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Sample records for a-madman annotation-based microarray

  1. SNAD: sequence name annotation-based designer

    Directory of Open Access Journals (Sweden)

    Gorbalenya Alexander E

    2009-08-01

    Full Text Available Abstract Background A growing diversity of biological data is tagged with unique identifiers (UIDs associated with polynucleotides and proteins to ensure efficient computer-mediated data storage, maintenance, and processing. These identifiers, which are not informative for most people, are often substituted by biologically meaningful names in various presentations to facilitate utilization and dissemination of sequence-based knowledge. This substitution is commonly done manually that may be a tedious exercise prone to mistakes and omissions. Results Here we introduce SNAD (Sequence Name Annotation-based Designer that mediates automatic conversion of sequence UIDs (associated with multiple alignment or phylogenetic tree, or supplied as plain text list into biologically meaningful names and acronyms. This conversion is directed by precompiled or user-defined templates that exploit wealth of annotation available in cognate entries of external databases. Using examples, we demonstrate how this tool can be used to generate names for practical purposes, particularly in virology. Conclusion A tool for controllable annotation-based conversion of sequence UIDs into biologically meaningful names and acronyms has been developed and placed into service, fostering links between quality of sequence annotation, and efficiency of communication and knowledge dissemination among researchers.

  2. Chromosome Microarray.

    Science.gov (United States)

    Anderson, Sharon

    2016-01-01

    Over the last half century, knowledge about genetics, genetic testing, and its complexity has flourished. Completion of the Human Genome Project provided a foundation upon which the accuracy of genetics, genomics, and integration of bioinformatics knowledge and testing has grown exponentially. What is lagging, however, are efforts to reach and engage nurses about this rapidly changing field. The purpose of this article is to familiarize nurses with several frequently ordered genetic tests including chromosomes and fluorescence in situ hybridization followed by a comprehensive review of chromosome microarray. It shares the complexity of microarray including how testing is performed and results analyzed. A case report demonstrates how this technology is applied in clinical practice and reveals benefits and limitations of this scientific and bioinformatics genetic technology. Clinical implications for maternal-child nurses across practice levels are discussed. PMID:27276104

  3. The Symbol of Isolated Mood of New Cultural Pioneer---A Discussion on the Application of Symbolic Expression and Its Significance in The Diary of a Madman%新文化先驱者孤绝心境的象征--论《狂人日记》中象征主义表现法的运用及其意义

    Institute of Scientific and Technical Information of China (English)

    张直心; 王平

    2015-01-01

    现代中国小说的开山之作《狂人日记》,与其说是“第一篇现实主义小说”,不如说是象征主义小说的发端。它主要借重象征主义表现法,使“狂人”的感觉能力得以升华,乃至发出“从来如此,便对么”的惊世之问,表征了新文化先驱不无孤绝地反传统的心境。而就小说的创作方法、属性问题的去讹存真,恰可揭示鲁迅审美视野的开阔,以及勉力集合诸种创作方法张力的用心。%As the pioneering work of modern Chinese fiction, The Diary of a Madman is, more or less, regarded to be the origin of symbolic fiction rather than the first realistic one. It is likely to get the feeling of the madman sublimated by means of symbol-ic expression, and thus comes out the world-shocking question “That’s the way it has always been. Does that make it right?”, which shows the isolated mood and anti-tradition attitude of the new cultural pioneer. It is suggested in this paper that a close study on writing techniques and properties of Lu Xun’s works by eliminating the false and retaining the true will inevitably reveal the writer’s wide aesthetic vision and his effort to combine the tension of all kinds of writing techniques.

  4. 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.

  5. Aptamer Microarrays

    Energy Technology Data Exchange (ETDEWEB)

    Angel-Syrett, Heather; Collett, Jim; Ellington, Andrew D.

    2009-01-02

    In vitro selection can yield specific, high-affinity aptamers. We and others have devised methods for the automated selection of aptamers, and have begun to use these reagents for the construction of arrays. Arrayed aptamers have proven to be almost as sensitive as their solution phase counterparts, and when ganged together can provide both specific and general diagnostic signals for proteins and other analytes. We describe here technical details regarding the production and processing of aptamer microarrays, including blocking, washing, drying, and scanning. We will also discuss the challenges involved in developing standardized and reproducible methods for binding and quantitating protein targets. While signals from fluorescent analytes or sandwiches are typically captured, it has proven possible for immobilized aptamers to be uniquely coupled to amplification methods not available to protein reagents, thus allowing for protein-binding signals to be greatly amplified. Into the future, many of the biosensor methods described in this book can potentially be adapted to array formats, thus further expanding the utility of and applications for aptamer arrays.

  6. Microarrays, Integrated Analytical Systems

    Science.gov (United States)

    Combinatorial chemistry is used to find materials that form sensor microarrays. This book discusses the fundamentals, and then proceeds to the many applications of microarrays, from measuring gene expression (DNA microarrays) to protein-protein interactions, peptide chemistry, carbodhydrate chemistry, electrochemical detection, and microfluidics.

  7. DNA Microarray Technique

    Directory of Open Access Journals (Sweden)

    Thakare SP

    2012-11-01

    Full Text Available DNA Microarray is the emerging technique in Biotechnology. The many varieties of DNA microarray or DNA chip devices and systems are described along with their methods for fabrication and their use. It also includes screening and diagnostic applications. The DNA microarray hybridization applications include the important areas of gene expression analysis and genotyping for point mutations, single nucleotide polymorphisms (SNPs, and short tandem repeats (STRs. In addition to the many molecular biological and genomic research uses, this review covers applications of microarray devices and systems for pharmacogenomic research and drug discovery, infectious and genetic disease and cancer diagnostics, and forensic and genetic identification purposes.

  8. Microarray Analysis in Glioblastomas

    Science.gov (United States)

    Bhawe, Kaumudi M.; Aghi, Manish K.

    2016-01-01

    Microarray analysis in glioblastomas is done using either cell lines or patient samples as starting material. A survey of the current literature points to transcript-based microarrays and immunohistochemistry (IHC)-based tissue microarrays as being the preferred methods of choice in cancers of neurological origin. Microarray analysis may be carried out for various purposes including the following: To correlate gene expression signatures of glioblastoma cell lines or tumors with response to chemotherapy (DeLay et al., Clin Cancer Res 18(10):2930–2942, 2012)To correlate gene expression patterns with biological features like proliferation or invasiveness of the glioblastoma cells (Jiang et al., PLoS One 8(6):e66008, 2013)To discover new tumor classificatory systems based on gene expression signature, and to correlate therapeutic response and prognosis with these signatures (Huse et al., Annu Rev Med 64(1):59–70, 2013; Verhaak et al., Cancer Cell 17(1):98–110, 2010) While investigators can sometimes use archived tumor gene expression data available from repositories such as the NCBI Gene Expression Omnibus to answer their questions, new arrays must often be run to adequately answer specific questions. Here, we provide a detailed description of microarray methodologies, how to select the appropriate methodology for a given question, and analytical strategies that can be used. Experimental methodology for protein microarrays is outside the scope of this chapter, but basic sample preparation techniques for transcript-based microarrays are included here. PMID:26113463

  9. Combining Affymetrix microarray results

    Directory of Open Access Journals (Sweden)

    Doerge RW

    2005-03-01

    Full Text Available Abstract Background As the use of microarray technology becomes more prevalent it is not unusual to find several laboratories employing the same microarray technology to identify genes related to the same condition in the same species. Although the experimental specifics are similar, typically a different list of statistically significant genes result from each data analysis. Results We propose a statistically-based meta-analytic approach to microarray analysis for the purpose of systematically combining results from the different laboratories. This approach provides a more precise view of genes that are significantly related to the condition of interest while simultaneously allowing for differences between laboratories. Of particular interest is the widely used Affymetrix oligonucleotide array, the results of which are naturally suited to a meta-analysis. A simulation model based on the Affymetrix platform is developed to examine the adaptive nature of the meta-analytic approach and to illustrate the usefulness of such an approach in combining microarray results across laboratories. The approach is then applied to real data involving a mouse model for multiple sclerosis. Conclusion The quantitative estimates from the meta-analysis model tend to be closer to the "true" degree of differential expression than any single lab. Meta-analytic methods can systematically combine Affymetrix results from different laboratories to gain a clearer understanding of genes' relationships to specific conditions of interest.

  10. Protein microarrays for systems biology

    Institute of Scientific and Technical Information of China (English)

    Lina Yang; Shujuan Guo; Yang Li; Shumin Zhou; Shengce Tao

    2011-01-01

    Systems biology holds the key for understanding biological systems on a system level. It eventually holds the key for the treatment and cure of complex diseases such as cancer,diabetes, obesity, mental disorders, and many others. The '-omics' technologies, such as genomics, transcriptomics,proteomics, and metabonomics, are among the major driving forces of systems biology. Featured as highthroughput, miniaturized, and capable of parallel analysis,protein microarrays have already become an important technology platform for systems biology, In this review, we will focus on the system level or global analysis of biological systems using protein microarrays. Four major types of protein microarrays will be discussed: proteome microarrays, antibody microarrays, reverse-phase protein arrays,and lectin microarrays. We will also discuss the challenges and future directions of protein microarray technologies and their applications for systems biology. We strongly believe that protein microarrays will soon become an indispensable and invaluable tool for systems biology.

  11. Microarray technology and its applications

    CERN Document Server

    Müller, UR

    2006-01-01

    It presents detailed overviews of the different techniques of fabricating microarrays, of the chemistries and preparative steps involved, of the different types of microarrays, and of the instrumentation and optical issues involved.

  12. Navigating public microarray databases.

    Science.gov (United States)

    Penkett, Christopher J; Bähler, Jürg

    2004-01-01

    With the ever-escalating amount of data being produced by genome-wide microarray studies, it is of increasing importance that these data are captured in public databases so that researchers can use this information to complement and enhance their own studies. Many groups have set up databases of expression data, ranging from large repositories, which are designed to comprehensively capture all published data, through to more specialized databases. The public repositories, such as ArrayExpress at the European Bioinformatics Institute contain complete datasets in raw format in addition to processed data, whilst the specialist databases tend to provide downstream analysis of normalized data from more focused studies and data sources. Here we provide a guide to the use of these public microarray resources. PMID:18629145

  13. Compressive Sensing DNA Microarrays

    Directory of Open Access Journals (Sweden)

    Richard G. Baraniuk

    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.

  14. 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. PMID:26614075

  15. 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.

  16. Microarray Scanner for Fluorescence Detection

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    A novel pseudo confocal microarray scanner is introduced, in which one dimension scanning is performed by a galvanometer optical scanner and a telecentric objective, another dimension scanning is performed by a stepping motor.

  17. Recent advances of protein microarrays

    OpenAIRE

    Hultschig, Claus; Kreutzberger, Jürgen; Seitz, Harald; Konthur, Zoltán; Büssow, Konrad; Lehrach, Hans

    2006-01-01

    Technological innovations and novel applications have greatly advanced the field of protein microarrays. Over the past two years, different types of protein microarrays have been used for serum profiling, protein abundance determinations, and identification of proteins that bind DNA or small compounds. However, considerable development is still required to ensure common quality standards and to establish large content repertoires. Here, we summarize applications available to date and discuss ...

  18. The Stanford Tissue Microarray Database.

    Science.gov (United States)

    Marinelli, Robert J; Montgomery, Kelli; Liu, Chih Long; Shah, Nigam H; Prapong, Wijan; Nitzberg, Michael; Zachariah, Zachariah K; Sherlock, Gavin J; Natkunam, Yasodha; West, Robert B; van de Rijn, Matt; Brown, Patrick O; Ball, Catherine A

    2008-01-01

    The Stanford Tissue Microarray Database (TMAD; http://tma.stanford.edu) is a public resource for disseminating annotated tissue images and associated expression data. Stanford University pathologists, researchers and their collaborators worldwide use TMAD for designing, viewing, scoring and analyzing their tissue microarrays. The use of tissue microarrays allows hundreds of human tissue cores to be simultaneously probed by antibodies to detect protein abundance (Immunohistochemistry; IHC), or by labeled nucleic acids (in situ hybridization; ISH) to detect transcript abundance. TMAD archives multi-wavelength fluorescence and bright-field images of tissue microarrays for scoring and analysis. As of July 2007, TMAD contained 205 161 images archiving 349 distinct probes on 1488 tissue microarray slides. Of these, 31 306 images for 68 probes on 125 slides have been released to the public. To date, 12 publications have been based on these raw public data. TMAD incorporates the NCI Thesaurus ontology for searching tissues in the cancer domain. Image processing researchers can extract images and scores for training and testing classification algorithms. The production server uses the Apache HTTP Server, Oracle Database and Perl application code. Source code is available to interested researchers under a no-cost license. PMID:17989087

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

    OpenAIRE

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

    2014-01-01

    Background 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 u...

  20. 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...

  1. 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.

  2. Microarray results: how accurate are they?

    Directory of Open Access Journals (Sweden)

    Mane Shrikant

    2002-08-01

    Full Text Available Abstract Background DNA microarray technology is a powerful technique that was recently developed in order to analyze thousands of genes in a short time. Presently, microarrays, or chips, of the cDNA type and oligonucleotide type are available from several sources. The number of publications in this area is increasing exponentially. Results In this study, microarray data obtained from two different commercially available systems were critically evaluated. Our analysis revealed several inconsistencies in the data obtained from the two different microarrays. Problems encountered included inconsistent sequence fidelity of the spotted microarrays, variability of differential expression, low specificity of cDNA microarray probes, discrepancy in fold-change calculation and lack of probe specificity for different isoforms of a gene. Conclusions In view of these pitfalls, data from microarray analysis need to be interpreted cautiously.

  3. Optimisation algorithms for microarray biclustering.

    Science.gov (United States)

    Perrin, Dimitri; Duhamel, Christophe

    2013-01-01

    In providing simultaneous information on expression profiles for thousands of genes, microarray technologies have, in recent years, been largely used to investigate mechanisms of gene expression. Clustering and classification of such data can, indeed, highlight patterns and provide insight on biological processes. A common approach is to consider genes and samples of microarray datasets as nodes in a bipartite graphs, where edges are weighted e.g. based on the expression levels. In this paper, using a previously-evaluated weighting scheme, we focus on search algorithms and evaluate, in the context of biclustering, several variations of Genetic Algorithms. We also introduce a new heuristic "Propagate", which consists in recursively evaluating neighbour solutions with one more or one less active conditions. The results obtained on three well-known datasets show that, for a given weighting scheme, optimal or near-optimal solutions can be identified. PMID:24109756

  4. How Can Microarrays Unlock Asthma?

    Directory of Open Access Journals (Sweden)

    Alen Faiz

    2012-01-01

    Full Text Available Asthma is a complex disease regulated by the interplay of a large number of underlying mechanisms which contribute to the overall pathology. Despite various breakthroughs identifying genes related to asthma, our understanding of the importance of the genetic background remains limited. Although current therapies for asthma are relatively effective, subpopulations of asthmatics do not respond to these regimens. By unlocking the role of these underlying mechanisms, a source of novel and more effective treatments may be identified. In the new age of high-throughput technologies, gene-expression microarrays provide a quick and effective method of identifying novel genes and pathways, which would be impossible to discover using an individual gene screening approach. In this review we follow the history of expression microarray technologies and describe their contributions to advancing our current knowledge and understanding of asthma pathology.

  5. Microarray analysis in pulmonary hypertension.

    Science.gov (United States)

    Hoffmann, Julia; Wilhelm, Jochen; Olschewski, Andrea; Kwapiszewska, Grazyna

    2016-07-01

    Microarrays are a powerful and effective tool that allows the detection of genome-wide gene expression differences between controls and disease conditions. They have been broadly applied to investigate the pathobiology of diverse forms of pulmonary hypertension, namely group 1, including patients with idiopathic pulmonary arterial hypertension, and group 3, including pulmonary hypertension associated with chronic lung diseases such as chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis. To date, numerous human microarray studies have been conducted to analyse global (lung homogenate samples), compartment-specific (laser capture microdissection), cell type-specific (isolated primary cells) and circulating cell (peripheral blood) expression profiles. Combined, they provide important information on development, progression and the end-stage disease. In the future, system biology approaches, expression of noncoding RNAs that regulate coding RNAs, and direct comparison between animal models and human disease might be of importance. PMID:27076594

  6. Construction of metastatic spinal cancer tissue microarrays

    Institute of Scientific and Technical Information of China (English)

    Yang Xinghai; Chen Huajiang; Xiao Jianru; Yuan Wen; Jia Lianshun

    2009-01-01

    Objective: To explore the construction of metastatic spinal cancer (MSC) tissue microarrays and validate its value in immunohistochemical study of MSC. Methods: Paraffin-embedded specimens from 71 MSC cases and 6 primary tumor cases were selected as donor blocks and prepared into MSC tissue microarrays by tissue array arrangement, the steps of which included location, punching, sampling, sample seeding, and re-diagnosis by hematoxylin-eosin (HE) as well as MMP-9 and MMP-14 immunohistochemical staining. Results: The MSC tissue microarrays thus constructed were intact and crackless, containing 154 complete and well arranged microarray points. None of the sectioned tissue microarrays was lost, and the results of HE staining was consistent with the primary pathologic diagnoses. Immunohistochemical staining was also good without non-specific or marginal effect. Conclusion: The MSC tissue microarrays have a high value in the immunohistochemical study of MSC.

  7. Comprehensive comparison of six microarray technologies

    OpenAIRE

    Yauk, Carole L.; Berndt, M. Lynn; Williams, Andrew; Douglas, George R

    2004-01-01

    Microarray technology is extensively used in biological research. The applied technologies vary greatly between laboratories, and outstanding questions remain regarding the degree of correlation among approaches. Recently, there has been a drive toward ensuring high-quality microarray data by the implementation of MIAME (Minimal Information About a Microarray Experiment) guidelines and an emphasis on ensuring public-availability to all datasets. However, despite its current widespread use and...

  8. MICROARRAYS AND THEIR POTENTIAL IN MEDICINE

    Institute of Scientific and Technical Information of China (English)

    Erick Ling; Jie Xu

    2003-01-01

    Advancement in microarray technology can revolutionize many aspects of medicine. Microarrays have applications in gene expression profiling, genotyping, mutation analysis, gene identification, and pharmacology. This paper provides a brief review on the use of microarrays in studies of cancer, infectious diseases, chromosome disorders, neurological/mental disorders, and drugs, along with a prospect on its great potential in diagnosis, prognosis and the treatment of human diseases.

  9. "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.

  10. Annotation-based genome-wide SNP discovery in the large and complex Aegilops tauschii genome using next-generation sequencing without a reference genome sequence

    Directory of Open Access Journals (Sweden)

    Luo Ming-Cheng

    2011-01-01

    Full Text Available Abstract Background Many plants have large and complex genomes with an abundance of repeated sequences. Many plants are also polyploid. Both of these attributes typify the genome architecture in the tribe Triticeae, whose members include economically important wheat, rye and barley. Large genome sizes, an abundance of repeated sequences, and polyploidy present challenges to genome-wide SNP discovery using next-generation sequencing (NGS of total genomic DNA by making alignment and clustering of short reads generated by the NGS platforms difficult, particularly in the absence of a reference genome sequence. Results An annotation-based, genome-wide SNP discovery pipeline is reported using NGS data for large and complex genomes without a reference genome sequence. Roche 454 shotgun reads with low genome coverage of one genotype are annotated in order to distinguish single-copy sequences and repeat junctions from repetitive sequences and sequences shared by paralogous genes. Multiple genome equivalents of shotgun reads of another genotype generated with SOLiD or Solexa are then mapped to the annotated Roche 454 reads to identify putative SNPs. A pipeline program package, AGSNP, was developed and used for genome-wide SNP discovery in Aegilops tauschii-the diploid source of the wheat D genome, and with a genome size of 4.02 Gb, of which 90% is repetitive sequences. Genomic DNA of Ae. tauschii accession AL8/78 was sequenced with the Roche 454 NGS platform. Genomic DNA and cDNA of Ae. tauschii accession AS75 was sequenced primarily with SOLiD, although some Solexa and Roche 454 genomic sequences were also generated. A total of 195,631 putative SNPs were discovered in gene sequences, 155,580 putative SNPs were discovered in uncharacterized single-copy regions, and another 145,907 putative SNPs were discovered in repeat junctions. These SNPs were dispersed across the entire Ae. tauschii genome. To assess the false positive SNP discovery rate, DNA

  11. Application of microarray technology in pulmonary diseases

    OpenAIRE

    Patlakas George; Tzouvelekis Argyris; Bouros Demosthenes

    2004-01-01

    Abstract Microarrays are a powerful tool that have multiple applications both in clinical and cell biology arenas of common lung diseases. To exemplify how this tool can be useful, in this review, we will provide an overview of the application of microarray technology in research relevant to common lung diseases and present some of the future perspectives.

  12. 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...... statistical weights, to omitting a large number of spots or omitting entire slides. Surprisingly, these very different approaches gave quite similar results when applied to the simulated data, although not all participating groups analysed both real and simulated data. The workshop was very successful...

  13. Carbohydrate Microarrays in Plant Science

    DEFF Research Database (Denmark)

    Fangel, Jonatan Ulrik; Pedersen, H.L.; Vidal-Melgosa, S.;

    2012-01-01

    Almost all plant cells are surrounded by glycan-rich cell walls, which form much of the plant body and collectively are the largest source of biomass on earth. Plants use polysaccharides for support, defense, signaling, cell adhesion, and as energy storage, and many plant glycans are also important...... industrially and nutritionally. Understanding the biological roles of plant glycans and the effective exploitation of their useful properties requires a detailed understanding of their structures, occurrence, and molecular interactions. Microarray technology has revolutionized the massively high...... for plant research and can be used to map glycan populations across large numbers of samples to screen antibodies, carbohydrate binding proteins, and carbohydrate binding modules and to investigate enzyme activities....

  14. DNA Microarrays for Identifying Fishes

    Science.gov (United States)

    Nölte, M.; Weber, H.; Silkenbeumer, N.; Hjörleifsdottir, S.; Hreggvidsson, G. O.; Marteinsson, V.; Kappel, K.; Planes, S.; Tinti, F.; Magoulas, A.; Garcia Vazquez, E.; Turan, C.; Hervet, C.; Campo Falgueras, D.; Antoniou, A.; Landi, M.; Blohm, D.

    2008-01-01

    In many cases marine organisms and especially their diverse developmental stages are difficult to identify by morphological characters. DNA-based identification methods offer an analytically powerful addition or even an alternative. In this study, a DNA microarray has been developed to be able to investigate its potential as a tool for the identification of fish species from European seas based on mitochondrial 16S rDNA sequences. Eleven commercially important fish species were selected for a first prototype. Oligonucleotide probes were designed based on the 16S rDNA sequences obtained from 230 individuals of 27 fish species. In addition, more than 1200 sequences of 380 species served as sequence background against which the specificity of the probes was tested in silico. Single target hybridisations with Cy5-labelled, PCR-amplified 16S rDNA fragments from each of the 11 species on microarrays containing the complete set of probes confirmed their suitability. True-positive, fluorescence signals obtained were at least one order of magnitude stronger than false-positive cross-hybridisations. Single nontarget hybridisations resulted in cross-hybridisation signals at approximately 27% of the cases tested, but all of them were at least one order of magnitude lower than true-positive signals. This study demonstrates that the 16S rDNA gene is suitable for designing oligonucleotide probes, which can be used to differentiate 11 fish species. These data are a solid basis for the second step to create a “Fish Chip” for approximately 50 fish species relevant in marine environmental and fisheries research, as well as control of fisheries products. PMID:18270778

  15. 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.

  16. DNA Microarrays in Herbal Drug Research

    Directory of Open Access Journals (Sweden)

    Preeti Chavan

    2006-01-01

    Full Text Available Natural products are gaining increased applications in drug discovery and development. Being chemically diverse they are able to modulate several targets simultaneously in a complex system. Analysis of gene expression becomes necessary for better understanding of molecular mechanisms. Conventional strategies for expression profiling are optimized for single gene analysis. DNA microarrays serve as suitable high throughput tool for simultaneous analysis of multiple genes. Major practical applicability of DNA microarrays remains in DNA mutation and polymorphism analysis. This review highlights applications of DNA microarrays in pharmacodynamics, pharmacogenomics, toxicogenomics and quality control of herbal drugs and extracts.

  17. 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...

  18. SLIMarray: Lightweight software for microarray facility management

    Directory of Open Access Journals (Sweden)

    Marzolf Bruz

    2006-10-01

    Full Text Available Abstract Background Microarray core facilities are commonplace in biological research organizations, and need systems for accurately tracking various logistical aspects of their operation. Although these different needs could be handled separately, an integrated management system provides benefits in organization, automation and reduction in errors. Results We present SLIMarray (System for Lab Information Management of Microarrays, an open source, modular database web application capable of managing microarray inventories, sample processing and usage charges. The software allows modular configuration and is well suited for further development, providing users the flexibility to adapt it to their needs. SLIMarray Lite, a version of the software that is especially easy to install and run, is also available. Conclusion SLIMarray addresses the previously unmet need for free and open source software for managing the logistics of a microarray core facility.

  19. Polymer microarrays for cell based applications

    OpenAIRE

    Hansen, Anne Klara Brigitte

    2012-01-01

    The development and identification of new biomaterials that can replace specific tissues and organs is desirable. In the presented PhD thesis polymer microarrays were applied for the screening of polyacrylates and polyurethanes and evaluation for material discovery for applications in the life sciences. In the first part of the thesis, the largest polymer microarray ever made with more than 7000 features was fabricated and subsequently used for the screening of polyacrylates...

  20. Text Mining Perspectives in Microarray Data Mining

    OpenAIRE

    Natarajan, Jeyakumar

    2013-01-01

    Current microarray data mining methods such as clustering, classification, and association analysis heavily rely on statistical and machine learning algorithms for analysis of large sets of gene expression data. In recent years, there has been a growing interest in methods that attempt to discover patterns based on multiple but related data sources. Gene expression data and the corresponding literature data are one such example. This paper suggests a new approach to microarray data mining as ...

  1. The Impact of Photobleaching on Microarray Analysis

    Directory of Open Access Journals (Sweden)

    Marcel von der Haar

    2015-09-01

    Full Text Available DNA-Microarrays have become a potent technology for high-throughput analysis of genetic regulation. However, the wide dynamic range of signal intensities of fluorophore-based microarrays exceeds the dynamic range of a single array scan by far, thus limiting the key benefit of microarray technology: parallelization. The implementation of multi-scan techniques represents a promising approach to overcome these limitations. These techniques are, in turn, limited by the fluorophores’ susceptibility to photobleaching when exposed to the scanner’s laser light. In this paper the photobleaching characteristics of cyanine-3 and cyanine-5 as part of solid state DNA microarrays are studied. The effects of initial fluorophore intensity as well as laser scanner dependent variables such as the photomultiplier tube’s voltage on bleaching and imaging are investigated. The resulting data is used to develop a model capable of simulating the expected degree of signal intensity reduction caused by photobleaching for each fluorophore individually, allowing for the removal of photobleaching-induced, systematic bias in multi-scan procedures. Single-scan applications also benefit as they rely on pre-scans to determine the optimal scanner settings. These findings constitute a step towards standardization of microarray experiments and analysis and may help to increase the lab-to-lab comparability of microarray experiment results.

