subsequently, we used the naïve Bayesian network to integrate these features as well as the functional co-annotation between transcription factors and their target genes. Then, based on the character of time-delay from the expression profile, we were able to predict the existence and direction of the regulatory relationship respectively. Conclusions Several novel parameters have been proposed and integrated to identify the regulatory relationship. This new model is proved to be of higher efficacy than that of individual features. It is believed that our parametric approach can serve as a fast approach for regulatory relationship mining.