  2. rapmad: Robust analysis of peptide microarray data

    Directory of Open Access Journals (Sweden)

    Rothermel Andrée

    2011-08-01

    Full Text Available Abstract Background Peptide microarrays offer an enormous potential as a screening tool for peptidomics experiments and have recently seen an increased field of application ranging from immunological studies to systems biology. By allowing the parallel analysis of thousands of peptides in a single run they are suitable for high-throughput settings. Since data characteristics of peptide microarrays differ from DNA oligonucleotide microarrays, computational methods need to be tailored to these specifications to allow a robust and automated data analysis. While follow-up experiments can ensure the specificity of results, sensitivity cannot be recovered in later steps. Providing sensitivity is thus a primary goal of data analysis procedures. To this end we created rapmad (Robust Alignment of Peptide MicroArray Data, a novel computational tool implemented in R. Results We evaluated rapmad in antibody reactivity experiments for several thousand peptide spots and compared it to two existing algorithms for the analysis of peptide microarrays. rapmad displays competitive and superior behavior to existing software solutions. Particularly, it shows substantially improved sensitivity for low intensity settings without sacrificing specificity. It thereby contributes to increasing the effectiveness of high throughput screening experiments. Conclusions rapmad allows the robust and sensitive, automated analysis of high-throughput peptide array data. The rapmad R-package as well as the data sets are available from http://www.tron-mz.de/compmed.

  3. DNA Microarrays in Comparative Genomics and Transcriptomics

    DEFF Research Database (Denmark)

    Willenbrock, Hanni

    2007-01-01

    data. For this, the DNA microarray technology has gained enormous popularity due to its ability to measure the presence or the activity of thousands of genes simultaneously. Microarrays for high throughput data analyses are not limited to a few organisms but may be applied to everything from bacteria...... at identifying the exact breakpoints where DNA has been gained or lost. In this thesis, three popular methods are compared and a realistic simulation model is presented for generating artificial data with known breakpoints and known DNA copy number. By using simulated data, we obtain a realistic evaluation...... of various strains of the bacteria, e.g. Escherichia coli, with regard to genes involved in pathogenesis. Finally, this thesis present results demonstrating that the gene expression level is sequence dependent, that is, it depends on both DNA structure and codon usage bias. Here, microarray data was used...

  4. Finding consistent disease subnetworks across microarray datasets

    Directory of Open Access Journals (Sweden)

    Soh Donny

    2011-11-01

    Full Text Available Abstract Background While contemporary methods of microarray analysis are excellent tools for studying individual microarray datasets, they have a tendency to produce different results from different datasets of the same disease. We aim to solve this reproducibility problem by introducing a technique (SNet. SNet provides both quantitative and descriptive analysis of microarray datasets by identifying specific connected portions of pathways that are significant. We term such portions within pathways as “subnetworks”. Results We tested SNet on independent datasets of several diseases, including childhood ALL, DMD and lung cancer. For each of these diseases, we obtained two independent microarray datasets produced by distinct labs on distinct platforms. In each case, our technique consistently produced almost the same list of significant nontrivial subnetworks from two independent sets of microarray data. The gene-level agreement of these significant subnetworks was between 51.18% to 93.01%. In contrast, when the same pairs of microarray datasets were analysed using GSEA, t-test and SAM, this percentage fell between 2.38% to 28.90% for GSEA, 49.60% tp 73.01% for t-test, and 49.96% to 81.25% for SAM. Furthermore, the genes selected using these existing methods did not form subnetworks of substantial size. Thus it is more probable that the subnetworks selected by our technique can provide the researcher with more descriptive information on the portions of the pathway actually affected by the disease. Conclusions These results clearly demonstrate that our technique generates significant subnetworks and genes that are more consistent and reproducible across datasets compared to the other popular methods available (GSEA, t-test and SAM. The large size of subnetworks which we generate indicates that they are generally more biologically significant (less likely to be spurious. In addition, we have chosen two sample subnetworks and validated them with

  5. 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

  6. Design of a covalently bonded glycosphingolipid microarray

    DEFF Research Database (Denmark)

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

    2012-01-01

    , a monoclonal antibody to sulfatide, Sulph 1; and a polyclonal antiserum reactive to asialo-G(M2)). Preliminary evaluation of the method indicated successful immobilization of the GSLs, and selective binding of test probes. The potential utility of this methodology for designing covalent microarrays......, 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...

  7. 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

  8. Prominent feature selection of microarray data

    Institute of Scientific and Technical Information of China (English)

    Yihui Liu

    2009-01-01

    For wavelet transform, a set of orthogonal wavelet basis aims to detect the localized changing features contained in microarray data. In this research, we investigate the performance of the selected wavelet features based on wavelet detail coefficients at the second level and the third level. The genetic algorithm is performed to optimize wavelet detail coefficients to select the best discriminant features. Exper-iments are carried out on four microarray datasets to evaluate the performance of classification. Experimental results prove that wavelet features optimized from detail coefficients efficiently characterize the differences between normal tissues and cancer tissues.

  9. 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.

  10. Microarray data mining with visual programming

    OpenAIRE

    Xu, Qikai; Curk, Tomaž; Shaulsky, Gad; Petrovič, Uroš; Bratko, Ivan; Zupan, Blaž; Demšar, Janez; Leban, Gregor

    2005-01-01

    Visual programming offers an intuitive means of combining known analysis and visualization methods into powerful applications. The system presented here enables users who are not programmers to manage microarray and genomic data flow and to customize their analyses by combining common data analysis tools to fit their needs.

  11. 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.

  12. Diagnostic Oligonucleotide Microarray Fingerprinting of Bacillus Isolates

    OpenAIRE

    Chandler, Darrell P.; Alferov, Oleg; Chernov, Boris; Daly, Don S; Golova, Julia; Perov, Alexander; Protic, Miroslava; Robison, Richard; Schipma, Matthew; White, Amanda; Willse, Alan

    2006-01-01

    A genome-independent microarray and new statistical techniques were used to genotype Bacillus strains and quantitatively compare DNA fingerprints with the known taxonomy of the genus. A synthetic DNA standard was used to understand process level variability and lead to recommended standard operating procedures for microbial forensics and clinical diagnostics.

  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. Role of Permutations in Significance Analysis of Microarray and Clustering of Significant Microarray Gene list

    Directory of Open Access Journals (Sweden)

    Tejashree Damle

    2012-03-01

    Full Text Available Microarray is the gene expression data that represent gene in different biological states. Methods are needed to determine the significance of these changes while accounting for the enormous number of genes. Significance analysis of microarrays (SAM is a statistical technique for determining whether changes in gene expression are statistically significant. During the SAM procedure permutation of microarray data is considered to observe the changes in the overall expression level of data. With increasing number of permutations false discovery rate for gene set varies. In our work we took microarray data of Normal Glucose Tolerance (NGT, and Diabetes Mellitus (DM Type II. In this paper we proposed the result of permutations during execution of SAM algorithm. The hierarchical clustering is applied for observing expression levels of significant data and visualize it with heat map.

  15. A comparative analysis of DNA barcode microarray feature size

    OpenAIRE

    Ammar, Ron; SMITH, ANDREW M.; Heisler, Lawrence E.; Giaever, Guri; Nislow, Corey

    2009-01-01

    Background Microarrays are an invaluable tool in many modern genomic studies. It is generally perceived that decreasing the size of microarray features leads to arrays with higher resolution (due to greater feature density), but this increase in resolution can compromise sensitivity. Results We demonstrate that barcode microarrays with smaller features are equally capable of detecting variation in DNA barcode intensity when compared to larger feature sizes within a specific microarray platfor...

  16. 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

  17. 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

    2010-01-01

    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. PMID

  18. 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.

  19. Background Adjustment for DNA Microarrays Using a Database of Microarray Experiments

    OpenAIRE

    Sui, Yunxia; Zhao, Xiaoyue; Speed, Terence P.; Wu, Zhijin

    2009-01-01

    DNA microarrays have become an indispensable technique in biomedical research. The raw measurements from microarrays undergo a number of preprocessing steps before the data are converted to the genomic level for further analysis. Background adjustment is an important step in preprocessing. Estimating background noise has been challenging because background levels vary a lot from probe to probe, yet there are limited observations on each probe. Most current methods have used the empirical Baye...

  20. 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.

  1. Undetected sex chromosome aneuploidy by chromosomal microarray.

    Science.gov (United States)

    Markus-Bustani, Keren; Yaron, Yuval; Goldstein, Myriam; Orr-Urtreger, Avi; Ben-Shachar, Shay

    2012-11-01

    We report on a case of a female fetus found to be mosaic for Turner syndrome (45,X) and trisomy X (47,XXX). Chromosomal microarray analysis (CMA) failed to detect the aneuploidy because of a normal average dosage of the X chromosome. This case represents an unusual instance in which CMA may not detect chromosomal aberrations. Such a possibility should be taken into consideration in similar cases where CMA is used in a clinical setting.

  2. A Gene Expression Barcode for Microarray Data

    OpenAIRE

    Zilliox, Michael J.; Irizarry, Rafael A.

    2007-01-01

    The ability to measure genome-wide expression holds great promise for characterizing cells and distinguishing diseased from normal tissues. Thus far, microarray technology has only been useful for measuring relative expression between two or more samples, which has handicapped its ability to classify tissue types. This paper presents the first method that can successfully predict tissue type based on data from a single hybridization. A preliminary web-tool is available at http://rafalab.jhsph...

  3. Pineal Function: Impact of Microarray Analysis

    OpenAIRE

    Klein, David C.; Bailey, Michael J; Carter, David A.; Kim, Jong-So; Shi, Qiong; Ho, Anthony; Chik, Constance; Gaildrat, Pascaline; Morin, Fabrice; Ganguly, Surajit; Rath, Martin F.; Møller, Morten; Sugden, David; Rangel, Zoila G.; Peter J Munson

    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-hour schedule. This effort has highlighted surprising similarity to the retina and has provided reason to explore new avenues of study including intracellular signaling, signal transduction, transcriptional cascades, thyroid/retinoic acid hormone signaling, metal biology...

  4. Linking microarray reporters with protein functions

    Directory of Open Access Journals (Sweden)

    Gaj Stan

    2007-09-01

    Full Text Available Abstract Background The analysis of microarray experiments requires accurate and up-to-date functional annotation of the microarray reporters to optimize the interpretation of the biological processes involved. Pathway visualization tools are used to connect gene expression data with existing biological pathways by using specific database identifiers that link reporters with elements in the pathways. Results This paper proposes a novel method that aims to improve microarray reporter annotation by BLASTing the original reporter sequences against a species-specific EMBL subset, that was derived from and crosslinked back to the highly curated UniProt database. The resulting alignments were filtered using high quality alignment criteria and further compared with the outcome of a more traditional approach, where reporter sequences were BLASTed against EnsEMBL followed by locating the corresponding protein (UniProt entry for the high quality hits. Combining the results of both methods resulted in successful annotation of > 58% of all reporter sequences with UniProt IDs on two commercial array platforms, increasing the amount of Incyte reporters that could be coupled to Gene Ontology terms from 32.7% to 58.3% and to a local GenMAPP pathway from 9.6% to 16.7%. For Agilent, 35.3% of the total reporters are now linked towards GO nodes and 7.1% on local pathways. Conclusion Our methods increased the annotation quality of microarray reporter sequences and allowed us to visualize more reporters using pathway visualization tools. Even in cases where the original reporter annotation showed the correct description the new identifiers often allowed improved pathway and Gene Ontology linking. These methods are freely available at http://www.bigcat.unimaas.nl/public/publications/Gaj_Annotation/.

  5. Tissue Microarrays for Analysis of Expression Patterns

    OpenAIRE

    Lindskog Bergström, Cecilia

    2013-01-01

    Proteins are essential building blocks in every living cell, and since the complete human genome was sequenced in 2004, researchers have attempted to map the human proteome, which is the functional representation of the genome. One such initiative is the Human Protein Atlas programme (HPA), which generates monospecific antibodies towards all human proteins and uses these for high-throughput tissue profiling on tissue microarrays (TMAs). The results are publically available at the website www....

  6. Metadata Management and Semantics in Microarray Repositories

    Science.gov (United States)

    Kocabaş, F; Can, T; Baykal, N

    2011-01-01

    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. PMID:24052712

  7. Microarrays for rapid identification of plant viruses.

    Science.gov (United States)

    Boonham, Neil; Tomlinson, Jenny; Mumford, Rick

    2007-01-01

    Many factors affect the development and application of diagnostic techniques. Plant viruses are an inherently diverse group that, unlike cellular pathogens, possess no nucleotide sequence type (e.g., ribosomal RNA sequences) in common. Detection of plant viruses is becoming more challenging as globalization of trade, particularly in ornamentals, and the potential effects of climate change enhance the movement of viruses and their vectors, transforming the diagnostic landscape. Techniques for assessing seed, other propagation materials and field samples for the presence of specific viruses include biological indexing, electron microscopy, antibody-based detection, including enzyme-linked immunosorbent assay (ELISA), polymerase chain reaction (PCR), and microarray detection. Of these, microarray detection provides the greatest capability for parallel yet specific testing, and can be used to detect individual, or combinations of viruses and, using current approaches, to do so with a sensitivity comparable to ELISA. Methods based on PCR provide the greatest sensitivity among the listed techniques but are limited in parallel detection capability even in "multiplexed" applications. Various aspects of microarray technology, including probe development, array fabrication, assay target preparation, hybridization, washing, scanning, and interpretation are presented and discussed, for both current and developing technology.

  8. Chicken sperm transcriptome profiling by microarray analysis.

    Science.gov (United States)

    Singh, R P; Shafeeque, C M; Sharma, S K; Singh, R; Mohan, J; Sastry, K V H; Saxena, V K; Azeez, P A

    2016-03-01

    It has been confirmed that mammalian sperm contain thousands of functional RNAs, and some of them have vital roles in fertilization and early embryonic development. Therefore, we attempted to characterize transcriptome of the sperm of fertile chickens using microarray analysis. Spermatozoal RNA was pooled from 10 fertile males and used for RNA preparation. Prior to performing the microarray, RNA quality was assessed using a bioanalyzer, and gDNA and somatic cell RNA contamination was assessed by CD4 and PTPRC gene amplification. The chicken sperm transcriptome was cross-examined by analysing sperm and testes RNA on a 4 × 44K chicken array, and results were verified by RT-PCR. Microarray analysis identified 21,639 predominantly nuclear-encoded transcripts in chicken sperm. The majority (66.55%) of the sperm transcripts were shared with the testes, while surprisingly, 33.45% transcripts were detected (raw signal intensity greater than 50) only in the sperm and not in the testes. The greatest proportion of up-regulated transcripts were responsible for signal transduction (63.20%) followed by embryonic development (56.76%) and cell structure (56.25%). Of the 20 most abundant transcripts, 18 remain uncharacterized, whereas the least abundant genes were mostly associated with the ribosome. These findings lay a foundation for more detailed investigations on sperm RNAs in chickens to identify sperm-based biomarkers for fertility.

  9. Integrating data from heterogeneous DNA microarray platforms.

    Science.gov (United States)

    Valente, Eduardo; Rocha, Miguel

    2015-01-01

    DNA microarrays are one of the most used technologies for gene expression measurement. However, there are several distinct microarray platforms, from different manufacturers, each with its own measurement protocol, resulting in data that can hardly be compared or directly integrated. Data integration from multiple sources aims to improve the assertiveness of statistical tests, reducing the data dimensionality problem. The integration of heterogeneous DNA microarray platforms comprehends a set of tasks that range from the re-annotation of the features used on gene expression, to data normalization and batch effect elimination. In this work, a complete methodology for gene expression data integration and application is proposed, which comprehends a transcript-based re-annotation process and several methods for batch effect attenuation. The integrated data will be used to select the best feature set and learning algorithm for a brain tumor classification case study. The integration will consider data from heterogeneous Agilent and Affymetrix platforms, collected from public gene expression databases, such as The Cancer Genome Atlas and Gene Expression Omnibus. PMID:26673932

  10. 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

  11. Generalization of DNA microarray dispersion properties: microarray equivalent of t-distribution

    DEFF Research Database (Denmark)

    Novak, Jaroslav P; Kim, Seon-Young; Xu, Jun;

    2006-01-01

    BACKGROUND: DNA microarrays are a powerful technology that can provide a wealth of gene expression data for disease studies, drug development, and a wide scope of other investigations. Because of the large volume and inherent variability of DNA microarray data, many new statistical methods have...... technology give "true" representation of physical processes, involved in measurement of RNA abundance. REVIEWERS: This article was reviewed by Yoav Gilad (nominated by Doron Lancet), Sach Mukherjee (nominated by Sandrine Dudoit) and Amir Niknejad and Shmuel Friedland (nominated by Neil Smalheiser)....

  12. Formation and characterization of DNA microarrays at silicon nitride substrates.

    Science.gov (United States)

    Manning, Mary; Redmond, Gareth

    2005-01-01

    A versatile method for direct, covalent attachment of DNA microarrays at silicon nitride layers, previously deposited by chemical vapor deposition at silicon wafer substrates, is reported. Each microarray fabrication process step, from silicon nitride substrate deposition, surface cleaning, amino-silanation, and attachment of a homobifunctional cross-linking molecule to covalent immobilization of probe oligonucleotides, is defined, characterized, and optimized to yield consistent probe microarray quality, homogeneity, and probe-target hybridization performance. The developed microarray fabrication methodology provides excellent (high signal-to-background ratio) and reproducible responsivity to target oligonucleotide hybridization with a rugged chemical stability that permits exposure of arrays to stringent pre- and posthybridization wash conditions through many sustained cycles of reuse. Overall, the achieved performance features compare very favorably with those of more mature glass based microarrays. It is proposed that this DNA microarray fabrication strategy has the potential to provide a viable route toward the successful realization of future integrated DNA biochips.

  13. Extended -Regular Sequence for Automated Analysis of Microarray Images

    Directory of Open Access Journals (Sweden)

    Jin Hee-Jeong

    2006-01-01

    Full Text Available Microarray study enables us to obtain hundreds of thousands of expressions of genes or genotypes at once, and it is an indispensable technology for genome research. The first step is the analysis of scanned microarray images. This is the most important procedure for obtaining biologically reliable data. Currently most microarray image processing systems require burdensome manual block/spot indexing work. Since the amount of experimental data is increasing very quickly, automated microarray image analysis software becomes important. In this paper, we propose two automated methods for analyzing microarray images. First, we propose the extended -regular sequence to index blocks and spots, which enables a novel automatic gridding procedure. Second, we provide a methodology, hierarchical metagrid alignment, to allow reliable and efficient batch processing for a set of microarray images. Experimental results show that the proposed methods are more reliable and convenient than the commercial tools.

  14. 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...... of labeled cDNA added to each slide reduces dye-bias and slide to slide variation. Efficient mixing of the hybridization solution throughout the hybridization reaction increases signals several fold. The amount of near perfect target-probe hybrids may be reduced by efficient stringency washes...

  15. Biocompatible polymer microarrays for cellular high-content screening

    OpenAIRE

    Pernagallo, Salvatore

    2010-01-01

    The global aim of this thesis was to study the use of microarray technology for the screening and identification of biocompatible polymers, to understand physiological phenomena, and the design of biomaterials, implant surfaces and tissue-engineering scaffolds. This work was based upon the polymer microarray platform developed by the Bradley group. Polymer microarrays were successfully applied to find the best polymer supports for: (i) mouse fibroblast cells and used to eval...

  16. DNA Microarray Assessment of Putative Borrelia burgdorferi Lipoprotein Genes

    OpenAIRE

    Liang, Fang Ting; Nelson, F. Kenneth; Fikrig, Erol

    2002-01-01

    A DNA microarray containing fragments of 137 Borrelia burgdorferi B31 putative lipoprotein genes was used to examine Lyme disease spirochetes. DNA from B. burgdorferi sensu stricto B31, 297, and N40; Borrelia garinii IP90; and Borrelia afzelii P/Gau was fluorescently labeled and hybridized to the microarray, demonstrating the degree to which the individual putative lipoprotein genes were conserved among the genospecies. These data show that a DNA microarray can globally examine the genes enco...

  17. Miniaturised Spotter-Compatible Multicapillary Stamping Tool for Microarray Printing

    CERN Document Server

    Drobyshev, A L; Zasedatelev, A S; Drobyshev, Alexei L; Verkhodanov, Nikolai N; Zasedatelev, Alexander S

    2007-01-01

    Novel microstamping tool for microarray printing is proposed. The tool is capable to spot up to 127 droplets of different solutions in single touch. It is easily compatible with commercially available microarray spotters. The tool is based on multichannel funnel with polypropylene capillaries inserted into its channels. Superior flexibility is achieved by ability to replace any printing capillary of the tool. As a practical implementation, hydrogel-based microarrays were stamped and successfully applied to identify the Mycobacterium tuberculosis drug resistance.

  18. Novel R pipeline for analyzing biolog phenotypic microarray data.

    OpenAIRE

    Minna Vehkala; Mikhail Shubin; Connor, Thomas R; Thomson, Nicholas R.; Jukka Corander

    2015-01-01

    Data produced by Biolog Phenotype MicroArrays are longitudinal measurements of cells' respiration on distinct substrates. We introduce a three-step pipeline to analyze phenotypic microarray data with novel procedures for grouping, normalization and effect identification. Grouping and normalization are standard problems in the analysis of phenotype microarrays defined as categorizing bacterial responses into active and non-active, and removing systematic errors from the experimental data, resp...

  19. A comparative analysis of DNA barcode microarray feature size

    OpenAIRE

    Smith Andrew M; Ammar Ron; Heisler Lawrence E; Giaever Guri; Nislow Corey

    2009-01-01

    Abstract Background Microarrays are an invaluable tool in many modern genomic studies. It is generally perceived that decreasing the size of microarray features leads to arrays with higher resolution (due to greater feature density), but this increase in resolution can compromise sensitivity. Results We demonstrate that barcode microarrays with smaller features are equally capable of detecting variation in DNA barcode intensity when compared to larger feature sizes within a specific microarra...

  20. Innovative DNA microarray design for bacterial flora composition evaluation

    OpenAIRE

    Huyghe, Antoine

    2009-01-01

    During the past decade, the advent of new molecular techniques has led to enormous progress in biology, notably with the development of DNA microarray technology. This technology allows monitoring simultaneously the expression of thousands of genes from a given organism. DNA microarrays have been used in a variety of applications, including the characterization of bacteria in biological samples. In this thesis, two distinct DNA microarray approaches for the characterization of bacterial flora...

  1. 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.

  2. Intensity-based segmentation of microarray images.

    Science.gov (United States)

    Nagarajan, Radhakrishnan

    2003-07-01

    The underlying principle in microarray image analysis is that the spot intensity is a measure of the gene expression. This implicitly assumes the gene expression of a spot to be governed entirely by the distribution of the pixel intensities. Thus, a segmentation technique based on the distribution of the pixel intensities is appropriate for the current problem. In this paper, clustering-based segmentation is described to extract the target intensity of the spots. The approximate boundaries of the spots in the microarray are determined by manual adjustment of rectilinear grids. The distribution of the pixel intensity in a grid containing a spot is assumed to be the superposition of the foreground and the local background. The k-means clustering technique and the partitioning around medoids (PAM) were used to generate a binary partition of the pixel intensity distribution. The median (k-means) and the medoid (PAM) of the cluster members are chosen as the cluster representatives. The effectiveness of the clustering-based segmentation techniques was tested on publicly available arrays generated in a lipid metabolism experiment (Callow et al., 2000). The results are compared against those obtained using the region-growing approach (SPOT) (Yang et al., 2001). The effect of additive white Gaussian noise is also investigated. PMID:12906242

  3. Microarray analysis of the developing cortex.

    Science.gov (United States)

    Semeralul, Mawahib O; Boutros, Paul C; Likhodi, Olga; Okey, Allan B; Van Tol, Hubert H M; Wong, Albert H C

    2006-12-01

    Abnormal development of the prefrontal cortex (PFC) is associated with a number of neuropsychiatric disorders that have an onset in childhood or adolescence. Although the basic laminar structure of the PFC is established in utero, extensive remodeling continues into adolescence. To map the overall pattern of changes in cortical gene transcripts during postnatal development, we made serial measurements of mRNA levels in mouse PFC using oligonucleotide microarrays. We observed changes in mRNA transcripts consistent with known postnatal morphological and biochemical events. Overall, most transcripts that changed significantly showed a progressive decrease in abundance after birth, with the majority of change between postnatal weeks 2 and 4. Genes with cell proliferative, cytoskeletal, extracellular matrix, plasma membrane lipid/transport, protein folding, and regulatory functions had decreases in mRNA levels. Quantitative PCR verified the microarray results for six selected genes: DNA methyltransferase 3A (Dnmt3a), procollagen, type III, alpha 1 (Col3a1), solute carrier family 16 (monocarboxylic acid transporters), member 1 (Slc16a1), MARCKS-like 1 (Marcksl1), nidogen 1 (Nid1) and 3-hydroxybutyrate dehydrogenase (heart, mitochondrial) (Bdh).

  4. Mining microarray datasets aided by knowledge stored in literature

    NARCIS (Netherlands)

    R. Jelier (Rob); G.W. Jenster (Guido); L.C.J. Dorssers (Lambert); E.M. van Mulligen (Erik); B. Mons (Barend); J.A. Kors (Jan)

    2003-01-01

    textabstractDNA microarray technology produces large amounts of data. For data mining of these datasets, background information on genes can be helpful. Unfortunately most information is stored in free text. Here, we present an approach to use this information for DNA microarray da

  5. 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.

  6. 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

  7. Defining best practice for microarray analyses in nutrigenomic studies

    NARCIS (Netherlands)

    Garosi, P.; Filippo, C. de; Erk, M. van; Rocca-Serra, P.; Sansone, S.A.; Elliott, R.

    2005-01-01

    Microarrays represent a powerful tool for studies of diet-gene interactions. Their use is, however, associated with a number of technical challenges and potential pitfalls. The cost of microarrays continues to drop but is still comparatively high. This, coupled with the complex logistical issues ass

  8. 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...

  9. Mathematical design of prokaryotic clone-based microarrays

    NARCIS (Netherlands)

    Pieterse, B.; Quirijns, E.J.; Schuren, F.H.J.; Werf, M.J. van der

    2005-01-01

    Background: Clone-based microarrays, on which each spot represents a random genomic fragment, are a good alternative to open reading frame-based microarrays, especially for microorganisms for which the complete genome sequence is not available. Since the generation of a genomic DNA library is a rand

  10. cDNA microarray screening in food safety

    International Nuclear Information System (INIS)

    The cDNA microarray technology and related bioinformatics tools presents a wide range of novel application opportunities. The technology may be productively applied to address food safety. In this mini-review article, we present an update highlighting the late breaking discoveries that demonstrate the vitality of cDNA microarray technology as a tool to analyze food safety with reference to microbial pathogens and genetically modified foods. In order to bring the microarray technology to mainstream food safety, it is important to develop robust user-friendly tools that may be applied in a field setting. In addition, there needs to be a standardized process for regulatory agencies to interpret and act upon microarray-based data. The cDNA microarray approach is an emergent technology in diagnostics. Its values lie in being able to provide complimentary molecular insight when employed in addition to traditional tests for food safety, as part of a more comprehensive battery of tests

  11. DNA microarray-based mutation discovery and genotyping.

    Science.gov (United States)

    Gresham, David

    2011-01-01

    DNA microarrays provide an efficient means of identifying single-nucleotide polymorphisms (SNPs) in DNA samples and characterizing their frequencies in individual and mixed samples. We have studied the parameters that determine the sensitivity of DNA probes to SNPs and found that the melting temperature (T (m)) of the probe is the primary determinant of probe sensitivity. An isothermal-melting temperature DNA microarray design, in which the T (m) of all probes is tightly distributed, can be implemented by varying the length of DNA probes within a single DNA microarray. I describe guidelines for designing isothermal-melting temperature DNA microarrays and protocols for labeling and hybridizing DNA samples to DNA microarrays for SNP discovery, genotyping, and quantitative determination of allele frequencies in mixed samples.

  12. 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 establish...

  13. 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.

  14. Digital microarray analysis for digital artifact genomics

    Science.gov (United States)

    Jaenisch, Holger; Handley, James; Williams, Deborah

    2013-06-01

    We implement a Spatial Voting (SV) based analogy of microarray analysis for digital gene marker identification in malware code sections. We examine a famous set of malware formally analyzed by Mandiant and code named Advanced Persistent Threat (APT1). APT1 is a Chinese organization formed with specific intent to infiltrate and exploit US resources. Manidant provided a detailed behavior and sting analysis report for the 288 malware samples available. We performed an independent analysis using a new alternative to the traditional dynamic analysis and static analysis we call Spatial Analysis (SA). We perform unsupervised SA on the APT1 originating malware code sections and report our findings. We also show the results of SA performed on some members of the families associated by Manidant. We conclude that SV based SA is a practical fast alternative to dynamics analysis and static analysis.

  15. Differential splicing using whole-transcript microarrays

    Directory of Open Access Journals (Sweden)

    Robinson Mark D

    2009-05-01

    Full Text Available Abstract Background The latest generation of Affymetrix microarrays are designed to interrogate expression over the entire length of every locus, thus giving the opportunity to study alternative splicing genome-wide. The Exon 1.0 ST (sense target platform, with versions for Human, Mouse and Rat, is designed primarily to probe every known or predicted exon. The smaller Gene 1.0 ST array is designed as an expression microarray but still interrogates expression with probes along the full length of each well-characterized transcript. We explore the possibility of using the Gene 1.0 ST platform to identify differential splicing events. Results We propose a strategy to score differential splicing by using the auxiliary information from fitting the statistical model, RMA (robust multichip analysis. RMA partitions the probe-level data into probe effects and expression levels, operating robustly so that if a small number of probes behave differently than the rest, they are downweighted in the fitting step. We argue that adjacent poorly fitting probes for a given sample can be evidence of differential splicing and have designed a statistic to search for this behaviour. Using a public tissue panel dataset, we show many examples of tissue-specific alternative splicing. Furthermore, we show that evidence for putative alternative splicing has a strong correspondence between the Gene 1.0 ST and Exon 1.0 ST platforms. Conclusion We propose a new approach, FIRMAGene, to search for differentially spliced genes using the Gene 1.0 ST platform. Such an analysis complements the search for differential expression. We validate the method by illustrating several known examples and we note some of the challenges in interpreting the probe-level data. Software implementing our methods is freely available as an R package.

  16. 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.

  17. Microintaglio Printing for Soft Lithography-Based in Situ Microarrays

    Directory of Open Access Journals (Sweden)

    Manish Biyani

    2015-07-01

    Full Text Available Advances in lithographic approaches to fabricating bio-microarrays have been extensively explored over the last two decades. However, the need for pattern flexibility, a high density, a high resolution, affordability and on-demand fabrication is promoting the development of unconventional routes for microarray fabrication. This review highlights the development and uses of a new molecular lithography approach, called “microintaglio printing technology”, for large-scale bio-microarray fabrication using a microreactor array (µRA-based chip consisting of uniformly-arranged, femtoliter-size µRA molds. In this method, a single-molecule-amplified DNA microarray pattern is self-assembled onto a µRA mold and subsequently converted into a messenger RNA or protein microarray pattern by simultaneously producing and transferring (immobilizing a messenger RNA or a protein from a µRA mold to a glass surface. Microintaglio printing allows the self-assembly and patterning of in situ-synthesized biomolecules into high-density (kilo-giga-density, ordered arrays on a chip surface with µm-order precision. This holistic aim, which is difficult to achieve using conventional printing and microarray approaches, is expected to revolutionize and reshape proteomics. This review is not written comprehensively, but rather substantively, highlighting the versatility of microintaglio printing for developing a prerequisite platform for microarray technology for the postgenomic era.

  18. A perspective on microarrays: current applications, pitfalls, and potential uses

    Directory of Open Access Journals (Sweden)

    Betenbaugh Michael

    2007-01-01

    Full Text Available Abstract With advances in robotics, computational capabilities, and the fabrication of high quality glass slides coinciding with increased genomic information being available on public databases, microarray technology is increasingly being used in laboratories around the world. In fact, fields as varied as: toxicology, evolutionary biology, drug development and production, disease characterization, diagnostics development, cellular physiology and stress responses, and forensics have benefiting from its use. However, for many researchers not familiar with microarrays, current articles and reviews often address neither the fundamental principles behind the technology nor the proper designing of experiments. Although, microarray technology is relatively simple, conceptually, its practice does require careful planning and detailed understanding of the limitations inherently present. Without these considerations, it can be exceedingly difficult to ascertain valuable information from microarray data. Therefore, this text aims to outline key features in microarray technology, paying particular attention to current applications as outlined in recent publications, experimental design, statistical methods, and potential uses. Furthermore, this review is not meant to be comprehensive, but rather substantive; highlighting important concepts and detailing steps necessary to conduct and interpret microarray experiments. Collectively, the information included in this text will highlight the versatility of microarray technology and provide a glimpse of what the future may hold.

  19. Algorithm of automatic image annotation based on MPEG-7 and MM mixture model%基于MPEG-7和MM混合模型的图像自动标注算法

    Institute of Scientific and Technical Information of China (English)

    罗晓燕; 欧阳宁; 莫建文; 李雁

    2012-01-01

    To compensate for the "semantic gap" between low-level visual features of image and high-level semantics and improve the performance of automatic image annotation, a algorithm of image annotation based on Multimedia Description Interface (MPEG-7) is proposed. Low-level visual features of images are extracted according to the color and texture descriptors which are recommended by the MPEG-7 standard. Mapping is setted up from low-level features to high-level semantics space by MM mixture model. Image is automaticly annotated with multi-label based on the overall low-level image features. The proposed algorithm is demonstrated to be feasible and effective on the corel image datesets.%为了弥补图像低层视觉特征和高层语义之间的“语义鸿沟”,改善图像自动标注的性能,提出了基于多媒体描述接口(MPEG-7)和MM (Mixture Model)混合模型的图像标注算法.该算法采用MPEG-7标准推荐的颜色和纹理描述子提取图像的低层视觉特征,通过MM混合模型建立低层特征到高层语义空间的映射,实现了基于图像整体低层特征的多标签图像自动标注.通过在corel图像数据集上的一系列实验测试验证了该方法的可行性和有效性.

  20. AFM 4.0: a toolbox for DNA microarray analysis

    OpenAIRE

    Breitkreutz, Bobby-Joe; Jorgensen, Paul; Breitkreutz, Ashton; Tyers, Mike

    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 ...

  1. 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....

  2. Imaging combined autoimmune and infectious disease microarrays

    Science.gov (United States)

    Ewart, Tom; Raha, Sandeep; Kus, Dorothy; Tarnopolsky, Mark

    2006-09-01

    Bacterial and viral pathogens are implicated in many severe autoimmune diseases, acting through such mechanisms as molecular mimicry, and superantigen activation of T-cells. For example, Helicobacter pylori, well known cause of stomach ulcers and cancers, is also identified in ischaemic heart disease (mimicry of heat shock protein 65), autoimmune pancreatitis, systemic sclerosis, autoimmune thyroiditis (HLA DRB1*0301 allele susceptibility), and Crohn's disease. Successful antibiotic eradication of H.pylori often accompanies their remission. Yet current diagnostic devices, and test-limiting cost containment, impede recognition of the linkage, delaying both diagnosis and therapeutic intervention until the chronic debilitating stage. We designed a 15 minute low cost 39 antigen microarray assay, combining autoimmune, viral and bacterial antigens1. This enables point-of-care serodiagnosis and cost-effective narrowly targeted concurrent antibiotic and monoclonal anti-T-cell and anti-cytokine immunotherapy. Arrays of 26 pathogen and 13 autoimmune antigens with IgG and IgM dilution series were printed in triplicate on epoxysilane covalent binding slides with Teflon well masks. Sera diluted 1:20 were incubated 10 minutes, washed off, anti-IgG-Cy3 (green) and anti-IgM-Dy647 (red) were incubated for 5 minutes, washed off and the slide was read in an ArrayWoRx(e) scanning CCD imager (Applied Precision, Issaquah, WA). As a preliminary model for the combined infectious disease-autoimmune diagnostic microarray we surveyed 98 unidentified, outdated sera that were discarded after Hepatitis B antibody testing. In these, significant IgG or IgM autoantibody levels were found: dsDNA 5, ssDNA 11, Ro 2, RNP 7, SSB 4, gliadin 2, thyroglobulin 13 cases. Since control sera showed no autoantibodies, the high frequency of anti-DNA and anti-thyroglobulin antibodies found in infected sera lend increased support for linkage of infection to subsequent autoimmune disease. Expansion of the antigen

  3. SAMMD: Staphylococcus aureus Microarray Meta-Database

    Directory of Open Access Journals (Sweden)

    Elasri Mohamed O

    2007-10-01

    Full Text Available Abstract Background Staphylococcus aureus is an important human pathogen, causing a wide variety of diseases ranging from superficial skin infections to severe life threatening infections. S. aureus is one of the leading causes of nosocomial infections. Its ability to resist multiple antibiotics poses a growing public health problem. In order to understand the mechanism of pathogenesis of S. aureus, several global expression profiles have been developed. These transcriptional profiles included regulatory mutants of S. aureus and growth of wild type under different growth conditions. The abundance of these profiles has generated a large amount of data without a uniform annotation system to comprehensively examine them. We report the development of the Staphylococcus aureus Microarray meta-database (SAMMD which includes data from all the published transcriptional profiles. SAMMD is a web-accessible database that helps users to perform a variety of analysis against and within the existing transcriptional profiles. Description SAMMD is a relational database that uses MySQL as the back end and PHP/JavaScript/DHTML as the front end. The database is normalized and consists of five tables, which holds information about gene annotations, regulated gene lists, experimental details, references, and other details. SAMMD data is collected from the peer-reviewed published articles. Data extraction and conversion was done using perl scripts while data entry was done through phpMyAdmin tool. The database is accessible via a web interface that contains several features such as a simple search by ORF ID, gene name, gene product name, advanced search using gene lists, comparing among datasets, browsing, downloading, statistics, and help. The database is licensed under General Public License (GPL. Conclusion SAMMD is hosted and available at http://www.bioinformatics.org/sammd/. Currently there are over 9500 entries for regulated genes, from 67 microarray

  4. Ontology-Based Analysis of Microarray Data.

    Science.gov (United States)

    Giuseppe, Agapito; Milano, Marianna

    2016-01-01

    The importance of semantic-based methods and algorithms for the analysis and management of biological data is growing for two main reasons. From a biological side, knowledge contained in ontologies is more and more accurate and complete, from a computational side, recent algorithms are using in a valuable way such knowledge. Here we focus on semantic-based management and analysis of protein interaction networks referring to all the approaches of analysis of protein-protein interaction data that uses knowledge encoded into biological ontologies. Semantic approaches for studying high-throughput data have been largely used in the past to mine genomic and expression data. Recently, the emergence of network approaches for investigating molecular machineries has stimulated in a parallel way the introduction of semantic-based techniques for analysis and management of network data. The application of these computational approaches to the study of microarray data can broad the application scenario of them and simultaneously can help the understanding of disease development and progress.

  5. 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.

  6. Robust Model Selection for Classification of Microarrays

    Directory of Open Access Journals (Sweden)

    Ikumi Suzuki

    2009-01-01

    Full Text Available Recently, microarray-based cancer diagnosis systems have been increasingly investigated. However, cost reduction and reliability assurance of such diagnosis systems are still remaining problems in real clinical scenes. To reduce the cost, we need a supervised classifier involving the smallest number of genes, as long as the classifier is sufficiently reliable. To achieve a reliable classifier, we should assess candidate classifiers and select the best one. In the selection process of the best classifier, however, the assessment criterion must involve large variance because of limited number of samples and non-negligible observation noise. Therefore, even if a classifier with a very small number of genes exhibited the smallest leave-one-out cross-validation (LOO error rate, it would not necessarily be reliable because classifiers based on a small number of genes tend to show large variance. We propose a robust model selection criterion, the min-max criterion, based on a resampling bootstrap simulation to assess the variance of estimation of classification error rates. We applied our assessment framework to four published real gene expression datasets and one synthetic dataset. We found that a state- of-the-art procedure, weighted voting classifiers with LOO criterion, had a non-negligible risk of selecting extremely poor classifiers and, on the other hand, that the new min-max criterion could eliminate that risk. These finding suggests that our criterion presents a safer procedure to design a practical cancer diagnosis system.

  7. Design, construction, characterization, and application of a hyperspectral microarray scanner.

    Science.gov (United States)

    Sinclair, Michael B; Timlin, Jerilyn A; Haaland, David M; Werner-Washburne, Margaret

    2004-04-01

    We describe the design, construction, and operation of a hyperspectral microarray scanner for functional genomic research. The hyperspectral instrument operates with spatial resolutions ranging from 3 to 30 microm and records the emission spectrum between 490 and 900 nm with a spectral resolution of 3 nm for each pixel of the microarray. This spectral information, when coupled with multivariate data analysis techniques, allows for identification and elimination of unwanted artifacts and greatly improves the accuracy of microarray experiments. Microarray results presented in this study clearly demonstrate the separation of fluorescent label emission from the spectrally overlapping emission due to the underlying glass substrate. We also demonstrate separation of the emission due to green fluorescent protein expressed by yeast cells from the spectrally overlapping autofluorescence of the yeast cells and the growth media.

  8. Microarray of DNA probes on carboxylate functional beads surface

    Institute of Scientific and Technical Information of China (English)

    黄承志; 李原芳; 黄新华; 范美坤

    2000-01-01

    The microarray of DNA probes with 5’ -NH2 and 5’ -Tex/3’ -NH2 modified terminus on 10 um carboxylate functional beads surface in the presence of 1-ethyl-3-(3-dimethylaminopropyl)-carbodiimide (EDC) is characterized in the preseni paper. it was found that the microarray capacity of DNA probes on the beads surface depends on the pH of the aqueous solution, the concentra-tion of DNA probe and the total surface area of the beads. On optimal conditions, the minimum distance of 20 mer single-stranded DNA probe microarrayed on beads surface is about 14 nm, while that of 20 mer double-stranded DNA probes is about 27 nm. If the probe length increases from 20 mer to 35 mer, its microarray density decreases correspondingly. Mechanism study shows that the binding mode of DNA probes on the beads surface is nearly parallel to the beads surface.

  9. Cell-Based Microarrays for In Vitro Toxicology

    Science.gov (United States)

    Wegener, Joachim

    2015-07-01

    DNA/RNA and protein microarrays have proven their outstanding bioanalytical performance throughout the past decades, given the unprecedented level of parallelization by which molecular recognition assays can be performed and analyzed. Cell microarrays (CMAs) make use of similar construction principles. They are applied to profile a given cell population with respect to the expression of specific molecular markers and also to measure functional cell responses to drugs and chemicals. This review focuses on the use of cell-based microarrays for assessing the cytotoxicity of drugs, toxins, or chemicals in general. It also summarizes CMA construction principles with respect to the cell types that are used for such microarrays, the readout parameters to assess toxicity, and the various formats that have been established and applied. The review ends with a critical comparison of CMAs and well-established microtiter plate (MTP) approaches.

  10. A measurement error model for microarray data analysis

    Institute of Scientific and Technical Information of China (English)

    ZHOU Yiming; CHENG Jing

    2005-01-01

    Microarray technology has been widely used to analyze the gene expression levels by detecting fluorescence intensity in a high throughput fashion. However, since the measurement error produced from various sources in microarray experiments is heterogeneous and too large to be ignored, we propose here a measurement error model for microarray data processing, by which the standard deviation of the measurement error is demonstrated to be linearly increased with fluorescence intensity. A robust algorithm, which estimates the parameters of the measurement error model from a single microarray without replicated spots, is provided. The model and algorithm for estimating of the parameters from a given data set are tested on both the real data set and the simulated data set, and the result has been proven satisfactory. And, combining the measurement error model with traditional Z-test method, a full statistical model has been developed. It can significantly improve the statistical inference for identifying differentially expressed genes.

  11. Feature extraction and signal processing for nylon DNA microarrays

    OpenAIRE

    Bertucci F; Loï L; Bourgeois A.; Loriod B; Rougemont J; Lopez F; Hingamp P; Houlgatte R; Granjeaud S

    2004-01-01

    Abstract Background High-density DNA microarrays require automatic feature extraction methodologies and softwares. These can be a potential source of non-reproducibility of gene expression measurements. Variation in feature location or in signal integration methodology may be a significant contribution to the observed variance in gene expression levels. Results We explore sources of variability in feature extraction from DNA microarrays on Nylon membrane with radioactive detection. We introdu...

  12. Emerging Use of Gene Expression Microarrays in Plant Physiology

    OpenAIRE

    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 e...

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

    OpenAIRE

    Tewfik Ahmed H; Tchagang Alain B

    2006-01-01

    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, w...

  14. Biclustering of microarray data with MOSPO based on crowding distance

    OpenAIRE

    Liu, Junwan; Li, Zhoujun; Hu, Xiaohua; Chen, Yiming

    2009-01-01

    Background High-throughput microarray technologies have generated and accumulated massive amounts of gene expression datasets that contain expression levels of thousands of genes under hundreds of different experimental conditions. The microarray datasets are usually presented in 2D matrices, where rows represent genes and columns represent experimental conditions. The analysis of such datasets can discover local structures composed by sets of genes that show coherent expression patterns unde...

  15. Microarrays meet the Voltaire challenge: Drug discovery on a chip?

    Science.gov (United States)

    Jackson, David B; Stein, Martin A; Merino, Alejandro; Eils, Roland

    2006-01-01

    The co-emergence of microarray technologies with systems oriented approaches to discovery is testament to the technological and conceptual advancements of recent years. By providing a platform for massively parallelized reductionism, microarrays are enabling us to examine the functional features of diverse classes of bio-system components in a contextually meaningful manner. Yet, to provide economic impact, future development of these technologies demands intimate alignment with the goal of producing safer and more efficacious drugs.: PMID:24980402

  16. Cluster stability scores for microarray data in cancer studies

    OpenAIRE

    Ghosh Debashis; Smolkin Mark

    2003-01-01

    Abstract Background A potential benefit of profiling of tissue samples using microarrays is the generation of molecular fingerprints that will define subtypes of disease. Hierarchical clustering has been the primary analytical tool used to define disease subtypes from microarray experiments in cancer settings. Assessing cluster reliability poses a major complication in analyzing output from clustering procedures. While most work has focused on estimating the number of clusters in a dataset, t...

  17. A comparative analysis of DNA barcode microarray feature size

    Directory of Open Access Journals (Sweden)

    Smith Andrew M

    2009-10-01

    Full Text Available Abstract Background Microarrays are an invaluable tool in many modern genomic studies. It is generally perceived that decreasing the size of microarray features leads to arrays with higher resolution (due to greater feature density, but this increase in resolution can compromise sensitivity. Results We demonstrate that barcode microarrays with smaller features are equally capable of detecting variation in DNA barcode intensity when compared to larger feature sizes within a specific microarray platform. The barcodes used in this study are the well-characterized set derived from the Yeast KnockOut (YKO collection used for screens of pooled yeast (Saccharomyces cerevisiae deletion mutants. We treated these pools with the glycosylation inhibitor tunicamycin as a test compound. Three generations of barcode microarrays at 30, 8 and 5 μm features sizes independently identified the primary target of tunicamycin to be ALG7. Conclusion We show that the data obtained with 5 μm feature size is of comparable quality to the 30 μm size and propose that further shrinking of features could yield barcode microarrays with equal or greater resolving power and, more importantly, higher density.

  18. Assessing Bacterial Interactions Using Carbohydrate-Based Microarrays

    Directory of Open Access Journals (Sweden)

    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.

  19. AN INTELLIGENT SEGMENTATION ALGORITHM FOR MICROARRAY IMAGE PROCESSING

    Directory of Open Access Journals (Sweden)

    P.Rajkumar

    2013-06-01

    Full Text Available Microarray technology consists of an array of thousands of microscopic spots of DNA oligonucleotides attached to a solid surface. It is a very powerful technique for analyzing gene expressions as well as to explore the underlying genetic causes of many human diseases. There are numerous applications of this technology, including environmental health research, drug design and discovery, clinical diagnosis and treatment and in cancer detection. The spots, which represent genes in microarray experiment contains the quantitative information that needs to be extracted accurately. For this process, preprocessing of microarray plays an essential role and it is also influential in future steps of the analysis. The three microarray preprocessing steps include gridding, segmentation and quantification. The first step is gridding, refers to the identification of the centre coordinates of each spot. The second step is segmentation, refers to the process of separating foreground and background fluorescence intensities. Segmentation is very important step as it directly affects the accuracy of gene expression analysis in the data mining process that follows. Accurate segmentation is one of the vital steps in microarray image processing. A novel method for segmentation of microarray image is proposed which accurately segment the spots from background when compared with adaptive threshold, combined global and local thresholdand fuzzy c-means clustering methods. Experimental results show that our proposed method provides better segmentation and improved intensity values than the above existing methods.

  20. Inferring gene regulatory networks from asynchronous microarray data with AIRnet

    Directory of Open Access Journals (Sweden)

    Lai Chun Wan J

    2010-11-01

    Full Text Available Abstract Background Modern approaches to treating genetic disorders, cancers and even epidemics rely on a detailed understanding of the underlying gene signaling network. Previous work has used time series microarray data to infer gene signaling networks given a large number of accurate time series samples. Microarray data available for many biological experiments is limited to a small number of arrays with little or no time series guarantees. When several samples are averaged to examine differences in mean value between a diseased and normal state, information from individual samples that could indicate a gene relationship can be lost. Results Asynchronous Inference of Regulatory Networks (AIRnet provides gene signaling network inference using more practical assumptions about the microarray data. By learning correlation patterns for the changes in microarray values from all pairs of samples, accurate network reconstructions can be performed with data that is normally available in microarray experiments. Conclusions By focussing on the changes between microarray samples, instead of absolute values, increased information can be gleaned from expression data.

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

    Directory of Open Access Journals (Sweden)

    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.

  2. Granulometric Analysis of Spots in DNA Microarray Images

    Institute of Scientific and Technical Information of China (English)

    Behara Latha; Balasubramanian Venkatesh

    2004-01-01

    As the topological properties of each spot in DNA microarray images may vary from one another, we employed granulometries to understand the shape-size con tent contributed due to a significant intensity value within a spot. Analysis was performed on the microarray image that consisted of 240 spots by using concepts from mathematical morphology. In order to find out indices for each spot and to further classify them, we adopted morphological multiscale openings, which provided microarrays at multiple scales. Successive opened microarrays were subtracted to identify the protrusions that were smaller than the size of structuring element. Spot-wise details, in terms of probability of these observed protrusions,were computed by placing a regularly spaced grid on microarray such that each spot was centered in each grid. Based on the probability of size distribution functions of these protrusions isolated at each level, we estimated the mean size and texture index for each spot. With these characteristics, we classified the spots in a microarray image into bright and dull categories through pattern spectrum and shape-size complexity measures. These segregated spots can be compared with those of hybridization levels.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  4. Photopatterning of Hydrogel Microarrays in Closed Microchips.

    Science.gov (United States)

    Gumuscu, Burcu; Bomer, Johan G; van den Berg, Albert; Eijkel, Jan C T

    2015-12-14

    To date, optical lithography has been extensively used for in situ patterning of hydrogel structures in a scale range from hundreds of microns to a few millimeters. The two main limitations which prevent smaller feature sizes of hydrogel structures are (1) the upper glass layer of a microchip maintains a large spacing (typically 525 μm) between the photomask and hydrogel precursor, leading to diffraction of UV light at the edges of mask patterns, (2) diffusion of free radicals and monomers results in irregular polymerization near the illumination interface. In this work, we present a simple approach to enable the use of optical lithography to fabricate hydrogel arrays with a minimum feature size of 4 μm inside closed microchips. To achieve this, we combined two different techniques. First, the upper glass layer of the microchip was thinned by mechanical polishing to reduce the spacing between the photomask and hydrogel precursor, and thereby the diffraction of UV light at the edges of mask patterns. The polishing process reduces the upper layer thickness from ∼525 to ∼100 μm, and the mean surface roughness from 20 to 3 nm. Second, we developed an intermittent illumination technique consisting of short illumination periods followed by relatively longer dark periods, which decrease the diffusion of monomers. Combination of these two methods allows for fabrication of 0.4 × 10(6) sub-10 μm sized hydrogel patterns over large areas (cm(2)) with high reproducibility (∼98.5% patterning success). The patterning method is tested with two different types of photopolymerizing hydrogels: polyacrylamide and polyethylene glycol diacrylate. This method enables in situ fabrication of well-defined hydrogel patterns and presents a simple approach to fabricate 3-D hydrogel matrices for biomolecule separation, biosensing, tissue engineering, and immobilized protein microarray applications.

  5. Pipeline for macro- and microarray analyses

    Directory of Open Access Journals (Sweden)

    R. Vicentini

    2007-05-01

    Full Text Available The pipeline for macro- and microarray analyses (PMmA is a set of scripts with a web interface developed to analyze DNA array data generated by array image quantification software. PMmA is designed for use with single- or double-color array data and to work as a pipeline in five classes (data format, normalization, data analysis, clustering, and array maps. It can also be used as a plugin in the BioArray Software Environment, an open-source database for array analysis, or used in a local version of the web service. All scripts in PMmA were developed in the PERL programming language and statistical analysis functions were implemented in the R statistical language. Consequently, our package is a platform-independent software. Our algorithms can correctly select almost 90% of the differentially expressed genes, showing a superior performance compared to other methods of analysis. The pipeline software has been applied to 1536 expressed sequence tags macroarray public data of sugarcane exposed to cold for 3 to 48 h. PMmA identified thirty cold-responsive genes previously unidentified in this public dataset. Fourteen genes were up-regulated, two had a variable expression and the other fourteen were down-regulated in the treatments. These new findings certainly were a consequence of using a superior statistical analysis approach, since the original study did not take into account the dependence of data variability on the average signal intensity of each gene. The web interface, supplementary information, and the package source code are available, free, to non-commercial users at http://ipe.cbmeg.unicamp.br/pub/PMmA.

  6. Pipeline for macro- and microarray analyses.

    Science.gov (United States)

    Vicentini, R; Menossi, M

    2007-05-01

    The pipeline for macro- and microarray analyses (PMmA) is a set of scripts with a web interface developed to analyze DNA array data generated by array image quantification software. PMmA is designed for use with single- or double-color array data and to work as a pipeline in five classes (data format, normalization, data analysis, clustering, and array maps). It can also be used as a plugin in the BioArray Software Environment, an open-source database for array analysis, or used in a local version of the web service. All scripts in PMmA were developed in the PERL programming language and statistical analysis functions were implemented in the R statistical language. Consequently, our package is a platform-independent software. Our algorithms can correctly select almost 90% of the differentially expressed genes, showing a superior performance compared to other methods of analysis. The pipeline software has been applied to 1536 expressed sequence tags macroarray public data of sugarcane exposed to cold for 3 to 48 h. PMmA identified thirty cold-responsive genes previously unidentified in this public dataset. Fourteen genes were up-regulated, two had a variable expression and the other fourteen were down-regulated in the treatments. These new findings certainly were a consequence of using a superior statistical analysis approach, since the original study did not take into account the dependence of data variability on the average signal intensity of each gene. The web interface, supplementary information, and the package source code are available, free, to non-commercial users at http://ipe.cbmeg.unicamp.br/pub/PMmA. PMID:17464422

  7. Analysis of porcine MHC using microarrays.

    Science.gov (United States)

    Gao, Yu; Wahlberg, Per; Marthey, Sylvain; Esquerré, Diane; Jaffrézic, Florence; Lecardonnel, Jérome; Hugot, Karine; Rogel-Gaillard, Claire

    2012-07-15

    The major histocompatibility complex (MHC) in Mammals is one of the most gene dense regions of the genome and contains the polymorphic histocompatibility gene families known to be involved in pathogen response and control of auto-immunity. The MHC is a complex genetic system that provides an interesting model system to study genome expression regulation and genetic diversity at the megabase scale. The pig MHC or SLA (Swine Leucocyte Antigen) complex spans 2.4 megabases and 151 loci have been annotated. We will review key results from previous RNA expression studies using microarrays containing probes specific to annotated loci within SLA and in addition present novel data obtained using high-density tiling arrays encompassing the whole SLA complex. We have focused on transcriptome modifications of porcine peripheral blood mononuclear cells stimulated with a mixture of phorbol myristate acetate and ionomycin known to activate B and T cell proliferation. Our results show that numerous loci mapping to the SLA complex are affected by the treatment. A general decreased level of expression for class I and II genes and an up-regulation of genes involved in peptide processing and transport were observed. Tiling array-based experiments contributed to refined gene annotations as presented for one SLA class I gene referred to as SLA-11. In conclusion, high-density tiling arrays can serve as an excellent tool to draw comprehensive transcription maps, and improve genome annotations for the SLA complex. We are currently studying their relevance to characterize SLA genetic diversity in combination with high throughput next generation sequencing. PMID:21561666

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

    Directory of Open Access Journals (Sweden)

    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.

  9. Significance analysis of lexical bias in microarray data

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  11. A novel method for preparation of tissue microarray

    Institute of Scientific and Technical Information of China (English)

    Han-Lei Dan; Yan-Qing Ding; Chun-Hai Guo; Dian-Yuan Zhou; Ya-Li Zhang; Yan Zhang; Ya-Dong Wang; Zuo-Sheng Lai; Yu-Jie Yang; Hai-Hong Cui; Yan-Ting Jian; Jian Geng

    2004-01-01

    AIM: To improve the technique of tissue microarray (tissue chip).METHODS: A new tissue microarraying method was invented with a common microscope installed with a special holing needle, a sampling needle, and a special box fixing paraffin blocks on the microscope slide carrier. With the movement of microscope tube and objective stage on vertical and cross dimensions respectively, the holing procedure on the recipient paraffin blocks and sampling procedure of core tissue biopsies taken from the donor blocks were performed with the refitted microscope on the same platform. The precise observation and localization of representative regions in the donor blocks were also performed with the microscope equipped with a stereoscope.RESULTS: Highly-qualified tissue chips of colorectal tumors were produced by a new method, which simplified the conventional microarraying procedure, and was more convenient and accurate than that employing the existing tissue microarraying instruments.CONCLUSION: Using the refitted common microscope to produce tissue microarray is a simple, reliable, cost-effective and well-applicable technique.

  12. Advanced Data Mining of Leukemia Cells Micro-Arrays

    Directory of Open Access Journals (Sweden)

    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.

  13. 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.

  14. A Protein Microarray ELISA for Screening Biological Fluids

    Energy Technology Data Exchange (ETDEWEB)

    Varnum, Susan M.; Woodbury, Ronald L.; Zangar, Richard C.

    2004-02-01

    Protein microarrays permit the simultaneous measurement of many proteins in a small sample volume and therefore provide an attractive approach for the quantitative measurement of proteins in biological fluids, including serum. This chapter describes a microarray ELISA assay. Capture antibodies are immobilized onto a glass surface, the covalently attached antibodies bind a specific antigen from a sample overlaying the array. A second, biotinylated antibody that recognizes the same antigen as the first antibody but at a different epitope is then used for detection. Detection is based upon an enzymatic signal enhancement method known as tyramide signal amplification (TSA). By coupling a microarray-ELISA format with the signal amplification of tyramide deposition, the assay sensitivity is as low as sub-pg/ml.

  15. 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.

  16. 基于模糊关联规则和决策树的图像自动标注%Automatic image annotation based on fuzzy associationr ules and decision trees

    Institute of Scientific and Technical Information of China (English)

    李志欣; 李灵芝; 张灿龙

    2015-01-01

    传统的基于关联规则算法的图像自动标注存在“锐利边界”问题,使分类存在模糊性、不准确性。且随着多媒体技术的飞速发展,图像信息数据迅速增长,海量的图像数据会形成大量冗余的关联规则,这将导致分类效率大大降低。针对这2个问题,文中提出基于模糊关联规则和决策树的图像自动标注模型。该模型首先获得关联训练图像低层特征和高层语义的模糊关联规则,再利用决策树方法删减冗余的模糊关联规则,基于决策树删减后的模糊关联规则,大大减小了算法的计算复杂度。实验在Corel 5k和IAPR-TC12两个基准数据集上进行,并从精度、召回率、F-measure以及产生的规则数量几个度量措施上进行比较。与其他几种前沿的图像自动标注方法的结果对比表明,该方法在图像的标注精度和标注效率上有很大的提高。%The traditional automatic image annotation based on association rules exists the problem of sharp boundary, which makes classification more fuzzy and inaccurate.Moreover, with the rapid development of multimedia technology, the size of image data increases quickly.Massive image data will produce a lot of redundant association rules, which greatly decreases the efficiency of image classification.In order to solve these two problems, this paper proposes an auto-matic image annotation approach based on fuzzy association rules and decision trees.The approach firstly obtains fuzzy association rules which represent the fuzzy correlations between low-level visual features and high-level semantic concepts of training images .Then, decision tree is adopted to reduce the redundant fuzzy association rules.As a result, computa-tional complexity of the algorithm is decreased to a large degree.Experiments were done on Corel5k and IAPR-TC12 datasets.The evaluation measures are compared from the aspects of precision, recall, F-measure and the number

  17. AMDA: an R package for the automated microarray data analysis

    Directory of Open Access Journals (Sweden)

    Foti Maria

    2006-07-01

    Full Text Available Abstract Background Microarrays are routinely used to assess mRNA transcript levels on a genome-wide scale. Large amount of microarray datasets are now available in several databases, and new experiments are constantly being performed. In spite of this fact, few and limited tools exist for quickly and easily analyzing the results. Microarray analysis can be challenging for researchers without the necessary training and it can be time-consuming for service providers with many users. Results To address these problems we have developed an automated microarray data analysis (AMDA software, which provides scientists with an easy and integrated system for the analysis of Affymetrix microarray experiments. AMDA is free and it is available as an R package. It is based on the Bioconductor project that provides a number of powerful bioinformatics and microarray analysis tools. This automated pipeline integrates different functions available in the R and Bioconductor projects with newly developed functions. AMDA covers all of the steps, performing a full data analysis, including image analysis, quality controls, normalization, selection of differentially expressed genes, clustering, correspondence analysis and functional evaluation. Finally a LaTEX document is dynamically generated depending on the performed analysis steps. The generated report contains comments and analysis results as well as the references to several files for a deeper investigation. Conclusion AMDA is freely available as an R package under the GPL license. The package as well as an example analysis report can be downloaded in the Services/Bioinformatics section of the Genopolis http://www.genopolis.it/

  18. Label and Label-Free Detection Techniques for Protein Microarrays

    Directory of Open Access Journals (Sweden)

    Amir Syahir

    2015-04-01

    Full Text Available Protein microarray technology has gone through numerous innovative developments in recent decades. In this review, we focus on the development of protein detection methods embedded in the technology. Early microarrays utilized useful chromophores and versatile biochemical techniques dominated by high-throughput illumination. Recently, the realization of label-free techniques has been greatly advanced by the combination of knowledge in material sciences, computational design and nanofabrication. These rapidly advancing techniques aim to provide data without the intervention of label molecules. Here, we present a brief overview of this remarkable innovation from the perspectives of label and label-free techniques in transducing nano‑biological events.

  19. 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 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...

  20. Compressió de microarrays d'ADN

    OpenAIRE

    Pueyo Navarro, Iván

    2015-01-01

    La tecnologia relacionada amb la creació d'imatges de microarray d'ADN és una eina de gran importància en el descobriment de l'estructura i funcionament de la nostra informació genètica. Dins d'aquest camp, la detecció del comportament de determinats gens sota condicions especifiques adquireix una gran rellevància. La grandària de les imatges de microarray sol ser de mitjana elevada, a causa de la gran quantitat de gens que s'analitzen i al fet que s'intenta mantenir en les imatges el major c...

  1. Fluorescence Lifetime Imaging of Quantum Dot Labeled DNA Microarrays

    Directory of Open Access Journals (Sweden)

    Jonathan G. Terry

    2009-04-01

    Full Text Available Quantum dot (QD labeling combined with fluorescence lifetime imaging microscopy is proposed as a powerful transduction technique for the detection of DNA hybridization events. Fluorescence lifetime analysis of DNA microarray spots of hybridized QD labeled target indicated a characteristic lifetime value of 18.8 ns, compared to 13.3 ns obtained for spots of free QD solution, revealing that QD labels are sensitive to the spot microenvironment. Additionally, time gated detection was shown to improve the microarray image contrast ratio by 1.8, achieving femtomolar target sensitivity. Finally, lifetime multiplexing based on Qdot525 and Alexa430 was demonstrated using a single excitation-detection readout channel.

  2. 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.

  3. The tissue microarray OWL schema: An open-source tool for sharing tissue microarray data

    Directory of Open Access Journals (Sweden)

    Hyunseok P Kang

    2010-01-01

    Full Text Available Background: Tissue microarrays (TMAs are enormously useful tools for translational research, but incompatibilities in database systems between various researchers and institutions prevent the efficient sharing of data that could help realize their full potential. Resource Description Framework (RDF provides a flexible method to represent knowledge in triples, which take the form Subject- Predicate-Object. All data resources are described using Uniform Resource Identifiers (URIs, which are global in scope. We present an OWL (Web Ontology Language schema that expands upon the TMA data exchange specification to address this issue and assist in data sharing and integration. Methods: A minimal OWL schema was designed containing only concepts specific to TMA experiments. More general data elements were incorporated from predefined ontologies such as the NCI thesaurus. URIs were assigned using the Linked Data format. Results: We present examples of files utilizing the schema and conversion of XML data (similar to the TMA DES to OWL. Conclusion: By utilizing predefined ontologies and global unique identifiers, this OWL schema provides a solution to the limitations of XML, which represents concepts defined in a localized setting. This will help increase the utilization of tissue resources, facilitating collaborative translational research efforts.

  4. 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.

  5. 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...

  6. Large scale multiplex PCR improves pathogen detection by DNA microarrays

    Directory of Open Access Journals (Sweden)

    Krönke Martin

    2009-01-01

    Full Text Available Abstract Background Medium density DNA microchips that carry a collection of probes for a broad spectrum of pathogens, have the potential to be powerful tools for simultaneous species identification, detection of virulence factors and antimicrobial resistance determinants. However, their widespread use in microbiological diagnostics is limited by the problem of low pathogen numbers in clinical specimens revealing relatively low amounts of pathogen DNA. Results To increase the detection power of a fluorescence-based prototype-microarray designed to identify pathogenic microorganisms involved in sepsis, we propose a large scale multiplex PCR (LSplex PCR for amplification of several dozens of gene-segments of 9 pathogenic species. This protocol employs a large set of primer pairs, potentially able to amplify 800 different gene segments that correspond to the capture probes spotted on the microarray. The LSplex protocol is shown to selectively amplify only the gene segments corresponding to the specific pathogen present in the analyte. Application of LSplex increases the microarray detection of target templates by a factor of 100 to 1000. Conclusion Our data provide a proof of principle for the improvement of detection of pathogen DNA by microarray hybridization by using LSplex PCR.

  7. Thermodynamics of competitive surface adsorption on DNA microarrays

    International Nuclear Information System (INIS)

    Gene microarrays provide a powerful functional genomics technology which permits the expression profiling of tens of thousands of genes in parallel. The basic idea of their functioning is based on the sequence specificity of probe-target interactions combined with fluorescence detection. In reality, this straightforward principle is opposed by the complexity of the experimental system due to imperfections of chip fabrication and RNA preparation, due to the non-linearity of the probe response and especially due to competitive interactions which are inherently connected with the high throughput character of the method. We theoretically analysed aspects of the hybridization of DNA oligonucleotide probes with a complex multicomponent mixture of RNA fragments, such as the effect of different interactions between nucleotide strands competing with the formation of specific duplexes, electrostatic and entropic blocking, the fragmentation of the RNA, the incomplete synthesis of the probes and 'zipping' effects in the oligonucleotide duplexes. The effective hybridization affinities of microarray probes are considerably smaller than those for bulk hybridization owing to the effects discussed, but they correlate well with the bulk data on a relative scale. In general, the hybridization isotherms of microarray probes are shown to deviate from a Langmuir-type behaviour. Nevertheless isotherms of the Langmuir or Sips type are predicted to provide a relatively simple description of the non-linear, probe-specific concentration dependence of the signal intensity of microarray probes

  8. 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.

  9. Storing, linking, and mining microarray databases using SRS.

    NARCIS (Netherlands)

    A. Veldhoven (Antoine); D. de Lange (Don); M. Smid (Marcel); V. de Jager (Victor); J.A. Kors (Jan); G.W. Jenster (Guido)

    2005-01-01

    textabstractBACKGROUND: SRS (Sequence Retrieval System) has proven to be a valuable platform for storing, linking, and querying biological databases. Due to the availability of a broad range of different scientific databases in SRS, it has become a useful platform to incorporate and mine microarray

  10. A microarray immunoassay for simultaneous detection of proteins and bacteria

    Science.gov (United States)

    Delehanty, James B.; Ligler, Frances S.

    2002-01-01

    We report the development and characterization of an antibody microarray biosensor for the rapid detection of both protein and bacterial analytes under flow conditions. Using a noncontact microarray printer, biotinylated capture antibodies were immobilized at discrete locations on the surface of an avidin-coated glass microscope slide. Preservation of capture antibody function during the deposition process was accomplished with the use of a low-salt buffer containing sucrose and bovine serum albumin. The slide was fitted with a six-channel flow module that conducted analyte-containing solutions over the array of capture antibody microspots. Detection of bound analyte was subsequently achieved using fluorescent tracer antibodies. The pattern of fluorescent complexes was interrogated using a scanning confocal microscope equipped with a 635-nm laser. This microarray system was employed to detect protein and bacterial analytes both individually and in samples containing mixtures of analytes. Assays were completed in 15 min, and detection of cholera toxin, staphylococcal enterotoxin B, ricin, and Bacillus globigii was demonstrated at levels as low as 8 ng/mL, 4 ng/mL, 10 ng/mL, and 6.2 x 10(4) cfu/mL, respectively. The assays presented here are very fast, as compared to previously published methods for measuring antibody-antigen interactions using microarrays (minutes versus hours).

  11. 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...

  12. Detection of bacterial pathogens in environmental samples using DNA microarrays.

    Science.gov (United States)

    Call, Douglas R; Borucki, Monica K; Loge, Frank J

    2003-05-01

    Polymerase chain reaction (PCR) is an important tool for pathogen detection, but historically, it has not been possible to accurately identify PCR products without sequencing, Southern blots, or dot-blots. Microarrays can be coupled with PCR where they serve as a set of parallel dot-blots to enhance product detection and identification. Microarrays are composed of many discretely located probes on a solid substrate such as glass. Each probe is composed of a sequence that is complimentary to a pathogen-specific gene sequence. PCR is used to amplify one or more genes and the products are then hybridized to the array to identify species-specific polymorphism within one or more genes. We illustrate this type of array using 16S rDNA probes suitable for distinguishing between several salmonid pathogens. We also describe the use of microarrays for direct detection of either RNA or DNA without the aid of PCR, although the sensitivity of these systems currently limits their application for pathogen detection. Finally, microarrays can also be used to "fingerprint" bacterial isolates and they can be used to identify diagnostic markers suitable for developing new PCR-based detection assays. We illustrate this type of array for subtyping an important food-borne pathogen, Listeria monocytogenes. PMID:12654494

  13. A methodology for global validation of microarray experiments

    Directory of Open Access Journals (Sweden)

    Sladek Robert

    2006-07-01

    Full Text Available Abstract Background DNA microarrays are popular tools for measuring gene expression of biological samples. This ever increasing popularity is ensuring that a large number of microarray studies are conducted, many of which with data publicly available for mining by other investigators. Under most circumstances, validation of differential expression of genes is performed on a gene to gene basis. Thus, it is not possible to generalize validation results to the remaining majority of non-validated genes or to evaluate the overall quality of these studies. Results We present an approach for the global validation of DNA microarray experiments that will allow researchers to evaluate the general quality of their experiment and to extrapolate validation results of a subset of genes to the remaining non-validated genes. We illustrate why the popular strategy of selecting only the most differentially expressed genes for validation generally fails as a global validation strategy and propose random-stratified sampling as a better gene selection method. We also illustrate shortcomings of often-used validation indices such as overlap of significant effects and the correlation coefficient and recommend the concordance correlation coefficient (CCC as an alternative. Conclusion We provide recommendations that will enhance validity checks of microarray experiments while minimizing the need to run a large number of labour-intensive individual validation assays.

  14. Chromosome microarrays in diagnostic testing: interpreting the genomic data.

    Science.gov (United States)

    Peters, Greg B; Pertile, Mark D

    2014-01-01

    DNA-based Chromosome MicroArrays (CMAs) are now well established as diagnostic tools in clinical genetics laboratories. Over the last decade, the primary application of CMAs has been the genome-wide detection of a particular class of mutation known as copy number variants (CNVs). Since 2010, CMA testing has been recommended as a first-tier test for detection of CNVs associated with intellectual disability, autism spectrum disorders, and/or multiple congenital anomalies…in the post-natal setting. CNVs are now regarded as pathogenic in 14-18 % of patients referred for these (and related) disorders.Through consideration of clinical examples, and several microarray platforms, we attempt to provide an appreciation of microarray diagnostics, from the initial inspection of the microarray data, to the composing of the patient report. In CMA data interpretation, a major challenge comes from the high frequency of clinically irrelevant CNVs observed within "patient" and "normal" populations. As might be predicted, the more common and clinically insignificant CNVs tend to be the smaller ones resolution, and some miscalling of CNVs is unavoidable. In this, there is no ideal solution, but various strategies for handling noise are available. Even without solutions, consideration of these diagnostic problems per se is informative, as they afford critical insights into the biological and technical underpinnings of CNV discovery. These are indispensable to any clinician or scientist practising within the field of genome diagnostics. PMID:24870134

  15. 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.

  16. Protein Microarrays for Quantitative Detection of PAI-1 in Serum

    Institute of Scientific and Technical Information of China (English)

    Xu Ma; Qing-yun Zhang

    2012-01-01

    Objective:Plasminogen activator inhibitor-1 (PAl-1),one crucial component of the plasminogen activator system,is a major player in the pathogenesis of many vascular diseases as well as in cancer.High levels of PAI-1 in breast cancer tissue are associated with poor prognosis.The aim of this study is to evaluate rigorously the potential of serum PAl-1 concentration functioning as a general screening test in diagnostic or prognostic assays.Methods:A protein-microarray-based sandwich fluorescence immunoassay (FIA) was developed to detect PAl-1 in serum.Several conditions of this microarray-based FIA were optimized to establish an efficacious method.Serum specimens of 84 healthy women and 285 women with breast cancer were analyzed using the optimized FIA microarray.Results:The median serum PAl-1 level of breast cancer patients was higher than that of healthy women (109.7 ng/ml vs.63.4 ng/ml).Analysis of covariance revealed that PAl-1 levels of the two groups were significantly different (P<0.001) when controlling for an age effect on PAl-1 levels.However,PAl-1 values in TNM stage Ⅰ-Ⅳ patients respectively were not significantly different from each other.Conclusion:This microarray-based sandwich FIA holds potential for quantitative analysis of tumor markers such as PAl-1.

  17. Microarrays/DNA Chips for the Detection of Waterborne Pathogens.

    Science.gov (United States)

    Vale, Filipa F

    2016-01-01

    DNA microarrays are useful for the simultaneous detection of microorganisms in water samples. Specific probes targeting waterborne pathogens are selected with bioinformatics tools, synthesized and spotted onto a DNA array. Here, the construction of a DNA chip for waterborne pathogen detection is described, including the processes of probe in silico selection, synthesis, validation, and data analysis. PMID:27460375

  18. 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...

  19. Disc-based microarrays: principles and analytical applications.

    Science.gov (United States)

    Morais, Sergi; Puchades, Rosa; Maquieira, Ángel

    2016-07-01

    The idea of using disk drives to monitor molecular biorecognition events on regular optical discs has received considerable attention during the last decade. CDs, DVDs, Blu-ray discs and other new optical discs are universal and versatile supports with the potential for development of protein and DNA microarrays. Besides, standard disk drives incorporated in personal computers can be used as compact and affordable optical reading devices. Consequently, a CD technology, resulting from the audio-video industry, has been used to develop analytical applications in health care, environmental monitoring, food safety and quality assurance. The review presents and critically evaluates the current state of the art of disc-based microarrays with illustrative examples, including past, current and future developments. Special mention is made of the analytical developments that use either chemically activated or raw standard CDs where proteins, oligonucleotides, peptides, haptens or other biological probes are immobilized. The discs are also used to perform the assays and must maintain their readability with standard optical drives. The concept and principle of evolving disc-based microarrays and the evolution of disk drives as optical detectors are also described. The review concludes with the most relevant uses ordered chronologically to provide an overview of the progress of CD technology applications in the life sciences. Also, it provides a selection of important references to the current literature. Graphical Abstract High density disc-based microarrays. PMID:26922341

  20. Exploiting fluorescence for multiplex immunoassays on protein microarrays

    International Nuclear Information System (INIS)

    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. (topical review)

  1. Electrostatic readout of DNA microarrays with charged microspheres

    Energy Technology Data Exchange (ETDEWEB)

    Clack, Nathan G. [Univ. of California, Berkeley, CA (United States). Biophysics Graduate Group; Salaita, Khalid [Univ. of California, Berkeley, CA (United States). Department of Chemistry; Groves, Jay T. [Univ. of California, Berkeley, CA (United States). Biophysics Graduate Group and Department of Chemistry

    2008-06-29

    DNA microarrays are used for gene-expression profiling, single-nucleotide polymorphism detection and disease diagnosis. A persistent challenge in this area is the lack of microarray screening technology suitable for integration into routine clinical care. In this paper, we describe a method for sensitive and label-free electrostatic readout of DNA or RNA hybridization on microarrays. The electrostatic properties of the microarray are measured from the position and motion of charged microspheres randomly dispersed over the surface. We demonstrate nondestructive electrostatic imaging with 10-μm lateral resolution over centimeter-length scales, which is four-orders of magnitude larger than that achievable with conventional scanning electrostatic force microscopy. Changes in surface charge density as a result of specific hybridization can be detected and quantified with 50-pM sensitivity, single base-pair mismatch selectivity and in the presence of complex background. Lastly, because the naked eye is sufficient to read out hybridization, this approach may facilitate broad application of multiplexed assays.

  2. Differentiating pancreatic lesions by Microarray and QPCR analysis of pancreatic juice RNAs

    NARCIS (Netherlands)

    C.D. Rogers; N. Fukushima; N. Sato; C. Shi; N. Prasad; S.R. Hustinx; H. Matsubayashi; M. Canto; J.R. Eshleman; R.H. Hruban; M. Goggins

    2006-01-01

    Background: The gene expression profile of pancreatic cancer is significantly different from that of normal pancreas. Differences in gene expression are detectable using microarrays, but microarrays have traditionally been applied to pancreatic cancer tissue obtained from surgical resection. We hypo

  3. DNA Microarray-based Ecotoxicological Biomarker Discovery in a Small Fish Model Species

    Science.gov (United States)

    This paper addresses several issues critical to use of zebrafish oligonucleotide microarrays for computational toxicology research on endocrine disrupting chemicals using small fish models, and more generally, the use of microarrays in aquatic toxicology.

  4. 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

  5. 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

  6. AffyMiner: mining differentially expressed genes and biological knowledge in GeneChip microarray data

    OpenAIRE

    Xia Yuannan; Nguyen The V; Lu Guoqing; Fromm Michael

    2006-01-01

    Abstract Background DNA microarrays are a powerful tool for monitoring the expression of tens of thousands of genes simultaneously. With the advance of microarray technology, the challenge issue becomes how to analyze a large amount of microarray data and make biological sense of them. Affymetrix GeneChips are widely used microarrays, where a variety of statistical algorithms have been explored and used for detecting significant genes in the experiment. These methods rely solely on the quanti...

  7. 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.

  8. Microarray analysis in the archaeon Halobacterium salinarum strain R1.

    Directory of Open Access Journals (Sweden)

    Jens Twellmeyer

    Full Text Available BACKGROUND: Phototrophy of the extremely halophilic archaeon Halobacterium salinarum was explored for decades. The research was mainly focused on the expression of bacteriorhodopsin and its functional properties. In contrast, less is known about genome wide transcriptional changes and their impact on the physiological adaptation to phototrophy. The tool of choice to record transcriptional profiles is the DNA microarray technique. However, the technique is still rarely used for transcriptome analysis in archaea. METHODOLOGY/PRINCIPAL FINDINGS: We developed a whole-genome DNA microarray based on our sequence data of the Hbt. salinarum strain R1 genome. The potential of our tool is exemplified by the comparison of cells growing under aerobic and phototrophic conditions, respectively. We processed the raw fluorescence data by several stringent filtering steps and a subsequent MAANOVA analysis. The study revealed a lot of transcriptional differences between the two cell states. We found that the transcriptional changes were relatively weak, though significant. Finally, the DNA microarray data were independently verified by a real-time PCR analysis. CONCLUSION/SIGNIFICANCE: This is the first DNA microarray analysis of Hbt. salinarum cells that were actually grown under phototrophic conditions. By comparing the transcriptomics data with current knowledge we could show that our DNA microarray tool is well applicable for transcriptome analysis in the extremely halophilic archaeon Hbt. salinarum. The reliability of our tool is based on both the high-quality array of DNA probes and the stringent data handling including MAANOVA analysis. Among the regulated genes more than 50% had unknown functions. This underlines the fact that haloarchaeal phototrophy is still far away from being completely understood. Hence, the data recorded in this study will be subject to future systems biology analysis.

  9. Functional protein microarray as molecular decathlete: a versatile player in clinical proteomics.

    Science.gov (United States)

    Zhu, Heng; Cox, Eric; Qian, Jiang

    2012-12-01

    Functional protein microarrays were developed as a high-throughput tool to overcome the limitations of DNA microarrays and to provide a versatile platform for protein functional analyses. Recent years have witnessed tremendous growth in the use of protein microarrays, particularly functional protein microarrays, to address important questions in the field of clinical proteomics. In this review, we will summarize some of the most innovative and exciting recent applications of protein microarrays in clinical proteomics, including biomarker identification, pathogen-host interactions, and cancer biology. PMID:23027439

  10. Aptamer Affinity Maturation by Resampling and Microarray Selection.

    Science.gov (United States)

    Kinghorn, Andrew B; Dirkzwager, Roderick M; Liang, Shaolin; Cheung, Yee-Wai; Fraser, Lewis A; Shiu, Simon Chi-Chin; Tang, Marco S L; Tanner, Julian A

    2016-07-19

    Aptamers have significant potential as affinity reagents, but better approaches are critically needed to discover higher affinity nucleic acids to widen the scope for their diagnostic, therapeutic, and proteomic application. Here, we report aptamer affinity maturation, a novel aptamer enhancement technique, which combines bioinformatic resampling of aptamer sequence data and microarray selection to navigate the combinatorial chemistry binding landscape. Aptamer affinity maturation is shown to improve aptamer affinity by an order of magnitude in a single round. The novel aptamers exhibited significant adaptation, the complexity of which precludes discovery by other microarray based methods. Honing aptamer sequences using aptamer affinity maturation could help optimize a next generation of nucleic acid affinity reagents. PMID:27346322

  11. Investigating amoebic pathogenesis using Entamoeba histolytica DNA microarrays

    Indian Academy of Sciences (India)

    Upinder Singh; Preetam Shah

    2002-11-01

    Entamoeba histolytica, a protozoan parasite, causes diarrhea and liver abscesses resulting in 50 million cases of infection worldwide annually. Elucidation of parasite virulence determinants has recently been investigated using genetic approaches. We have undertaken a genomics approach to identify novel virulence determinants in the parasite. A DNA microarray of E. histolytica is being developed based on sequenced genomic clones from the genome sequencing efforts of The Institute of Genomic Research (TIGR) and the Sanger Center. Hybridization of the slides with samples labelled differentially using fluorescent dyes allows the characterization of transcriptional profiles of genes under the biological conditions tested. Additionally, a genome-wide comparison of E. histolytica and E. dispar can be undertaken. The development of an E. histolytica microarray will be outlined and its uses in identifying novel virulence determinants and characterizing amoebic biology will be discussed.

  12. MatArray: a Matlab toolbox for microarray data.

    Science.gov (United States)

    Venet, David

    2003-03-22

    The microarray technology allows the high-throughput quantification of the mRNA level of thousands of genes under dozens of conditions, generating a wealth of data which must be analyzed using some form of computational means. A popular framework for such analysis is Matlab, a powerful computing language for which many functions have been written. However, although complex topics like neural networks or principal component analysis are freely available in Matlab, functions to perform more basic tasks like data normalization or hierarchical clustering in an efficient manner are not. The MatArray toolbox aims at filling this gap by offering efficient implementations of the most needed functions for microarray analysis. The functions in the toolbox are command-line only, since it is geared toward seasoned Matlab users.

  13. Iterative normalization of cDNA microarray data.

    Science.gov (United States)

    Wang, Yue; Lu, Jianping; Lee, Richard; Gu, Zhiping; Clarke, Robert

    2002-03-01

    This paper describes a new approach to normalizing microarray expression data. The novel feature is to unify the tasks of estimating normalization coefficients and identifying control gene set. Unification is realized by constructing a window function over the scatter plot defining the subset of constantly expressed genes and by affecting optimization using an iterative procedure. The structure of window function gates contributions to the control gene set used to estimate normalization coefficients. This window measures the consistency of the matched neighborhoods in the scatter plot and provides a means of rejecting control gene outliers. The recovery of normalizational regression and control gene selection are interleaved and are realized by applying coupled operations to the mean square error function. In this way, the two processes bootstrap one another. We evaluate the technique on real microarray data from breast cancer cell lines and complement the experiment with a data cluster visualization study. PMID:11936594

  14. R/BHC: fast Bayesian hierarchical clustering for microarray data

    Directory of Open Access Journals (Sweden)

    Grant Murray

    2009-08-01

    Full Text Available Abstract Background Although the use of clustering methods has rapidly become one of the standard computational approaches in the literature of microarray gene expression data analysis, little attention has been paid to uncertainty in the results obtained. Results We present an R/Bioconductor port of a fast novel algorithm for Bayesian agglomerative hierarchical clustering and demonstrate its use in clustering gene expression microarray data. The method performs bottom-up hierarchical clustering, using a Dirichlet Process (infinite mixture to model uncertainty in the data and Bayesian model selection to decide at each step which clusters to merge. Conclusion Biologically plausible results are presented from a well studied data set: expression profiles of A. thaliana subjected to a variety of biotic and abiotic stresses. Our method avoids several limitations of traditional methods, for example how many clusters there should be and how to choose a principled distance metric.

  15. Nanomedicine, microarrays and their applications in clinical microbiology

    Directory of Open Access Journals (Sweden)

    Özcan Deveci

    2010-12-01

    Full Text Available Growing interest in the future medical applications of nanotechnology is leading to the emergence of a new scientific field that called as “nanomedicine”. Nanomedicine may be defined as the investigating, treating, reconstructing and controlling human biology and health at the molecular level, using engineered nanodevices and nanostructures. Microarray technology is a revolutionary tool for elucidating roles of genes in infectious diseases, shifting from traditional methods of research to integrated approaches. This technology has great potential to provide medical diagnosis, monitor treatment and help in the development of new tools for infectious disease prevention and/or management. The aim of this paper is to provide an overview of the current application of microarray platforms and nanomedicine in the study of experimental microbiology and the impact of this technology in clinical settings.

  16. Enhancing the quality metric of protein microarray image

    Institute of Scientific and Technical Information of China (English)

    王立强; 倪旭翔; 陆祖康; 郑旭峰; 李映笙

    2004-01-01

    The novel method of improving the quality metric of protein microarray image presented in this paper reduces impulse noise by using an adaptive median filter that employs the switching scheme based on local statistics characters; and achieves the impulse detection by using the difference between the standard deviation of the pixels within the filter window and the current pixel of concern. It also uses a top-hat filter to correct the background variation. In order to decrease time consumption, the top-hat filter core is cross structure. The experimental results showed that, for a protein microarray image contaminated by impulse noise and with slow background variation, the new method can significantly increase the signal-to-noise ratio, correct the trends in the background, and enhance the flatness of the background and the consistency of the signal intensity.

  17. Bioinformatics and Microarray Data Analysis on the Cloud.

    Science.gov (United States)

    Calabrese, Barbara; Cannataro, Mario

    2016-01-01

    High-throughput platforms such as microarray, mass spectrometry, and next-generation sequencing are producing an increasing volume of omics data that needs large data storage and computing power. Cloud computing offers massive scalable computing and storage, data sharing, on-demand anytime and anywhere access to resources and applications, and thus, it may represent the key technology for facing those issues. In fact, in the recent years it has been adopted for the deployment of different bioinformatics solutions and services both in academia and in the industry. Although this, cloud computing presents several issues regarding the security and privacy of data, that are particularly important when analyzing patients data, such as in personalized medicine. This chapter reviews main academic and industrial cloud-based bioinformatics solutions; with a special focus on microarray data analysis solutions and underlines main issues and problems related to the use of such platforms for the storage and analysis of patients data. PMID:25863787

  18. Classification analysis of microarray data based on ontological engineering

    Institute of Scientific and Technical Information of China (English)

    LI Guo-qi; SHENG Huan-ye

    2007-01-01

    Background knowledge is important for data mining, especially in complicated situation. Ontological engineering is the successor of knowledge engineering. The sharable knowledge bases built on ontology can be used to provide background knowledge to direct the process of data mining. This paper gives a common introduction to the method and presents a practical analysis example using SVM (support vector machine) as the classifier. Gene Ontology and the accompanying annotations compose a big knowledge base, on which many researches have been carried out. Microarray dataset is the output of DNA chip.With the help of Gene Ontology we present a more elaborate analysis on microarray data than former researchers. The method can also be used in other fields with similar scenario.

  19. DNA Microarray-Based Typing of Streptococcus agalactiae Isolates

    OpenAIRE

    Nitschke, Heike; Slickers, Peter; Müller, Elke; Ehricht, Ralf; Monecke, Stefan

    2014-01-01

    Streptococcus agalactiae frequently colonizes the urogenital tract, and it is a major cause of bacterial septicemia, meningitis, and pneumonia in newborns. For typing purposes, a microarray targeting group B streptococcus (GBS) virulence-associated markers and resistance genes was designed and validated with reference strains, as well as clinical and veterinary isolates. Selected isolates were also subjected to multilocus sequence typing. It was observed that putative typing markers, such as ...

  20. DNA-Microarray-based Genotyping of Clostridium difficile

    OpenAIRE

    Gawlik, Darius; Slickers, Peter; Engelmann, Ines; Müller, Elke; Lück, Christian; Friedrichs, Anette; Ehricht, Ralf; Monecke, Stefan

    2015-01-01

    Background Clostridium difficile can cause antibiotic-associated diarrhea and a possibility of outbreaks in hospital settings warrants molecular typing. A microarray was designed that included toxin genes (tcdA/B, cdtA/B), genes related to antimicrobial resistance, the slpA gene and additional variable genes. Results DNA of six reference strains and 234 clinical isolates from South-Western and Eastern Germany was subjected to linear amplification and labeling with dUTP-linked biotin. Amplicon...

  1. Assessing the Application of Tissue Microarray Technology to Kidney Research

    OpenAIRE

    Zhang, Ming-Zhi; Su, Yinghao; Yao, Bing; Zheng, Wei; deCaestecker, Mark; Harris, Raymond C.

    2010-01-01

    Tissue microarray (TMA) is a new high-throughput method that enables simultaneous analysis of the profiles of protein expression in multiple tissue samples. TMA technology has not previously been adapted for physiological and pathophysiological studies of rodent kidneys. We have evaluated the validity and reliability of using TMA to assess protein expression in mouse and rat kidneys. A representative TMA block that we have produced included: (1) mouse and rat kidney cortex, outer medulla, and...

  2. Portable System for Microbial Sample Preparation and Oligonucleotide Microarray Analysis

    OpenAIRE

    Bavykin, Sergei G.; Akowski, James P.; Zakhariev, Vladimir M.; Barsky, Viktor E.; Perov, Alexander N.; Mirzabekov, Andrei D.

    2001-01-01

    We have developed a three-component system for microbial identification that consists of (i) a universal syringe-operated silica minicolumn for successive DNA and RNA isolation, fractionation, fragmentation, fluorescent labeling, and removal of excess free label and short oligonucleotides; (ii) microarrays of immobilized oligonucleotide probes for 16S rRNA identification; and (iii) a portable battery-powered device for imaging the hybridization of fluorescently labeled RNA fragments with the ...

  3. Microarray analysis of gene expression profiles in ripening pineapple fruits

    Directory of Open Access Journals (Sweden)

    Koia Jonni H

    2012-12-01

    Full Text Available Abstract Background Pineapple (Ananas comosus is a tropical fruit crop of significant commercial importance. Although the physiological changes that occur during pineapple fruit development have been well characterized, little is known about the molecular events that occur during the fruit ripening process. Understanding the molecular basis of pineapple fruit ripening will aid the development of new varieties via molecular breeding or genetic modification. In this study we developed a 9277 element pineapple microarray and used it to profile gene expression changes that occur during pineapple fruit ripening. Results Microarray analyses identified 271 unique cDNAs differentially expressed at least 1.5-fold between the mature green and mature yellow stages of pineapple fruit ripening. Among these 271 sequences, 184 share significant homology with genes encoding proteins of known function, 53 share homology with genes encoding proteins of unknown function and 34 share no significant homology with any database accession. Of the 237 pineapple sequences with homologs, 160 were up-regulated and 77 were down-regulated during pineapple fruit ripening. DAVID Functional Annotation Cluster (FAC analysis of all 237 sequences with homologs revealed confident enrichment scores for redox activity, organic acid metabolism, metalloenzyme activity, glycolysis, vitamin C biosynthesis, antioxidant activity and cysteine peptidase activity, indicating the functional significance and importance of these processes and pathways during pineapple fruit development. Quantitative real-time PCR analysis validated the microarray expression results for nine out of ten genes tested. Conclusions This is the first report of a microarray based gene expression study undertaken in pineapple. Our bioinformatic analyses of the transcript profiles have identified a number of genes, processes and pathways with putative involvement in the pineapple fruit ripening process. This study

  4. Pattern-driven neighborhood search for biclustering of microarray data

    OpenAIRE

    Ayadi, Wassim; Elloumi, Mourad; Hao, Jin-Kao

    2012-01-01

    Background Biclustering aims at finding subgroups of genes that show highly correlated behaviors across a subgroup of conditions. Biclustering is a very useful tool for mining microarray data and has various practical applications. From a computational point of view, biclustering is a highly combinatorial search problem and can be solved with optimization methods. Results We describe a stochastic pattern-driven neighborhood search algorithm for the biclustering problem. Starting from an initi...

  5. Nanomedicine, microarrays and their applications in clinical microbiology

    OpenAIRE

    Özcan Deveci; Erkan Yula

    2010-01-01

    Growing interest in the future medical applications of nanotechnology is leading to the emergence of a new scientific field that called as “nanomedicine”. Nanomedicine may be defined as the investigating, treating, reconstructing and controlling human biology and health at the molecular level, using engineered nanodevices and nanostructures. Microarray technology is a revolutionary tool for elucidating roles of genes in infectious diseases, shifting from traditional methods of research to int...

  6. Parsimonious selection of useful genes in microarray gene expression data

    OpenAIRE

    González Navarro, Félix Fernando; Belanche Muñoz, Luis Antonio

    2011-01-01

    Machine Learning methods have of late made significant efforts to solving multidisciplinary problems in the field of cancer classification in microarray gene expression data. These tasks are characterized by a large number of features and a few observations, making the modeling a non-trivial undertaking. In this work we apply entropic filter methods for gene selection, in combination with several off-the-shelf classifiers. The introduction of bootstrap resampling techniques permits the achiev...

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

    Directory of Open Access Journals (Sweden)

    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

  8. Tissue Microarray A New Tool for Cancer Research

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    Shanghai Outdo Biotech Co.Ltd. (Outdo Biotech) is a leading company in human/animal Tissue Microarrays (TMA) and "Clinical-Type" Gene Chip (CTGC) in China. Our shareholders are Shanghai Biochip Co., Ltd. & National Engineering Center for Biochip at Shanghai, Shanghai Cancer institute and Eastern Liver and Bladder Hospital of Second Military Medical University. TMA is a mean of combining tens to hundreds of specimens of tissue, paraffin embedded or frozen, onto a single slide for analysis at once. Our constr...

  9. 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.

  10. RECOGNITION OF CDNA MICROARRAY IMAGE USING FEEDFORWARD ARTIFICIAL NEURAL NETWORK

    Directory of Open Access Journals (Sweden)

    R. M. Farouk

    2014-09-01

    Full Text Available The complementary DNA (cDNA sequence considered the magic biometric technique for personal identification. Microarray image processing used for the concurrent genes identification. In this paper, we present a new method for cDNA recognition based on the artificial neural network (ANN. We have segmented the location of the spots in a cDNA microarray. Thus, a precise localization and segmenting of a spot are essential to obtain a more exact intensity measurement, leading to a more accurate gene expression measurement. The segmented cDNA microarray image resized and used as an input for the proposed artificial neural network. For matching and recognition, we have trained the artificial neural network. Recognition results are given for the galleries of cDNA sequences . The numerical results show that, the proposed matching technique is an effective in the cDNA sequences process. The experimental results of our matching approach using different databases shows that, the proposed technique is an effective matching performance.

  11. Coupled Two-Way Clustering Analysis of Gene Microarray Data

    CERN Document Server

    Getz, G; Domany, E

    2000-01-01

    We present a novel coupled two-way clustering approach to gene microarray data analysis. The main idea is to identify subsets of the genes and samples, such that when one of these is used to cluster the other, stable and significant partitions emerge. The search for such subsets is a computationally complex task: we present an algorithm, based on iterative clustering, which performs such a search. This analysis is especially suitable for gene microarray data, where the contributions of a variety of biological mechanisms to the gene expression levels are entangled in a large body of experimental data. The method was applied to two gene microarray data sets, on colon cancer and leukemia. By identifying relevant subsets of the data and focusing on them we were able to discover partitions and correlations that were masked and hidden when the full dataset was used in the analysis. Some of these partitions have clear biological interpretation; others can serve to identify possible directions for future research.

  12. Fecal source tracking in water using a mitochondrial DNA microarray.

    Science.gov (United States)

    Vuong, Nguyet-Minh; Villemur, Richard; Payment, Pierre; Brousseau, Roland; Topp, Edward; Masson, Luke

    2013-01-01

    A mitochondrial-based microarray (mitoArray) was developed for rapid identification of the presence of 28 animals and one family (cervidae) potentially implicated in fecal pollution in mixed activity watersheds. Oligonucleotide probes for genus or subfamily-level identification were targeted within the 12S rRNA - Val tRNA - 16S rRNA region in the mitochondrial genome. This region, called MI-50, was selected based on three criteria: 1) the ability to be amplified by universal primers 2) these universal primer sequences are present in most commercial and domestic animals of interest in source tracking, and 3) that sufficient sequence variation exists within this region to meet the minimal requirements for microarray probe discrimination. To quantify the overall level of mitochondrial DNA (mtDNA) in samples, a quantitative-PCR (Q-PCR) universal primer pair was also developed. Probe validation was performed using DNA extracted from animal tissues and, for many cases, animal-specific fecal samples. To reduce the amplification of potentially interfering fish mtDNA sequences during the MI-50 enrichment step, a clamping PCR method was designed using a fish-specific peptide nucleic acid. DNA extracted from 19 water samples were subjected to both array and independent PCR analyses. Our results confirm that the mitochondrial microarray approach method could accurately detect the dominant animals present in water samples emphasizing the potential for this methodology in the parallel scanning of a large variety of animals normally monitored in fecal source tracking.

  13. A Glance at DNA Microarray Technology and Applications

    Directory of Open Access Journals (Sweden)

    Amir-Ata Saei

    2011-08-01

    Full Text Available Introduction: Because of huge impacts of “OMICS” technologies in life sciences, many researchers aim to implement such high throughput approach to address cellular and/or molecular functions in response to any influential intervention in genomics, proteomics, or metabolomics levels. However, in many cases, use of such technologies often encounters some cybernetic difficulties in terms of knowledge extraction from a bunch of data using related softwares. In fact, there is little guidance upon data mining for novices. The main goal of this article is to provide a brief review on different steps of microarray data handling and mining for novices and at last to introduce different PC and/or web-based softwares that can be used in preprocessing and/or data mining of microarray data. Methods: To pursue such aim, recently published papers and microarray softwares were reviewed. Results: It was found that defining the true place of the genes in cell networks is the main phase in our understanding of programming and functioning of living cells. This can be obtained with global/selected gene expression profiling. Conclusion: Studying the regulation patterns of genes in groups, using clustering and classification methods helps us understand different pathways in the cell, their functions, regulations and the way one component in the system affects the other one. These networks can act as starting points for data mining and hypothesis generation, helping us reverse engineer.

  14. Application of nanostructured biochips for efficient cell transfection microarrays

    Science.gov (United States)

    Akkamsetty, Yamini; Hook, Andrew L.; Thissen, Helmut; Hayes, Jason P.; Voelcker, Nicolas H.

    2007-01-01

    Microarrays, high-throughput devices for genomic analysis, can be further improved by developing materials that are able to manipulate the interfacial behaviour of biomolecules. This is achieved both spatially and temporally by smart materials possessing both switchable and patterned surface properties. A system had been developed to spatially manipulate both DNA and cell growth based upon the surface modification of highly doped silicon by plasma polymerisation and polyethylene grafting followed by masked laser ablation for formation of a pattered surface with both bioactive and non-fouling regions. This platform has been successfully applied to transfected cell microarray applications with the parallel expression of genes by utilising its ability to direct and limit both DNA and cell attachment to specific sites. One of the greatest advantages of this system is its application to reverse transfection, whereupon by utilising the switchable adsorption and desorption of DNA using a voltage bias, the efficiency of cell transfection can be enhanced. However, it was shown that application of a voltage also reduces the viability of neuroblastoma cells grown on a plasma polymer surface, but not human embryonic kidney cells. This suggests that the application of a voltage may not only result in the desorption of bound DNA but may also affect attached cells. The characterisation of a DNA microarray by contact printing has also been investigated.

  15. Sequencing ebola and marburg viruses genomes using microarrays.

    Science.gov (United States)

    Hardick, Justin; Woelfel, Roman; Gardner, Warren; Ibrahim, Sofi

    2016-08-01

    Periodic outbreaks of Ebola and Marburg hemorrhagic fevers have occurred in Africa over the past four decades with case fatality rates reaching as high as 90%. The latest Ebola outbreak in West Africa in 2014 raised concerns that these infections can spread across continents and pose serious health risks. Early and accurate identification of the causative agents is necessary to contain outbreaks. In this report, we describe sequencing-by-hybridization (SBH) technique using high density microarrays to identify Ebola and Marburg viruses. The microarrays were designed to interrogate the sequences of entire viral genomes, and were evaluated with three species of Ebolavirus (Reston, Sudan, and Zaire), and three strains of Marburgvirus (Angola, Musoke, and Ravn). The results showed that the consensus sequences generated with four or more hybridizations had 92.1-98.9% accuracy over 95-99% of the genomes. Additionally, with SBH microarrays it was possible to distinguish between different strains of the Lake Victoria Marburgvirus. J. Med. Virol. 88:1303-1308, 2016. © 2016 Wiley Periodicals, Inc. PMID:26822839

  16. Rapid bacterial identification using evanescent-waveguide oligonucleotide microarray classification.

    Science.gov (United States)

    Francois, Patrice; Charbonnier, Yvan; Jacquet, Jean; Utinger, Dominic; Bento, Manuela; Lew, Daniel; Kresbach, Gerhard M; Ehrat, Markus; Schlegel, Werner; Schrenzel, Jacques

    2006-06-01

    Bacterial identification relies primarily on culture-based methodologies and requires 48-72 h to deliver results. We developed and used i) a bioinformatics strategy to select oligonucleotide signature probes, ii) a rapid procedure for RNA labelling and hybridization, iii) an evanescent-waveguide oligoarray with exquisite signal/noise performance, and iv) informatics methods for microarray data analysis. Unique 19-mer signature oligonucleotides were selected in the 5'-end of 16s rDNA genes of human pathogenic bacteria. Oligonucleotides spotted onto a Ta(2)O(5)-coated microarray surface were incubated with chemically labelled total bacterial RNA. Rapid hybridization and stringent washings were performed before scanning and analyzing the slide. In the present paper, the eight most abundant bacterial pathogens representing >54% of positive blood cultures were selected. Hierarchical clustering analysis of hybridization data revealed characteristic patterns, even for closely related species. We then evaluated artificial intelligence-based approaches that outperformed conventional threshold-based identification schemes on cognate probes. At this stage, the complete procedure applied to spiked blood cultures was completed in less than 6 h. In conclusion, when coupled to optimal signal detection strategy, microarrays provide bacterial identification within a few hours post-sampling, allowing targeted antimicrobial prescription. PMID:16216356

  17. Genopal™: a novel hollow fibre array for focused microarray analysis.

    Science.gov (United States)

    Okuzaki, Daisuke; Fukushima, Tatsunobu; Tougan, Takahiro; Ishii, Tomonori; Kobayashi, Shigeto; Yoshizaki, Kazuyuki; Akita, Takashi; Nojima, Hiroshi

    2010-12-01

    Expression profiling of target genes in patient blood is a powerful tool for RNA diagnosis. Here, we describe Genopal™, a novel platform ideal for efficient focused microarray analysis. Genopal™, which consists of gel-filled fibres, is advantageous for high-quality mass production via large-scale slicing of the Genopal™ block. We prepared two arrays, infectant and autoimmunity, that provided highly reliable data in terms of repetitive scanning of the same and/or distinct microarrays. Moreover, we demonstrated that Genopal™ had sensitivity sufficient to yield signals in short hybridization times (0.5 h). Application of the autoimmunity array to blood samples allowed us to identify an expression pattern specific to Takayasu arteritis based on the Spearman rank correlation by comparing the reference profile with those of several autoimmune diseases and healthy volunteers (HVs). The comparison of these data with those obtained by other methods revealed that they exhibited similar expression profiles of many target genes. Taken together, these data demonstrate that Genopal™ is an advantageous platform for focused microarrays with regard to its low cost, rapid results and reliable quality. PMID:21059707

  18. Microarray, SAGE and their applications to cardiovascular diseases

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    The wealth of DNA data generated by the human genome project coupling with recently invented high-throughput gene expression profiling techniques has dramatically sped up the process for biomedical researchers on elucidating the role of genes in human diseases. One powerful method to reveal insight into gene functions is the systematic analysis of gene expression. Two popular high-throughput gene expression technologies, microarray and Serial Analysis of Gene Expression (SAGE) are capable of producing large amounts of gene expression data with the potential of providing novel insights into fundamental disease processes, especially complex syndromes such as cardiovascular disease, whose etiologies are due to multiple genetic factors and their interplay with the environment. Microarray and SAGE have already been used to examine gene expression patterns of cell-culture, animal and human tissues models of cardiovascular diseases. In this review, we will first give a brief introduction of microarray and SAGE technologies and point out their limitations. We will then discuss the major discoveries and the new biological insightsthat have emerged from their applications to cardiovascular diseases. Finally we will touch upon potential challenges and future developments in this area.

  19. Subtype Identification of Avian Influenza Virus on DNA Microarray

    Institute of Scientific and Technical Information of China (English)

    WANG Xiu-rong; YU Kang-zhen; DENG Guo-hua; SHI Rui; LIU Li-ling; QIAO Chuan-ling; BAO Hong-mei; KONG Xian-gang; CHEN Hua-lan

    2005-01-01

    We have developed a rapid microarray-based assay for the reliable detection of H5, H7 and H9 subtypes of avian influenza virus (AIV). The strains used in the experiment were A/Goose/Guangdong/1/96 (H5N1), A/African starling/983/79 (H7N1) and A/Turkey/Wiscosin/1/66 (H9N2). The capture DNAs clones which encoding approximate 500-bp avian influenza virus gene fragments obtained by RT-PCR, were spotted on a slide-bound microarray. Cy5-1abeled fluorescent cDNAs,which generated from virus RNA during reverse transcription were hybridized to these capture DNAs. These capture DNAs contained multiple fragments of the hemagglutinin and matrix protein genes of AIV respectively, for subtyping and typing AIV. The arrays were scanned to determine the probe binding sites. The hybridization pattern agreed approximately with the known grid location of each target. The results show that DNA microarray technology provides a useful diagnostic method for AIV.

  20. Laser-based patterning for transfected cell microarrays

    Energy Technology Data Exchange (ETDEWEB)

    Hook, Andrew L; Creasey, Rhiannon; Voelcker, Nicolas H [Flinders University, GPO Box 2100, Bedford Park, SA 5042 (Australia); Hayes, Jason P [MiniFAB, 1 Dalmore Drive, Caribbean Park, Scoresby VIC 3179 (Australia); Thissen, Helmut, E-mail: Nico.Voelcker@flinders.edu.a [CSIRO Molecular and Health Technologies, Bayview Avenue, Clayton VIC 3168 (Australia)

    2009-12-15

    The spatial control over biomolecule- and cell-surface interactions is of great interest to a broad range of biomedical applications, including sensors, implantable devices and cell microarrays. Microarrays in particular require precise spatial control and the formation of patterns with microscale features. Here, we have developed an approach specifically designed for transfected cell microarray (TCM) applications that allows microscale spatial control over the location of both DNA and cells on highly doped p-type silicon substrates. This was achieved by surface modification, involving plasma polymerization of allylamine, grafting of poly(ethylene glycol) and subsequent excimer laser ablation. DNA could be delivered in a spatially defined manner using ink-jet printing. In addition, electroporation was investigated as an approach to transfect attached cells with adsorbed DNA and good transfection efficiencies of approximately 20% were observed. The ability of the microstructured surfaces to spatially direct both DNA adsorption and cell attachment was demonstrated in a functional TCM, making this system an exciting platform for chip-based functional genomics.

  1. 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.

  2. 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

  3. 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

  4. 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.

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

    Science.gov (United States)

    Schumacher, Sarah; Muekusch, Sandra; Seitz, Harald

    2015-04-23

    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.

  6. Design issues in toxicogenomics using DNA microarray experiment

    International Nuclear Information System (INIS)

    The methods of toxicogenomics might be classified into omics study (e.g., genomics, proteomics, and metabolomics) and population study focusing on risk assessment and gene-environment interaction. In omics study, microarray is the most popular approach. Genes falling into several categories (e.g., xenobiotics metabolism, cell cycle control, DNA repair etc.) can be selected up to 20,000 according to a priori hypothesis. The appropriate type of samples and species should be selected in advance. Multiple doses and varied exposure durations are suggested to identify those genes clearly linked to toxic response. Microarray experiments can be affected by numerous nuisance variables including experimental designs, sample extraction, type of scanners, etc. The number of slides might be determined from the magnitude and variance of expression change, false-positive rate, and desired power. Instead, pooling samples is an alternative. Online databases on chemicals with known exposure-disease outcomes and genetic information can aid the interpretation of the normalized results. Gene function can be inferred from microarray data analyzed by bioinformatics methods such as cluster analysis. The population study often adopts hospital-based or nested case-control design. Biases in subject selection and exposure assessment should be minimized, and confounding bias should also be controlled for in stratified or multiple regression analysis. Optimal sample sizes are dependent on the statistical test for gene-to-environment or gene-to-gene interaction. The design issues addressed in this mini-review are crucial in conducting toxicogenomics study. In addition, integrative approach of exposure assessment, epidemiology, and clinical trial is required

  7. Quantitative Dose-Response Curves from Subcellular Lipid Multilayer Microarrays

    Science.gov (United States)

    Kusi-Appiah, A. E.; Lowry, T. W.; Darrow, E. M.; Wilson, K.; Chadwick, B. P.; Davidson, M. W.; Lenhert, S.

    2015-01-01

    The dose-dependent bioactivity of small molecules on cells is a crucial factor in drug discovery and personalized medicine. Although small-molecule microarrays are a promising platform for miniaturized screening, it has been a challenge to use them to obtain quantitative dose-response curves in vitro, especially for lipophilic compounds. Here we establish a small-molecule microarray assay capable of controlling the dosage of small lipophilic molecules delivered to cells by varying the sub-cellular volumes of surface supported lipid micro- and nanostructure arrays fabricated with nanointaglio. Features with sub-cellular lateral dimensions were found necessary to obtain normal cell adhesion with HeLa cells. The volumes of the lipophilic drug-containing nanostructures were determined using a fluorescence microscope calibrated by atomic-force microscopy. We used the surface supported lipid volume information to obtain EC-50 values for the response of HeLa cells to three FDA-approved lipophilic anticancer drugs, docetaxel, imiquimod and triethylenemelamine, which were found to be significantly different from neat lipid controls. No significant toxicity was observed on the control cells surrounding the drug/lipid patterns, indicating lack of interference or leakage from the arrays. Comparison of the microarray data to dose-response curves for the same drugs delivered liposomally from solution revealed quantitative differences in the efficacy values, which we explain in terms of cell-adhesion playing a more important role in the surface-based assay. The assay should be scalable to a density of at least 10,000 dose response curves on the area of a standard microtiter plate. PMID:26167949

  8. EXPANDER – an integrative program suite for microarray data analysis

    Directory of Open Access Journals (Sweden)

    Shiloh Yosef

    2005-09-01

    Full Text Available Abstract Background Gene expression microarrays are a prominent experimental tool in functional genomics which has opened the opportunity for gaining global, systems-level understanding of transcriptional networks. Experiments that apply this technology typically generate overwhelming volumes of data, unprecedented in biological research. Therefore the task of mining meaningful biological knowledge out of the raw data is a major challenge in bioinformatics. Of special need are integrative packages that provide biologist users with advanced but yet easy to use, set of algorithms, together covering the whole range of steps in microarray data analysis. Results Here we present the EXPANDER 2.0 (EXPression ANalyzer and DisplayER software package. EXPANDER 2.0 is an integrative package for the analysis of gene expression data, designed as a 'one-stop shop' tool that implements various data analysis algorithms ranging from the initial steps of normalization and filtering, through clustering and biclustering, to high-level functional enrichment analysis that points to biological processes that are active in the examined conditions, and to promoter cis-regulatory elements analysis that elucidates transcription factors that control the observed transcriptional response. EXPANDER is available with pre-compiled functional Gene Ontology (GO and promoter sequence-derived data files for yeast, worm, fly, rat, mouse and human, supporting high-level analysis applied to data obtained from these six organisms. Conclusion EXPANDER integrated capabilities and its built-in support of multiple organisms make it a very powerful tool for analysis of microarray data. The package is freely available for academic users at http://www.cs.tau.ac.il/~rshamir/expander

  9. 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.

  10. Determination of strongly overlapping signaling activity from microarray data

    Directory of Open Access Journals (Sweden)

    Bidaut Ghislain

    2006-02-01

    Full Text Available Abstract Background As numerous diseases involve errors in signal transduction, modern therapeutics often target proteins involved in cellular signaling. Interpretation of the activity of signaling pathways during disease development or therapeutic intervention would assist in drug development, design of therapy, and target identification. Microarrays provide a global measure of cellular response, however linking these responses to signaling pathways requires an analytic approach tuned to the underlying biology. An ongoing issue in pattern recognition in microarrays has been how to determine the number of patterns (or clusters to use for data interpretation, and this is a critical issue as measures of statistical significance in gene ontology or pathways rely on proper separation of genes into groups. Results Here we introduce a method relying on gene annotation coupled to decompositional analysis of global gene expression data that allows us to estimate specific activity on strongly coupled signaling pathways and, in some cases, activity of specific signaling proteins. We demonstrate the technique using the Rosetta yeast deletion mutant data set, decompositional analysis by Bayesian Decomposition, and annotation analysis using ClutrFree. We determined from measurements of gene persistence in patterns across multiple potential dimensionalities that 15 basis vectors provides the correct dimensionality for interpreting the data. Using gene ontology and data on gene regulation in the Saccharomyces Genome Database, we identified the transcriptional signatures of several cellular processes in yeast, including cell wall creation, ribosomal disruption, chemical blocking of protein synthesis, and, criticially, individual signatures of the strongly coupled mating and filamentation pathways. Conclusion This works demonstrates that microarray data can provide downstream indicators of pathway activity either through use of gene ontology or transcription

  11. Oligonucleotide microarray for subtyping of influenza A viruses

    Science.gov (United States)

    Klotchenko, S. A.; Vasin, A. V.; Sandybaev, N. T.; Plotnikova, M. A.; Chervyakova, O. V.; Smirnova, E. A.; Kushnareva, E. V.; Strochkov, V. M.; Taylakova, E. T.; Egorov, V. V.; Koshemetov, J. K.; Kiselev, O. I.; Sansyzbay, A. R.

    2012-02-01

    Influenza is one of the most widespread respiratory viral diseases, infecting humans, horses, pigs, poultry and some other animal populations. Influenza A viruses (IAV) are classified into subtypes on the basis of the surface hemagglutinin (H1 to H16) and neuraminidase (N1 to N9) glycoproteins. The correct determination of IAV subtype is necessary for clinical and epidemiological studies. In this article we propose an oligonucleotide microarray for subtyping of IAV using universal one-step multisegment RT-PCR fluorescent labeling of viral gene segments. It showed to be an advanced approach for fast detection and identification of IAV.

  12. Producing reverse phase protein microarrays from formalin-fixed tissues.

    Science.gov (United States)

    Wolff, Claudia; Schott, Christina; Malinowsky, Katharina; Berg, Daniela; Becker, Karl-Friedrich

    2011-01-01

    In most hospitals around the world FFPE (formalin fixed, paraffin embedded) tissues have been used for diagnosis and have subsequently been archived since decades. This has lead to a sizeable pool of this kind of tissues. Till quite recently it was not possible to use this congeries of samples for protein analysis, but now several groups described successful protein extraction from FFPE tissues. In this chapter, we describe a protein extraction protocol established in our laboratory combined with the use of reverse phase protein microarray.

  13. Dielectrophoretic Manipulation and Separation of Microparticles Using Microarray Dot Electrodes

    Directory of Open Access Journals (Sweden)

    Bashar Yafouz

    2014-04-01

    Full Text Available This paper introduces a dielectrophoretic system for the manipulation and separation of microparticles. The system is composed of five layers and utilizes microarray dot electrodes. We validated our system by conducting size-dependent manipulation and separation experiments on 1, 5 and 15 μm polystyrene particles. Our findings confirm the capability of the proposed device to rapidly and efficiently manipulate and separate microparticles of various dimensions, utilizing positive and negative dielectrophoresis (DEP effects. Larger size particles were repelled and concentrated in the center of the dot by negative DEP, while the smaller sizes were attracted and collected by the edge of the dot by positive DEP.

  14. GenePublisher: automated analysis of DNA microarray data

    DEFF Research Database (Denmark)

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

    2003-01-01

    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......, 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....

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

    DEFF Research Database (Denmark)

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

    2007-01-01

    A new hybrid magnetic bead separator that combines an external magnetic field with 175@mm 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....

  16. Two heuristic approaches to describe periodicities in genomic microarrays

    Directory of Open Access Journals (Sweden)

    Jörg Aßmus

    2009-09-01

    Full Text Available In the first part we discuss the filtering of panels of time series based on singular value decomposition. The discussion is based on an approach where this filtering is used to normalize microarray data. We point out effects on the periodicity and phases for time series panels. In the second part we investigate time dependent periodic panels with different phases. We align the time series in the panel and discuss the periodogram of the aligned time series with the purpose of describing the periodic structure of the panel. The method is quite powerful assuming known phases in the model, but it deteriorates rapidly for noisy data.  

  17. Oligonucleotide microarray for subtyping of influenza A viruses

    International Nuclear Information System (INIS)

    Influenza is one of the most widespread respiratory viral diseases, infecting humans, horses, pigs, poultry and some other animal populations. Influenza A viruses (IAV) are classified into subtypes on the basis of the surface hemagglutinin (H1 to H16) and neuraminidase (N1 to N9) glycoproteins. The correct determination of IAV subtype is necessary for clinical and epidemiological studies. In this article we propose an oligonucleotide microarray for subtyping of IAV using universal one-step multisegment RT-PCR fluorescent labeling of viral gene segments. It showed to be an advanced approach for fast detection and identification of IAV.

  18. Improving comparability between microarray probe signals by thermodynamic intensity correction

    DEFF Research Database (Denmark)

    Bruun, G. M.; Wernersson, Rasmus; Juncker, Agnieszka;

    2007-01-01

    different probes. It is therefore of great interest to correct for the variation between probes. Much of this variation is sequence dependent. We demonstrate that a thermodynamic model for hybridization of either DNA or RNA to a DNA microarray, which takes the sequence-dependent probe affinities...... determination of transcription start sites for a subset of yeast genes. In another application, we identify present/absent calls for probes hybridized to the sequenced Escherichia coli strain O157:H7 EDL933. The model improves the correct calls from 85 to 95% relative to raw intensity measures. The model thus...

  19. Low-Level and High-Level Microarray Data Analysis

    OpenAIRE

    Chen, Xin

    2010-01-01

    Microarray data analysis involves low-level and high-level analysis.The low-level analysis focuses on how to get accurate and precisegene expression data. The analysis built on gene expression data isthe high-level analysis such as differential gene expressionanalysis, SFP detection, eQTL analysis and so on. This thesisfocuses on applications in both low-level and high-level analysis.In the low-level analysis, the proposed L-GCRMA method combines theadvantage of the GCRMA model and the Langmu...

  20. Simulation and visualization of flow pattern in microarrays for liquid phase oligonucleotide and peptide synthesis.

    Science.gov (United States)

    O-Charoen, Sirimon; Srivannavit, Onnop; Gulari, Erdogan

    2007-01-01

    Microfluidic microarrays have been developed for economical and rapid parallel synthesis of oligonucleotide and peptide libraries. For a synthesis system to be reproducible and uniform, it is crucial to have a uniform reagent delivery throughout the system. Computational fluid dynamics (CFD) is used to model and simulate the microfluidic microarrays to study geometrical effects on flow patterns. By proper design geometry, flow uniformity could be obtained in every microreactor in the microarrays. PMID:17480053

  1. A visual analytics approach for understanding biclustering results from microarray data

    OpenAIRE

    Quintales Luis; Therón Roberto; Santamaría Rodrigo

    2008-01-01

    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 ...

  2. A Hybrid Multi Objective Particle Swarm Optimization Method to Discover Biclusters in Microarray Data

    OpenAIRE

    lashkargir, Mohsen; Monadjemi, S. Amirhassan; Dastjerdi, Ahmad Baraani

    2009-01-01

    In recent years, with the development of microarray technique, discovery of useful knowledge from microarray data has become very important. Biclustering is a very useful data mining technique for discovering genes which have similar behavior. In microarray data, several objectives have to be optimized simultaneously and often these objectives are in conflict with each other. A Multi Objective model is capable of solving such problems. Our method proposes a Hybrid algorithm which is based on ...

  3. Identification of Novel Epithelial Ovarian Cancer Biomarkers by Cross-laboratory Microarray Analysis

    Institute of Scientific and Technical Information of China (English)

    蒋学锋; 朱涛; 杨洁; 李双; 叶双梅; 廖书杰; 孟力; 卢运萍; 马丁

    2010-01-01

    The purpose of this study was to pool information in epithelial ovarian cancer by combining studies using Affymetrix expression microarray datasets made at different laboratories to identify novel biomarkers.Epithelial microarray expression information across laboratories was screened and combined after preprocessing raw microarray data,then ANOVA and unpaired T test statistical analysis was performed for identifying differentially expressed genes(DEGs),followed by clustering and pathway analysis for these ...

  4. Microarray Technology for Major Chemical Contaminants Analysis in Food: Current Status and Prospects

    OpenAIRE

    Xiaoxia Ding; Wen Zhang; Xiaofeng Hu; Qi Zhang; Peiwu Li; Zhaowei Zhang

    2012-01-01

    Chemical contaminants in food have caused serious health issues in both humans and animals. Microarray technology is an advanced technique suitable for the analysis of chemical contaminates. In particular, immuno-microarray approach is one of the most promising methods for chemical contaminants analysis. The use of microarrays for the analysis of chemical contaminants is the subject of this review. Fabrication strategies and detection methods for chemical contaminants are discussed in detail....

  5. Are Gene Expression Microarray Analyses Reliable? A Review of Studies of Retinoic Acid Responsive Genes

    Institute of Scientific and Technical Information of China (English)

    Peter J. van der Spek; Andreas Kremer; Lynn Murry; Michael G. Walker

    2003-01-01

    Microarray analyses of gene expression are widely used, but reports of the same analyses by different groups give widely divergent results, and raise questions regarding reproducibility and reliability. We take as an example recent published reports on microarray experiments that were designed to identify retinoic acid responsive genes. These reports show substantial differences in their results. In this article, we review the methodology, results, and potential causes of differences in these applications of microarrays. Finally, we suggest practices to improve the reliability and reproducibility of microarray experiments.

  6. Robust protein microarray image segmentation using improved seeded region growing algorithm

    Institute of Scientific and Technical Information of China (English)

    Liqiang Wang(王立强); Xuxiang Ni(倪旭翔); Zukang Lu(陆祖康)

    2003-01-01

    Protein microarray technology has recently emerged as a powerful tool for biomedical research. Before automatic analysis the protein microarray images, protein spots in the images must be determined appropriately by spot segmentation algorithm. In this paper, an improved seeded region growing (ISRG)algorithm for protein microarray segmentation is presented, the seeds are obtained by finding the positions of the printed spots, and the protein spot regions are grown through these seeds. The experiment results show that the presented algorithm is accurate for adaptive shape segmentation and robust for protein microarray images contaminated by noise.

  7. Are Gene Expression Microarray Analyses Reliable? A Review of Studies of Retinoic Acid Responsive Genes

    Institute of Scientific and Technical Information of China (English)

    PeterJ.vanderSpek; AndreasKremer; LynnMurry; MichaelG.Walker

    2003-01-01

    Microarray analyses of gene expression are widely used,but reports of the same analyses by different groups give widely divergent results,and raise questions regarding reproducibility and reliability.We take as an example recent published reports on microarray experiments that were designed to identify retinoic acid responsive genes.These reports show substantial differences in their results.In this article,we review the methodology,results,and potential causes of differences in these applications of microarrays.Finally,we suggest practices to improve the reliability and reproducibility of microarray experiments.

  8. RiceDB: A Web-Based Integrated Database for Annotating Rice Microarray

    Institute of Scientific and Technical Information of China (English)

    HE Fei; SHI Qing-yun; CHEN Ming; WU Ping

    2007-01-01

    RiceDB, a web-based integrated database to annotate rice microarray in various biological contexts was developed. It is composed of eight modules. RiceMap module archives the process of Affymetrix probe sets mapping to different databases about rice, and aims to the genes represented by a microarray set by retrieving annotation information via the identifier or accession number of every database; RiceGO module indicates the association between a microarray set and gene ontology (GO) categories; RiceKO module is used to annotate a microarray set based on the KEGG biochemical pathways; RiceDO module indicates the information of domain associated with a microarray set; RiceUP module is used to obtain promoter sequences for all genes represented by a microarray set; RiceMR module lists potential microRNA which regulated the genes represented by a microarray set; RiceCD and RiceGF are used to annotate the genes represented by a microarray set in the context of chromosome distribution and rice paralogous family distribution. The results of automatic annotation are mostly consistent with manual annotation. Biological interpretation of the microarray data is quickened by the help of RiceDB.

  9. Microarray gene expression profiling and analysis in renal cell carcinoma

    Directory of Open Access Journals (Sweden)

    Sadhukhan Provash

    2004-06-01

    Full Text Available Abstract Background Renal cell carcinoma (RCC is the most common cancer in adult kidney. The accuracy of current diagnosis and prognosis of the disease and the effectiveness of the treatment for the disease are limited by the poor understanding of the disease at the molecular level. To better understand the genetics and biology of RCC, we profiled the expression of 7,129 genes in both clear cell RCC tissue and cell lines using oligonucleotide arrays. Methods Total RNAs isolated from renal cell tumors, adjacent normal tissue and metastatic RCC cell lines were hybridized to affymatrix HuFL oligonucleotide arrays. Genes were categorized into different functional groups based on the description of the Gene Ontology Consortium and analyzed based on the gene expression levels. Gene expression profiles of the tissue and cell line samples were visualized and classified by singular value decomposition. Reverse transcription polymerase chain reaction was performed to confirm the expression alterations of selected genes in RCC. Results Selected genes were annotated based on biological processes and clustered into functional groups. The expression levels of genes in each group were also analyzed. Seventy-four commonly differentially expressed genes with more than five-fold changes in RCC tissues were identified. The expression alterations of selected genes from these seventy-four genes were further verified using reverse transcription polymerase chain reaction (RT-PCR. Detailed comparison of gene expression patterns in RCC tissue and RCC cell lines shows significant differences between the two types of samples, but many important expression patterns were preserved. Conclusions This is one of the initial studies that examine the functional ontology of a large number of genes in RCC. Extensive annotation, clustering and analysis of a large number of genes based on the gene functional ontology revealed many interesting gene expression patterns in RCC. Most

  10. Single-Round Patterned DNA Library Microarray Aptamer Lead Identification

    Directory of Open Access Journals (Sweden)

    Jennifer A. Martin

    2015-01-01

    Full Text Available A method for identifying an aptamer in a single round was developed using custom DNA microarrays containing computationally derived patterned libraries incorporating no information on the sequences of previously reported thrombin binding aptamers. The DNA library was specifically designed to increase the probability of binding by enhancing structural complexity in a sequence-space confined environment, much like generating lead compounds in a combinatorial drug screening library. The sequence demonstrating the highest fluorescence intensity upon target addition was confirmed to bind the target molecule thrombin with specificity by surface plasmon resonance, and a novel imino proton NMR/2D NOESY combination was used to screen the structure for G-quartet formation. We propose that the lack of G-quartet structure in microarray-derived aptamers may highlight differences in binding mechanisms between surface-immobilized and solution based strategies. This proof-of-principle study highlights the use of a computational driven methodology to create a DNA library rather than a SELEX based approach. This work is beneficial to the biosensor field where aptamers selected by solution based evolution have proven challenging to retain binding function when immobilized on a surface.

  11. Feature extraction and signal processing for nylon DNA microarrays

    Directory of Open Access Journals (Sweden)

    Bertucci F

    2004-06-01

    Full Text Available Abstract Background High-density DNA microarrays require automatic feature extraction methodologies and softwares. These can be a potential source of non-reproducibility of gene expression measurements. Variation in feature location or in signal integration methodology may be a significant contribution to the observed variance in gene expression levels. Results We explore sources of variability in feature extraction from DNA microarrays on Nylon membrane with radioactive detection. We introduce a mathematical model of the signal emission and derive methods for correcting biases such as overshining, saturation or variation in probe amount. We also provide a quality metric which can be used qualitatively to flag weak or untrusted signals or quantitatively to modulate the weight of each experiment or gene in higher level analyses (clustering or discriminant analysis. Conclusions Our novel feature extraction methodology, based on a mathematical model of the radioactive emission, reduces variability due to saturation, neighbourhood effects and variable probe amount. Furthermore, we provide a fully automatic feature extraction software, BZScan, which implements the algorithms described in this paper.

  12. Screening for C3 deficiency in newborns using microarrays.

    Directory of Open Access Journals (Sweden)

    Magdalena Janzi

    Full Text Available BACKGROUND: Dried blood spot samples (DBSS from newborns are widely used in neonatal screening for selected metabolic diseases and diagnostic possibilities for additional disorders are continuously being evaluated. Primary immunodeficiency disorders comprise a group of more than one hundred diseases, several of which are fatal early in life. Yet, a majority of the patients are not diagnosed due to lack of high-throughput screening methods. METHODOLOGY/PRINCIPAL FINDINGS: We have previously developed a system using reverse phase protein microarrays for analysis of IgA levels in serum samples. In this study, we extended the applicability of the method to include determination of complement component C3 levels in eluates from DBSS collected at birth. Normal levels of C3 were readily detected in 269 DBSS from healthy newborns, while no C3 was detected in sera and DBSS from C3 deficient patients. CONCLUSIONS/SIGNIFICANCE: The findings suggest that patients with deficiencies of specific serum proteins can be identified by analysis of DBSS using reverse phase protein microarrays.

  13. Quantum Dots-based Reverse Phase Protein Microarray

    Energy Technology Data Exchange (ETDEWEB)

    Shingyoji, Masato; Gerion, Daniele; Pinkel, Dan; Gray, Joe W.; Chen, Fanqing

    2005-07-15

    CdSe nanocrystals, also called quantum dots (Qdots) are a novel class of fluorophores, which have a diameter of a few nanometers and possess high quantum yield, tunable emission wavelength and photostability. They are an attractive alternative to conventional fluorescent dyes. Quantum dots can be silanized to be soluble in aqueous solution under biological conditions, and thus be used in bio-detection. In this study, we established a novel Qdot-based technology platform that can perform accurate and reproducible quantification of protein concentration in a crude cell lysate background. Protein lysates have been spiked with a target protein, and a dilution series of the cell lysate with a dynamic range of three orders of magnitude has been used for this proof-of-concept study. The dilution series has been spotted in microarray format, and protein detection has been achieved with a sensitivity that is at least comparable to standard commercial assays, which are based on horseradish peroxidase (HRP) catalyzed diaminobenzidine (DAB) chromogenesis. The data obtained through the Qdot method has shown a close linear correlation between relative fluorescence unit and relative protein concentration. The Qdot results are in almost complete agreement with data we obtained with the well-established HRP-DAB colorimetric array (R{sup 2} = 0.986). This suggests that Qdots can be used for protein quantification in microarray format, using the platform presented here.

  14. 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.

  15. Gene expression profiling in peanut using high density oligonucleotide microarrays

    Directory of Open Access Journals (Sweden)

    Burow Mark

    2009-06-01

    Full Text Available Abstract Background Transcriptome expression analysis in peanut to date has been limited to a relatively small set of genes and only recently has a significant number of ESTs been released into the public domain. Utilization of these ESTs for oligonucleotide microarrays provides a means to investigate large-scale transcript responses to a variety of developmental and environmental signals, ultimately improving our understanding of plant biology. Results We have developed a high-density oligonucleotide microarray for peanut using 49,205 publicly available ESTs and tested the utility of this array for expression profiling in a variety of peanut tissues. To identify putatively tissue-specific genes and demonstrate the utility of this array for expression profiling in a variety of peanut tissues, we compared transcript levels in pod, peg, leaf, stem, and root tissues. Results from this experiment showed 108 putatively pod-specific/abundant genes, as well as transcripts whose expression was low or undetected in pod compared to peg, leaf, stem, or root. The transcripts significantly over-represented in pod include genes responsible for seed storage proteins and desiccation (e.g., late-embryogenesis abundant proteins, aquaporins, legumin B, oil production, and cellular defense. Additionally, almost half of the pod-abundant genes represent unknown genes allowing for the possibility of associating putative function to these previously uncharacterized genes. Conclusion The peanut oligonucleotide array represents the majority of publicly available peanut ESTs and can be used as a tool for expression profiling studies in diverse tissues.

  16. Classification of microarray data with penalized logistic regression

    Science.gov (United States)

    Eilers, Paul H. C.; Boer, Judith M.; van Ommen, Gert-Jan; van Houwelingen, Hans C.

    2001-06-01

    Classification of microarray data needs a firm statistical basis. In principle, logistic regression can provide it, modeling the probability of membership of a class with (transforms of) linear combinations of explanatory variables. However, classical logistic regression does not work for microarrays, because generally there will be far more variables than observations. One problem is multicollinearity: estimating equations become singular and have no unique and stable solution. A second problem is over-fitting: a model may fit well into a data set, but perform badly when used to classify new data. We propose penalized likelihood as a solution to both problems. The values of the regression coefficients are constrained in a similar way as in ridge regression. All variables play an equal role, there is no ad-hoc selection of most relevant or most expressed genes. The dimension of the resulting systems of equations is equal to the number of variables, and generally will be too large for most computers, but it can dramatically be reduced with the singular value decomposition of some matrices. The penalty is optimized with AIC (Akaike's Information Criterion), which essentially is a measure of prediction performance. We find that penalized logistic regression performs well on a public data set (the MIT ALL/AML data).

  17. Extraction of Spots in DNA Microarrays Using Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    A. Sreedevi

    2013-12-01

    Full Text Available DNA microarray technology is an eminent tool for ge nomic studies. Accurate extraction of spots is a crucial issue since biological interpretations depe nd on it. The image analysis starts with the format ion of grid, which is a laborious process requiring human intervention. This paper presents a method for opti mal search of the spots using genetic algorithm without formation of grid. The information of every spot i s extracted by obtaining a pixel belonging to that sp ot. The method developed selects pixels of high int ensity in the image, thereby spot is recognized. The objec tive function, which is implemented, helps in ident ifying the exact pixel. The algorithm is applied to differ ent sizes of sub images and features of the spots a re obtained. It is found that there is a tradeoff betw een accuracy in the number of spots identified and time required for processing the image. Segmentation pro cess is independent of shape, size and location of the spots. Background estimation is one step process as both foreground and complete spot are realized. Coding of the proposed algorithm is developed in MA TLAB-7 and applied to cDNA microarray images. This approach provides reliable results for identif ication of even low intensity spots and elimination of spurious spots.

  18. 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.

  19. Microbial forensics: fiber optic microarray subtyping of Bacillus anthracis

    Science.gov (United States)

    Shepard, Jason R. E.

    2009-05-01

    The past decade has seen increased development and subsequent adoption of rapid molecular techniques involving DNA analysis for detection of pathogenic microorganisms, also termed microbial forensics. The continued accumulation of microbial sequence information in genomic databases now better positions the field of high-throughput DNA analysis to proceed in a more manageable fashion. The potential to build off of these databases exists as technology continues to develop, which will enable more rapid, cost effective analyses. This wealth of genetic information, along with new technologies, has the potential to better address some of the current problems and solve the key issues involved in DNA analysis of pathogenic microorganisms. To this end, a high density fiber optic microarray has been employed, housing numerous DNA sequences simultaneously for detection of various pathogenic microorganisms, including Bacillus anthracis, among others. Each organism is analyzed with multiple sequences and can be sub-typed against other closely related organisms. For public health labs, real-time PCR methods have been developed as an initial preliminary screen, but culture and growth are still considered the gold standard. Technologies employing higher throughput than these standard methods are better suited to capitalize on the limitless potential garnered from the sequence information. Microarray analyses are one such format positioned to exploit this potential, and our array platform is reusable, allowing repetitive tests on a single array, providing an increase in throughput and decrease in cost, along with a certainty of detection, down to the individual strain level.

  20. 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.

  1. Rank-based algorithms for anlaysis of microarrays

    Science.gov (United States)

    Liu, Wei-min; Mei, Rui; Bartell, Daniel M.; Di, Xiaojun; Webster, Teresa A.; Ryder, Tom

    2001-06-01

    Analysis of microarray data often involves extracting information from raw intensities of spots of cells and making certain calls. Rank-based algorithms are powerful tools to provide probability values of hypothesis tests, especially when the distribution of the intensities is unknown. For our current gene expression arrays, a gene is detected by a set of probe pairs consisting of perfect match and mismatch cells. The one-sided upper-tail Wilcoxon's signed rank test is used in our algorithms for absolute calls (whether a gene is detected or not), as well as comparative calls (whether a gene is increasing or decreasing or no significant change in a sample compared with another sample). We also test the possibility to use only perfect match cells to make calls. This paper focuses on absolute calls. We have developed error analysis methods and software tools that allow us to compare the accuracy of the calls in the presence or absence of mismatch cells at different target concentrations. The usage of nonparametric rank-based tests is not limited to absolute and comparative calls of gene expression chips. They can also be applied to other oligonucleotide microarrays for genotyping and mutation detection, as well as spotted arrays.

  2. Multiplex component-based allergen microarray in recent clinical studies.

    Science.gov (United States)

    Patelis, A; Borres, M P; Kober, A; Berthold, M

    2016-08-01

    During the last decades component-resolved diagnostics either as singleplex or multiplex measurements has been introduced into the field of clinical allergology, providing important information that cannot be obtained from extract-based tests. Here we review recent studies that demonstrate clinical applications of the multiplex microarray technique in the diagnosis and risk assessment of allergic patients, and its usefulness in studies of allergic diseases. The usefulness of ImmunoCAP ISAC has been validated in a wide spectrum of allergic diseases like asthma, allergic rhinoconjunctivitis, atopic dermatitis, eosinophilic esophagitis, food allergy and anaphylaxis. ISAC provides a broad picture of a patient's sensitization profile from a single test, and provides information on specific and cross-reactive sensitizations that facilitate diagnosis, risk assessment, and disease management. Furthermore, it can reveal unexpected sensitizations which may explain anaphylaxis previously categorized as idiopathic and also display for the moment clinically non-relevant sensitizations. ISAC can facilitate a better selection of relevant allergens for immunotherapy compared with extract testing. Microarray technique can visualize the allergic march and molecular spreading in the preclinical stages of allergic diseases, and may indicate that the likelihood of developing symptomatic allergy is associated with specific profiles of sensitization to allergen components. ISAC is shown to be a useful tool in routine allergy diagnostics due to its ability to improve risk assessment, to better select relevant allergens for immunotherapy as well as detecting unknown sensitization. Multiplex component testing is especially suitable for patients with complex symptomatology. PMID:27196983

  3. 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.

  4. Human genomics and microarrays: implications for the plastic surgeon.

    Science.gov (United States)

    Cole, Jana; Isik, Frank

    2002-09-01

    The Human Genome Project was launched in 1989 in an effort to sequence the entire span of human DNA. Although coding sequences are important in identifying mutations, the static order of DNA does not explain how a cell or organism may respond to normal and abnormal biological processes. By examining the mRNA content of a cell, researchers can determine which genes are being activated in response to a stimulus. Traditional methods in molecular biology generally work on a "one gene: one experiment" basis, which means that the throughput is very limited and the "whole picture" of gene function is hard to obtain. To study each of the 60,000 to 80,000 genes in the human genome under each biological circumstance is not practical. Recently, microarrays (also known as gene or DNA chips) have emerged; these allow for the simultaneous determination of expression for thousands of genes and analysis of genome-wide mRNA expression. The purpose of this article is twofold: first, to provide the clinical plastic surgeon with a working knowledge and understanding of the fields of genomics, microarrays, and bioinformatics and second, to present a case to illustrate how these technologies can be applied in the study of wound healing.

  5. Characterization of adjacent breast tumors using oligonucleotide microarrays

    International Nuclear Information System (INIS)

    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

  6. 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.

  7. 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.

  8. Cluster stability scores for microarray data in cancer studies

    Directory of Open Access Journals (Sweden)

    Ghosh Debashis

    2003-09-01

    Full Text Available Abstract Background A potential benefit of profiling of tissue samples using microarrays is the generation of molecular fingerprints that will define subtypes of disease. Hierarchical clustering has been the primary analytical tool used to define disease subtypes from microarray experiments in cancer settings. Assessing cluster reliability poses a major complication in analyzing output from clustering procedures. While most work has focused on estimating the number of clusters in a dataset, the question of stability of individual-level clusters has not been addressed. Results We address this problem by developing cluster stability scores using subsampling techniques. These scores exploit the redundancy in biologically discriminatory information on the chip. Our approach is generic and can be used with any clustering method. We propose procedures for calculating cluster stability scores for situations involving both known and unknown numbers of clusters. We also develop cluster-size adjusted stability scores. The method is illustrated by application to data three cancer studies; one involving childhood cancers, the second involving B-cell lymphoma, and the final is from a malignant melanoma study. Availability Code implementing the proposed analytic method can be obtained at the second author's website.

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

    Science.gov (United States)

    Tchagang, Alain B.; Tewfik, Ahmed H.

    2006-12-01

    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.

  10. 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

  11. 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

  12. 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

  13. 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

  14. A microarray screen for novel candidate genes in coeliac disease pathogenesis

    NARCIS (Netherlands)

    Diosdado, B; Wapenaar, MC; Franke, L; Duran, KJ; Goerres, MJ; Hadithi, M; Crusius, JBA; Meijer, JWR; Duggan, DJ; Mulder, CJJ; Holstege, FCP; Wijmenga, C

    2004-01-01

    Background and aims: The causative molecular pathways underlying the pathogenesis of coeliac disease are poorly understood. To unravel novel aspects of disease pathogenesis, we used microarrays to determine changes in gene expression of duodenal biopsies. Methods: cDNA microarrays representing 19 20

  15. A microarray screen for novel candidate genes in coeliac disease pathogenesis.

    NARCIS (Netherlands)

    Diosdado, B; Wapenaar, MC; Franke, L; Duran, KJ; Goerres, MJ; Hadithi, M. al; Crusius, J.B.A.; Meijer, JW; Duggan, DJ; Mulder, C.J.J.; Holstege, FC; Wijmenga, C.

    2004-01-01

    BACKGROUND AND AIMS: The causative molecular pathways underlying the pathogenesis of coeliac disease are poorly understood. To unravel novel aspects of disease pathogenesis, we used microarrays to determine changes in gene expression of duodenal biopsies. METHODS: cDNA microarrays representing 19 20

  16. Differential and correlation analyses of microarray gene expression data in the CEPH Utah families

    DEFF Research Database (Denmark)

    Tan, Qihua; Zhao, Jinghua; Li, Shuxia;

    2008-01-01

    The widespread microarray technology capable of analyzing global gene expression at the level of transcription is expanding its application not only in medicine but also in studies on basic biology. This paper presents our analysis on microarray gene expression data in the CEPH Utah families...

  17. Can subtle changes in gene expression be consistently detected with different microarray platforms?

    NARCIS (Netherlands)

    P. Pedotti; P.A.C. 't Hoen (Peter); E. Vreugdenhil (Erno); G.J. Schenk (Geert); R. Vossen (Rolf); Y. Ariyurek (Yavuz); M. de Hollander (Mattias); R. Kuiper (Rowan); G.J. van Ommen (Gert); J.T. den Dunnen (Johan); J.M. Boer (Judith); R.X. de Menezes (Renee)

    2008-01-01

    textabstractBackground: The comparability of gene expression data generated with different microarray platforms is still a matter of concern. Here we address the performance and the overlap in the detection of differentially expressed genes for five different microarray platforms in a challenging bi

  18. Jetset: selecting the optimal microarray probe set to represent a gene

    DEFF Research Database (Denmark)

    Li, Qiyuan; Birkbak, Nicolai Juul; Gyorffy, Balazs;

    2011-01-01

    Background: Interpretation of gene expression microarrays requires a mapping from probe set to gene. On many Affymetrix gene expression microarrays, a given gene may be detected by multiple probe sets, which may deliver inconsistent or even contradictory measurements. Therefore, obtaining an unam...

  19. Is there an alternative to increasing the sample size in microarray studies?

    OpenAIRE

    Klebanov, Lev; Yakovlev, Andrei

    2007-01-01

    Our answer to the question posed in the title is negative. This intentionally provocative note discusses the issue of sample size in microarray studies from several angles. We suggest that the current view of microarrays as no more than a screening tool be changed and small sample studies no longer be considered appropriate.

  20. Fabrication of oligonucleotide microarray for the detection of Japanese encephalitis virus

    Institute of Scientific and Technical Information of China (English)

    HAI YAN ZHANG; WEN LI MA; XIAO MING ZHANG; WEN LING ZHENG

    2006-01-01

    A low-density oligonucleotide microarray was used for the detection of Japanese encephalitis virus (JEV), combining with restriction display PCR labeling method. The hybridization targets were amplified from 6 plasmids containing several JEV gene fragments. Corresponding oligonucleotide probe spots were detected unambiguously. We claim that the oligonucleotide microarray technology is feasible and may have potential for clinical laboratory application.

  1. 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

  2. Individual variation of adipose gene expression and identification of covariated genes by cDNA microarrays

    NARCIS (Netherlands)

    Boeuf, S.; Keijer, J.; Franssen-Hal, van N.L.W.; Klaus, S.

    2002-01-01

    Gene expression profiling through the application of microarrays provides comprehensive assessment of gene expression levels in a given tissue or cell population, as well as information on changes of gene expression in altered physiological or pathological situations. Microarrays are particularly su

  3. 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 ...

  4. 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

    building arrays, because they combine high sample throughput with investigation of optimal assay conditions. The array processors can increase specificity in all DNA microarray assays, e.g. for gene expression, and microRNA and mutation analysis. Increased specificity of the array will also benefit...... microarray-based loci selection prior to high-throughput sequencing....

  5. Interim report on updated microarray probes for the LLNL Burkholderia pseudomallei SNP array

    Energy Technology Data Exchange (ETDEWEB)

    Gardner, S; Jaing, C

    2012-03-27

    The overall goal of this project is to forensically characterize 100 unknown Burkholderia isolates in the US-Australia collaboration. We will identify genome-wide single nucleotide polymorphisms (SNPs) from B. pseudomallei and near neighbor species including B. mallei, B. thailandensis and B. oklahomensis. We will design microarray probes to detect these SNP markers and analyze 100 Burkholderia genomic DNAs extracted from environmental, clinical and near neighbor isolates from Australian collaborators on the Burkholderia SNP microarray. We will analyze the microarray genotyping results to characterize the genetic diversity of these new isolates and triage the samples for whole genome sequencing. In this interim report, we described the SNP analysis and the microarray probe design for the Burkholderia SNP microarray.

  6. Exploring the feasibility of next-generation sequencing and microarray data meta-analysis

    Science.gov (United States)

    Wu, Po-Yen; Phan, John H.; Wang, May D.

    2016-01-01

    Emerging next-generation sequencing (NGS) technology potentially resolves many issues that prevent widespread clinical use of gene expression microarrays. However, the number of publicly available NGS datasets is still smaller than that of microarrays. This paper explores the possibilities for combining information from both microarray and NGS gene expression datasets for the discovery of differentially expressed genes (DEGs). We evaluate several existing methods in detecting DEGs using individual datasets as well as combined NGS and microarray datasets. Results indicate that analysis of combined NGS and microarray data is feasible, but successful detection of DEGs may depend on careful selection of algorithms as well as on data normalization and pre-processing. PMID:22256102

  7. A Pathway Analysis Tool for Analyzing Microarray Data of Species with Low Physiological Information

    Directory of Open Access Journals (Sweden)

    M. A. Smits

    2008-12-01

    Full Text Available Pathway information provides insight into the biological processes underlying microarray data. Pathway information is widely available for humans and laboratory animals in databases through the internet, but less for other species, for example, livestock. Many software packages use species-specific gene IDs that cannot handle genomics data from other species. We developed a species-independent method to search pathways databases to analyse microarray data. Three PERL scripts were developed that use the names of the genes on the microarray. (1 Add synonyms of gene names by searching the Gene Ontology (GO database. (2 Search the Kyoto Encyclopaedia of Genes and Genomes (KEGG database for pathway information using this GO-enriched gene list. (3 Combine the pathway data with the microarray data and visualize the results using color codes indicating regulation. To demonstrate the power of the method, we used a previously reported chicken microarray experiment investigating line-specific reactions to Salmonella infection as an example.

  8. Noise Removal From Microarray Images Using Maximum a Posteriori Based Bivariate Estimator

    Directory of Open Access Journals (Sweden)

    A.Sharmila Agnal

    2013-01-01

    Full Text Available Microarray Image contains information about thousands of genes in an organism and these images are affected by several types of noises. They affect the circular edges of spots and thus degrade the image quality. Hence noise removal is the first step of cDNA microarray image analysis for obtaining gene expression level and identifying the infected cells. The Dual Tree Complex Wavelet Transform (DT-CWT is preferred for denoising microarray images due to its properties like improved directional selectivity and near shift-invariance. In this paper, bivariate estimators namely Linear Minimum Mean Squared Error (LMMSE and Maximum A Posteriori (MAP derived by applying DT-CWT are used for denoising microarray images. Experimental results show that MAP based denoising method outperforms existing denoising techniques for microarray images.

  9. Graph-driven features extraction from microarray data

    CERN Document Server

    Vert, J P; Vert, Jean-Philippe; Kanehisa, Minoru

    2002-01-01

    Gene function prediction from microarray data is a first step toward better understanding the machinery of the cell from relatively cheap and easy-to-produce data. In this paper we investigate whether the knowledge of many metabolic pathways and their catalyzing enzymes accumulated over the years can help improve the performance of classifiers for this problem. The complex network of known biochemical reactions in the cell results in a representation where genes are nodes of a graph. Formulating the problem as a graph-driven features extraction problem, based on the simple idea that relevant features are likely to exhibit correlation with respect to the topology of the graph, we end up with an algorithm which involves encoding the network and the set of expression profiles into kernel functions, and performing a regularized form of canonical correlation analysis in the corresponding reproducible kernel Hilbert spaces. Function prediction experiments for the genes of the yeast S. Cerevisiae validate this appro...

  10. Visualization of Growth Curve Data from Phenotype MicroarrayExperiments

    Energy Technology Data Exchange (ETDEWEB)

    Jacobsen, Janet S.; Joyner, Dominique C.; Borglin, Sharon E.; Hazen, Terry C.; Arkin, Adam P.; Bethel, E. Wes

    2007-04-19

    Phenotype microarrays provide a technology to simultaneouslysurvey the response of an organism to nearly 2,000 substrates, includingcarbon, nitrogen and potassium sources; varying pH; varying saltconcentrations; and antibiotics. In order to more quickly and easily viewand compare the large number of growth curves produced by phenotypemicroarray experiments, we have developed software to produce and displaycolor images, each of which corresponds to a set of 96 growth curves.Using color images to represent growth curves data has proven to be avaluable way to assess experiment quality, compare replicates, facilitatecomparison of the responses of different organisms, and identifysignificant phenotypes. The color images are linked to traditional plotsof growth versus time, as well as to information about the experiment,organism, and substrate. In order to share and view information and dataproject-wide, all information, plots, and data are accessible using onlya Web browser.

  11. 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...... at the same time according to a loading protocol generated by the user. Biotinylated deoxyribonucleic acid (DNA) is directed to the pad(s) via the electronic field(s) and bound to streptavidin in the hydrogel layer. Subsequently, fluorescently labeled reporter oligos and a stabilizer oligo are hybridized...... to the bound DNA. Base stacking between the short reporter and the longer stabilizer oligo stabilizes the binding of a matching reporter, whereas the binding of a reporter carrying a mismatch in the SNP position will be relatively weak. Thermal stringency is applied to the NanoChip array according to a reader...

  12. A COMPARATIVE STUDY OF CLUSTERING AND BICLUSTERING OF MICROARRAY DATA

    Directory of Open Access Journals (Sweden)

    Haifa Ben Saber

    2014-12-01

    Full Text Available There are subsets of genes that have similar behavior under subsets of conditions, so we say that they coexpress, but behave independently under other subsets of conditions. Discovering such coexpressions can be helpful to uncover genomic knowledge such as gene networks or gene interactions. That is why, it is of utmost importance to make a simultaneous clustering of genes and conditions to identify clusters of genes that are coexpressed under clusters of conditions. This type of clustering is called biclustering. Biclustering is an NP-hard problem. Consequently, heuristic algorithms are typically used to approximate this problem by finding suboptimal solutions. In this paper, we make a new survey on clustering and biclustering of gene expression data, also called microarray data.

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

    DEFF Research Database (Denmark)

    Li, Lei; Wang, Xiangfeng; Stolc, Viktor;

    2006-01-01

    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....... 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...... 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...

  14. Microarray tools to unveil viral-microbe interactions in nature

    Directory of Open Access Journals (Sweden)

    Fernando eSantos

    2014-07-01

    Full Text Available The interactions between viruses and their microbial hosts play a central role in the control of microbial communities in nature. However, the study of such interactions within the uncultured majority is technically very challenging. Here, we review how microarray tools can be used to analyze the interactions between viruses and their microbial hosts in nature, away from laboratory pure culture-based models. We show examples of how DNA arrays have been used to study the expression of viral assemblages in natural samples, and to assign viruses to hosts within uncultured communities. Finally, we briefly discuss the possibilities of protein and glycan arrays to gain insight into the ways microbes interact with their viruses.

  15. Straightforward protein immobilization on Sylgard 184 PDMS microarray surface.

    Science.gov (United States)

    Heyries, Kevin A; Marquette, Christophe A; Blum, Loïc J

    2007-04-10

    In this work, a straightforward technique for protein immobilization on Sylgard 184 is described. The method consists of a direct transfer of dried protein/salt solutions to the PDMS interface during the polymer curing. Such non-conventional treatment of proteins was found to have no major negative consequence on their integrity. The mechanisms of this direct immobilization were investigated using a lysine modified dextran molecule as a model. Clear experimental results suggested that both chemical bounding and molding effect were implicated. As a proof of concept study, three different proteins were immobilized on a single microarray (Arachis hypogaea lectin, rabbit IgG, and human IgG) and used as antigens for capture of chemiluminescent immunoassays. The proteins were shown to be easily recognized by their specific antibodies, giving antibody detection limits in the fmol range.

  16. A review of statistical methods for preprocessing oligonucleotide microarrays.

    Science.gov (United States)

    Wu, Zhijin

    2009-12-01

    Microarrays have become an indispensable tool in biomedical research. This powerful technology not only makes it possible to quantify a large number of nucleic acid molecules simultaneously, but also produces data with many sources of noise. A number of preprocessing steps are therefore necessary to convert the raw data, usually in the form of hybridisation images, to measures of biological meaning that can be used in further statistical analysis. Preprocessing of oligonucleotide arrays includes image processing, background adjustment, data normalisation/transformation and sometimes summarisation when multiple probes are used to target one genomic unit. In this article, we review the issues encountered in each preprocessing step and introduce the statistical models and methods in preprocessing.

  17. A NEW SURVEY ON BICLUSTERING OF MICROARRAY DATA

    Directory of Open Access Journals (Sweden)

    Haifa Ben Saber

    2014-12-01

    Full Text Available There are subsets of genes that have similar behavior under subsets of conditions, so we say that they coexpress, but behave independently under other subsets of conditions. Discovering such coexpressions can be helpful to uncover genomic knowledge such as gene networks or gene interactions. That is why, it is of utmost importance to make a simultaneous clustering of genes and conditions to identify clusters of genes that are coexpressed under clusters of conditions. This type of clustering is called biclustering. Biclustering is an NP-hard problem. Consequently, heuristic algorithms are typically used to approximate this problem by finding suboptimal solutions. In this paper, we make a new survey on biclustering of gene expression data, also called microarray data.

  18. Rhodamine B doped silica nanoparticle labels for protein microarray detection

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    A core-shell Rhodamine B-doped SiO2 nanoparticle was synthesized and its fluorescent intensity was found to be 1000 times higher than that of individual Rhodamine B molecule. The doped nanoparticles were further conjugated with streptavidin and the resulting nanoparticles were used in the detection of reverse-phase protein microarrays, in which human IgG of various concentrations was first immobilized on aldehyde-modified glass slides and then biotinlyated goat anti human IgG as well as the labeled nanoparticles were sequentially conjugated. The calibration curve is linear over the range from 800 fg to 500 pg and the limit of detection is 100 fg, which is 8 times lower than that of streptavidin-labeled Cy3 fluorescent dyes. The dyedoped SiO2 nanoparticles show potentials for the protein array detection.

  19. Fuzzy Logic for Elimination of Redundant Information of Microarray Data

    Institute of Scientific and Technical Information of China (English)

    Edmundo Bonilla Huerta; Béatrice Duval; Jin-Kao Hao

    2008-01-01

    Gene subset selection is essential for classification and analysis of microarray data. However, gene selection is known to be a very difficult task since gene expression data not only have high dimensionalities, but also contain redundant information and noises. To cope with these difficulties, this paper introduces a fuzzy logic based pre-processing approach composed of two main steps. First, we use fuzzy inference rules to transform the gene expression levels of a given dataset into fuzzy values. Then we apply a similarity relation to these fuzzy values to define fuzzy equivalence groups, each group containing strongly similar genes. Dimension reduction is achieved by considering for each group of similar genes a single representative based on mutual information. To assess the usefulness of this approach, extensive experimentations were carried out on three well-known public datasets with a combined classification model using three statistic filters and three classifiers.

  20. Chromosomal Microarray Testing in NEC: A Case Report.

    Science.gov (United States)

    Burjonrappa, Sathyaprasad C; Schwartzberg, David

    2016-01-01

    Necrotizing enterocolitis (NEC) remains the most common reason for emergent surgery in the neonatal intensive care unit. The common pathophysiology in all NEC involves alteration in gut microflora, abnormal blood supply to the intestine, and uncontrolled cytokine release. We report a full-term neonate who developed NEC. The neonate had surgical resection of approximately 120cms of bowel. After an initial proximal jejunostomy she underwent a successful jejuno-ileal anastomosis with preservation of her ileocolic valve at 6 weeks of age. A little more than one year of age, she is being weaned off her parenteral nutrition (PN) as her bowel adaptation continues. A chromosomal microarray analysis (CMA) resulted in the identification of a 15q13.3 microdeletion. PMID:27433452

  1. Microarray analysis of Escherichia coli0157:H7

    Institute of Scientific and Technical Information of China (English)

    Hui-Ying Jin; Kai-Hua Tao; Yue-Xi Li; Fa-Qing Li; Su-Qin Li

    2005-01-01

    AIM: To establish the rapid, specific, and sensitive method for detecting O157:H7 with DNA microchips.METHODS: Specific oligonucleotide probes (26-28 nt) of bacterial antigenic and virulent genes of E. coli O157:H7 and other related pathogen genes were pre-synthesized and immobilized on a solid support to make microchips. The four genes encoding O157 somatic antigen (rfbE), H7 fiagellar antigen (fliC) and toxins (SLT1, SLT2) were monitored by multiplex PCR with four pairs of specific primers. Fluorescence-Cy3 labeled samples for hybridization were generated by PCR with Cy3-labeled single prime. Hybridization was performed for 60 min at 45 ℃. Microchip images were taken using a confocal fluorescent scanner.RESULTS: Twelve different bacterial strains were detected with various combinations of four virulent genes. All the O157:H7 strains yielded positive results by multiplex PCR.The size of the PCR products generated with these primers varied from 210 to 678 bp. All the rfbE/fliC/SLT1/SLT2 probes specifically recognized Cy3-labeled fluorescent samples from O157:H7 strains, or strains containing O157 and H7 genes. No cross hybridization of O157:H7 fluorescent samples occurred in other probes. Non-O157:H7 pathogens failed to yield any signal under comparable conditions. If the Cy3-labeled fluorescent product of O157 single PCR was diluted 50-fold, no signal was found in agarose gel electrophoresis, but a positive signal was found in microarray hybridization.CONCLUSION: Microarray analysis of O157:H7 is a rapid,specific, and efficient method for identification and detection of bacterial pathogens.

  2. Detection and correction of probe-level artefacts on microarrays

    Directory of Open Access Journals (Sweden)

    Petri Tobias

    2012-05-01

    Full Text Available Abstract Background A recent large-scale analysis of Gene Expression Omnibus (GEO data found frequent evidence for spatial defects in a substantial fraction of Affymetrix microarrays in the GEO. Nevertheless, in contrast to quality assessment, artefact detection is not widely used in standard gene expression analysis pipelines. Furthermore, although approaches have been proposed to detect diverse types of spatial noise on arrays, the correction of these artefacts is mostly left to either summarization methods or the corresponding arrays are completely discarded. Results We show that state-of-the-art robust summarization procedures are vulnerable to artefacts on arrays and cannot appropriately correct for these. To address this problem, we present a simple approach to detect artefacts with high recall and precision, which we further improve by taking into account the spatial layout of arrays. Finally, we propose two correction methods for these artefacts that either substitute values of defective probes using probeset information or filter corrupted probes. We show that our approach can identify and correct defective probe measurements appropriately and outperforms existing tools. Conclusions While summarization is insufficient to correct for defective probes, this problem can be addressed in a straightforward way by the methods we present for identification and correction of defective probes. As these methods output CEL files with corrected probe values that serve as input to standard normalization and summarization procedures, they can be easily integrated into existing microarray analysis pipelines as an additional pre-processing step. An R package is freely available from http://www.bio.ifi.lmu.de/artefact-correction.

  3. Acute hepatotoxicity: a predictive model based on focused illumina microarrays.

    Science.gov (United States)

    Zidek, Nadine; Hellmann, Juergen; Kramer, Peter-Juergen; Hewitt, Philip G

    2007-09-01

    Drug-induced hepatotoxicity is a major issue for drug development, and toxicogenomics has the potential to predict toxicity during early toxicity screening. A bead-based Illumina oligonucleotide microarray containing 550 liver specific genes has been developed. We have established a predictive screening system for acute hepatotoxicity by analyzing differential gene expression profiles of well-known hepatotoxic and nonhepatotoxic compounds. Low and high doses of tetracycline, carbon tetrachloride (CCL4), 1-naphthylisothiocyanate (ANIT), erythromycin estolate, acetaminophen (AAP), or chloroform as hepatotoxicants, clofibrate, theophylline, naloxone, estradiol, quinidine, or dexamethasone as nonhepatotoxic compounds, were administered as a single dose to male Sprague-Dawley rats. After 6, 24, and 72 h, livers were taken for histopathological evaluation and for analysis of gene expression alterations. All hepatotoxic compounds tested generated individual gene expression profiles. Based on leave-one-out cross-validation analysis, gene expression profiling allowed the accurate discrimination of all model compounds, 24 h after high dose treatment. Even during the regeneration phase, 72 h after treatment, CCL4, ANIT, and AAP were predicted to be hepatotoxic, and only these three compounds showed histopathological changes at this time. Furthermore, we identified 64 potential marker genes responsible for class prediction, which reflected typical hepatotoxicity responses. These genes and pathways, commonly deregulated by hepatotoxicants, may be indicative of the early characterization of hepatotoxicity and possibly predictive of later hepatotoxicity onset. Two unknown test compounds were used for prevalidating the screening test system, with both being correctly predicted. We conclude that focused gene microarrays are sufficient to classify compounds with respect to toxicity prediction. PMID:17522070

  4. Microarray analysis of thioacetamide-treated type 1 diabetic rats

    International Nuclear Information System (INIS)

    It is well known that diabetes imparts high sensitivity to numerous hepatotoxicants. Previously, we have shown that a normally non-lethal dose of thioacetamide (TA, 300 mg/kg) causes 90% mortality in type 1 diabetic (DB) rats due to inhibited tissue repair allowing progression of liver injury. On the other hand, DB rats exposed to 30 mg TA/kg exhibit delayed tissue repair and delayed recovery from injury. The objective of this study was to investigate the mechanism of impaired tissue repair and progression of liver injury in TA-treated DB rats by using cDNA microarray. Gene expression pattern was examined at 0, 6, and 12 h after TA challenge, and selected mechanistic leads from microarray experiments were confirmed by real-time RT-PCR and further investigated at protein level over the time course of 0 to 36 h after TA treatment. Diabetic condition itself increased gene expression of proteases and decreased gene expression of protease inhibitors. Administration of 300 mg TA/kg to DB rats further elevated gene expression of proteases and suppressed gene expression of protease inhibitors, explaining progression of liver injury in DB rats after TA treatment. Inhibited expression of genes involved in cell division cycle (cyclin D1, IGFBP-1, ras, E2F) was observed after exposure of DB rats to 300 mg TA/kg, explaining inhibited tissue repair in these rats. On the other hand, DB rats receiving 30 mg TA/kg exhibit delayed expression of genes involved in cell division cycle, explaining delayed tissue repair in these rats. In conclusion, impaired cyclin D1 signaling along with increased proteases and decreased protease inhibitors may explain impaired tissue repair that leads to progression of liver injury initiated by TA in DB rats

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

    Directory of Open Access Journals (Sweden)

    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

  6. 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

  7. 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

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

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    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

  9. 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.

  10. 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.

  11. 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

    2013-01-01

    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. PMID:27605178

  12. Design and application of 60mer oligonucleotide microarray in SARS coronavirus detection

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    The 60mer oligonucleotide microarray was designed and applied to detecting of SARS (severe acute respiratory syndrome) coronavirus. Thirty 60mer specific oligos were designed to cover the whole genome of the first submitted coronavirus strain, according to the sequence of TOR2 (GENEBANK Accession: AY274119). These primers were synthesized and printed into a microarray with 12×12 spots. RNAs were extracted from the throat swab and gargling fluid of SARS patients and reverse-transcripted into the double strand cDNAs. The cDNAs were prepared as restricted cDNA fragments by the restriction display (RD) technique and labeled by PCR with the Cy5-universal primer. The labeled samples were then applied to the oligo microarray for hybridization. The diagnostic capability of the microarray was evaluated after the washing and scanning steps. The scanning result showed that samples of SARS patients were hybridized with multiple SARS probes on the microarray, and there is no signal on the negative and blank controls. These results indicate that the genome of SARS coronavirus can be detected in parallel by the 60mer oligonucleotide microarray, which can improve the positive ratio of the diagnosis. The oligo microarray can also be used for monitoring the behavior of the virus genes in different stages of the disease status.

  13. Improved detection of differentially expressed genes in microarray experiments through multiple scanning and image integration

    Science.gov (United States)

    Romualdi, Chiara; Trevisan, Silvia; Celegato, Barbara; Costa, Germano; Lanfranchi, Gerolamo

    2003-01-01

    The variability of results in microarray technology is in part due to the fact that independent scans of a single hybridised microarray give spot images that are not quite the same. To solve this problem and turn it to our advantage, we introduced the approach of multiple scanning and of image integration of microarrays. To this end, we have developed specific software that creates a virtual image that statistically summarises a series of consecutive scans of a microarray. We provide evidence that the use of multiple imaging (i) enhances the detection of differentially expressed genes; (ii) increases the image homogeneity; and (iii) reveals false-positive results such as differentially expressed genes that are detected by a single scan but not confirmed by successive scanning replicates. The increase in the final number of differentially expressed genes detected in a microarray experiment with this approach is remarkable; 50% more for microarrays hybridised with targets labelled by reverse transcriptase, and 200% more for microarrays developed with the tyramide signal amplification (TSA) technique. The results have been confirmed by semi-quantitative RT–PCR tests. PMID:14627839

  14. Interpreting Microarray Data to Build Models of Microbial Genetic Regulation Networks

    Energy Technology Data Exchange (ETDEWEB)

    Sokhansanj, B; Garnham, J B; Fitch, J P

    2002-01-23

    Microarrays and DNA chips are an efficient, high-throughput technology for measuring temporal changes in the expression of message RNA (mRNA) from thousands of genes (often the entire genome of an organism) in a single experiment. A crucial drawback of microarray experiments is that results are inherently qualitative: data are generally neither quantitatively repeatable, nor may microarray spot intensities be calibrated to in vivo mRNA concentrations. Nevertheless, microarrays represent by the far the cheapest and fastest way to obtain information about a cells global genetic regulatory networks. Besides poor signal characteristics, the massive number of data produced by microarray experiments poses challenges for visualization, interpretation and model building. Towards initial model development, we have developed a Java tool for visualizing the spatial organization of gene expression in bacteria. We are also developing an approach to inferring and testing qualitative fuzzy logic models of gene regulation using microarray data. Because we are developing and testing qualitative hypotheses that do not require quantitative precision, our statistical evaluation of experimental data is limited to checking for validity and consistency. Our goals are to maximize the impact of inexpensive microarray technology, bearing in mind that biological models and hypotheses are typically qualitative.

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

    Science.gov (United States)

    Ramirez, Lisa S; Wang, Jun

    2016-01-01

    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. PMID:26780370

  16. The effect of column purification on cDNA indirect labelling for microarrays

    Directory of Open Access Journals (Sweden)

    Kiss John Z

    2007-06-01

    Full Text Available Abstract Background The success of the microarray reproducibility is dependent upon the performance of standardized procedures. Since the introduction of microarray technology for the analysis of global gene expression, reproducibility of results among different laboratories has been a major problem. Two of the main contributors to this variability are the use of different microarray platforms and different laboratory practices. In this paper, we address the latter question in terms of how variation in one of the steps of a labelling procedure affects the cDNA product prior to microarray hybridization. Results We used a standard procedure to label cDNA for microarray hybridization and employed different types of column chromatography for cDNA purification. After purifying labelled cDNA, we used the Agilent 2100 Bioanalyzer and agarose gel electrophoresis to assess the quality of the labelled cDNA before its hybridization onto a microarray platform. There were major differences in the cDNA profile (i.e. cDNA fragment lengths and abundance as a result of using four different columns for purification. In addition, different columns have different efficiencies to remove rRNA contamination. This study indicates that the appropriate column to use in this type of protocol has to be experimentally determined. Finally, we present new evidence establishing the importance of testing the method of purification used during an indirect labelling procedure. Our results confirm the importance of assessing the quality of the sample in the labelling procedure prior to hybridization onto a microarray platform. Conclusion Standardization of column purification systems to be used in labelling procedures will improve the reproducibility of microarray results among different laboratories. In addition, implementation of a quality control check point of the labelled samples prior to microarray hybridization will prevent hybridizing a poor quality sample to expensive

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

    International Nuclear Information System (INIS)

    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

  18. Ontology-based retrieval of bio-medical information based on microarray text corpora

    DEFF Research Database (Denmark)

    Hansen, Kim Allan; Zambach, Sine; Have, Christian Theil

    degree. We explore the possibilities of retrieving biomedical information from microarrays in Gene Expression Omnibus (GEO), of which we have indexed a sample semantically, as a rst step towards ontology based searches. Through an example we argue that it is possible to improve the retrieval......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...

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

    OpenAIRE

    Ashutosh Halder; Manish Jain; Amanpreet Kaur Kalsi

    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 d...

  20. Microarray Technology for Major Chemical Contaminants Analysis in Food: Current Status and Prospects

    Directory of Open Access Journals (Sweden)

    Xiaoxia Ding

    2012-07-01

    Full Text Available Chemical contaminants in food have caused serious health issues in both humans and animals. Microarray technology is an advanced technique suitable for the analysis of chemical contaminates. In particular, immuno-microarray approach is one of the most promising methods for chemical contaminants analysis. The use of microarrays for the analysis of chemical contaminants is the subject of this review. Fabrication strategies and detection methods for chemical contaminants are discussed in detail. Application to the analysis of mycotoxins, biotoxins, pesticide residues, and pharmaceutical residues is also described. Finally, future challenges and opportunities are discussed.

  1. A microarray-based gastric carcinoma prewarning system

    Institute of Scientific and Technical Information of China (English)

    Da-Xiang Cui; Jin-Rong Zhao; Fen-Chan Han; Ju Zhang; Jia-Le Hu; Dai-Ming Fan; Hua-Jian Gao; Li Zhang; Xiao-Jun Yan; Ling-Xia Zhang; Jun-Rong Xu; Yan-Hai Guo; Gui-Qiu Jin; Giovani Gomez; Ding Li

    2005-01-01

    AIM: To develop a microarray-based prewarning system consisting of gastric cancer chip, prewarning data and analysissoftware for early detection of gastric cancer and pre-cancerous lesions.METHODS: Two high-density chips with 8 464 human cDNA sites were used to primarily identify potential genes specific for normal gastric mucosa, pre-cancerous lesion and gastric cancer. The low-density chips, composed of selected genes associated with normal gastric mucosa,precancerous lesion and gastric cancer, were fabricated and used to screen 150 specimens including 60 specimens of gastric cancer, 60 of pre-cancerous tissues and 30 of normal gastric mucosa. CAD software was used to screen out the relevant genes and their critical threshold values of expression levels distinguishing normal mucosa from pre-cancerous lesion and cancer. All data were stored in a computer database to establish a prewarning data library for gastric cancer. Two potential markers brcaa1 and ndr1were identified by Western blot and immunohistochemistry.RESULTS: A total of 412 genes associated with three stages of gastric cancer development were identified.There were 216 genes displaying higher expression in gastric cancer, 85 genes displaying higher expression in pre-cancerous lesion and 88 genes displaying higher expression in normal gastric mucosa. Also 15 genes associated with metastasis of gastric cancer and 8 genes associated with risk factors were screened out for target genes of diagnosis chip of early gastric cancer. The threshold values of 412 selected genes to distinguish gastric cancer, pre-cancerous lesion from normal gastric mucosa were defined as 6.01±2.40, 4.86±1.94 and 5.42±2.17, respectively. These selected 412 genes and critical threshold values were compiled into an analysis software, which can automatically provide reports by analyzing the results of 412 genes obtained by examining gastric tissues. All data were compiled into a prewarning database for gastric cancer by CGO

  2. RECOGNITION OF CDNA MICROARRAY IMAGE USING FEEDFORWARD ARTIFICIAL NEURAL NETWORK

    Directory of Open Access Journals (Sweden)

    R. M. Farouk

    2014-07-01

    Full Text Available The complementary DNA (cDNA sequence considered th e magic biometric technique for personal identification. Microarray image processing used fo r the concurrent genes identification. In this pape r, we present a new method for cDNA recognition based on the artificial neural network (ANN. We have segmented the location of the spots in a cDNA micro array. Thus, a precise localization and segmenting of a spot are essential to obtain a more exact intensity measurement, leading to a more accurate gene expression measurement. The segmented cDNA microarr ay image resized and used as an input for the proposed artificial neural network. For matching an d recognition, we have trained the artificial neura l network. Recognition results are given for the gall eries of cDNA sequences . The numerical results sho w that, the proposed matching technique is an effecti ve in the cDNA sequences process. The experimental results of our matching approach using different da tabases shows that, the proposed technique is an effective matching performance.

  3. ADVANTAGES AND APPLICATIONS OF TISSUE MICROARRAY TECHNOLOGY ON CANCER RESEARCH

    Institute of Scientific and Technical Information of China (English)

    张喜平; 苏丹; 程琪辉

    2003-01-01

    S To provide evidences for exploiting tissue microarray (TMA) technology, we reviewed advantages and applications of TMA on tumor research. TMA has many advantages, including (1) section from TMA blocks can be utilized for the simultaneous analysis of up to 1,000 different tumors at DNA, RNA or protein level; (2) TMA is highly representative of their donor tissues; (3) TMA can improve conservation of tissue resources and experimental reagents, improve internal experimental control, and increase sample numbers per experiment, and can be used for large-scale, massively parallel in situ analysis; (4) TMA facilitates rapid translation of molecular discoveries to clinical applications. TMA has been applied to tumor research, such as glioma, breast tumor, lung cancer and so on. The development of novel biochip technologies has opened up new possibilities for the high-throughput molecular profiling of human tumors. Novel molecular markers emerging from high-throughput expression surveys could be analyzed on tumor TMA. It is anticipated that TMA, a new member of biochip, will soon become a widely used tool for all types of tissue-based research. TMA will lead to a significant acceleration of the transition of basic research findings into clinical applications.

  4. DNA microarray analysis of genes differentially expressed in adipocyte differentiation

    Indian Academy of Sciences (India)

    Chunyan Yin; Yanfeng Xiao; Wei Zhang; Erdi Xu; Weihua Liu; Xiaoqing Yi; Ming Chang

    2014-06-01

    In the present study, the human liposarcoma cell line SW872 was used to identify global changes in gene expression profiles occurring during adipogenesis. We further explored some of the genes expressed during the late phase of adipocyte differentiation. 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 exhibited a ≥ 10-fold increase in the late phase of adipocyte differentiation by polymerase chain reaction (RT-PCR). Compared with undifferentiated preadipocytes, we found that 763 genes were increased in early differentiated adipocytes, and 667 genes were increased in later differentiated adipocytes. Furthermore, 21 genes were found being expressed 10-fold higher in the late phase of adipocyte differentiation. The results were in accordance with the RT-PCR test, which validated 11 genes, namely, CIDEC, PID1, LYRM1, ADD1, PPAR2, ANGPTL4, ADIPOQ, ACOX1, FIP1L1, MAP3K2 and PEX14. Most of these genes were found being expressed in the later phase of adipocyte differentiation involved in obesity-related diseases. The findings may help to better understand the mechanism of obesity and related diseases.

  5. Using Semantic Web Technologies to Annotate and Align Microarray Designs

    Directory of Open Access Journals (Sweden)

    Sebastian Szpakowski

    2009-05-01

    Full Text Available In this paper, we annotate and align two different gene expression microarray designs using the Genomic ELement Ontology (GELO. GELO is a new ontology that leverages an existing community resource, Sequence Ontology (SO, to create views of genomically-aligned data in a semantic web environment. We start the process by mapping array probes to genomic coordinates. The coordinates represent an implicit link between the probes and multiple genomic elements, such as genes, transcripts, miRNA, and repetitive elements, which are represented using concepts in SO. We then use the RDF Query Language (SPARQL to create explicit links between the probes and the elements. We show how the approach allows us to easily determine the element coverage and genomic overlap of the two array designs. We believe that the method will ultimately be useful for integration of cancer data across multiple omic studies. The ontology and other materials described in this paper are available at http://krauthammerlab.med.yale.edu/wiki/Gelo.

  6. Flexible automated platform for blood group genotyping on DNA microarrays.

    Science.gov (United States)

    Paris, Sandra; Rigal, Dominique; Barlet, Valérie; Verdier, Martine; Coudurier, Nicole; Bailly, Pascal; Brès, Jean-Charles

    2014-05-01

    The poor suitability of standard hemagglutination-based assay techniques for large-scale automated screening of red blood cell antigens severely limits the ability of blood banks to supply extensively phenotype-matched blood. With better understanding of the molecular basis of blood antigens, it is now possible to predict blood group phenotype by identifying single-nucleotide polymorphisms in genomic DNA. Development of DNA-typing assays for antigen screening in blood donation qualification laboratories promises to enable blood banks to provide optimally matched donations. We have designed an automated genotyping system using 96-well DNA microarrays for blood donation screening and a first panel of eight single-nucleotide polymorphisms to identify 16 alleles in four blood group systems (KEL, KIDD, DUFFY, and MNS). Our aim was to evaluate this system on 960 blood donor samples with known phenotype. Study data revealed a high concordance rate (99.92%; 95% CI, 99.77%-99.97%) between predicted and serologic phenotypes. These findings demonstrate that our assay using a simple protocol allows accurate, relatively low-cost phenotype prediction at the DNA level. This system could easily be configured with other blood group markers for identification of donors with rare blood types or blood units for IH panels or antigens from other systems. PMID:24726279

  7. 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.

  8. Bulk segregant analysis using single nucleotide polymorphism microarrays.

    Directory of Open Access Journals (Sweden)

    Anthony Becker

    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.

  9. Algorithm for Finding Optimal Gene Sets in Microarray Prediction

    CERN Document Server

    Deutsch, J M

    2001-01-01

    Motivation: Microarray data has been recently been shown to be efficacious in distinguishing closely related cell types that often appear in the diagnosis of cancer. It is useful to determine the minimum number of genes needed to do such a diagnosis both for clinical use and to determine the importance of specific genes for cancer. Here a replication algorithm is used for this purpose. It evolves an ensemble of predictors, all using different combinations of genes to generate a set of optimal predictors. Results: We apply this method to the leukemia data of the Whitehead/MIT group that attempts to differentially diagnose two kinds of leukemia, and also to data of Khan et. al. to distinguish four different kinds of childhood cancers. In the latter case we were able to reduce the number of genes needed from 96 down to 15, while at the same time being able to perfectly classify all of their test data. Availability: http://stravinsky.ucsc.edu/josh/gesses/ Contact: josh@physics.ucsc.edu

  10. Gene Expression Profiling on Acute Rejected Transplant Kidneys with Microarray

    Institute of Scientific and Technical Information of China (English)

    Deping LI; Kang WANG; Yong DAI; Tianyu LV

    2008-01-01

    To investigate the gene expression profiles in acute allograft rejection of renal trans- plantation, and identify the markers for the early diagnosis of acute rejection, heterotopic kidney transplantation was performed by using F344 or Lewis donors and Lewis recipients. No immunosup- pressant was used. Renal grafts were harvested on days 3, 7, and 14. A commercial microarray was used to measure gene expression levels in day-7 grafts. The expression levels of 48 genes were up-regulated in the allograft in comparison with the isograft control, and interferon-y-induced GTPase gene was most significantly up-regulated in allografts. It is concluded that a variety of pathways are involved in organ transplant rejection which is dynamic and non-balanced. IFN-inducible genes, such as IGTP, may play an important role in the rejection. A lot of important factors involved in acute re- jection are unnecessary but sufficient conditions for the rejection. We are led to conclude that it is virtually impossible to make an early diagnosis based on a single gene marker, but it could he achieved on the basis of a set of markers.

  11. TMAinspiration: Decode Interdependencies in Multifactorial Tissue Microarray Data.

    Science.gov (United States)

    Boecker, Florian; Buerger, Horst; Mallela, Nikhil V; Korsching, Eberhard

    2016-01-01

    There are no satisfying tools in tissue microarray (TMA) data analysis up to now to analyze the cooperative behavior of all measured markers in a multifactorial TMA approach. The developed tool TMAinspiration is not only offering an analysis option to close this gap but also offering an ecosystem consisting of quality control concepts and supporting scripts to make this approach a platform for informed practice and further research. The TMAinspiration method is specifically focusing on the demands of the TMA analysis by controlling errors and noise by a generalized regression scheme while at the same time avoiding to introduce a priori too many constraints into the analysis of the data. So, we are testing partitions of a proximity table to find an optimal support for a ranking scheme of molecular dependencies. The idea of combining several partitions to one ensemble, which is balancing the optimization process, is based on the main assumption that all these perspectives on the cellular network need to be self-consistent. Several application examples in breast cancer and one in squamous cell carcinoma demonstrate that this procedure is nicely confirming a priori knowledge on the expression characteristics of protein markers, while also integrating many new results discovered in the treasury of a bigger TMA experiment. The code and software are now freely available at: http://complex-systems.uni-muenster.de/tma_inspiration.html. PMID:27398021

  12. 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.

  13. Xylella fastidiosa gene expression analysis by DNA microarrays

    Directory of Open Access Journals (Sweden)

    Regiane F. Travensolo

    2009-01-01

    Full Text Available Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcription reactions and which were obtained from bacteria grown under two different conditions (liquid XDM2 and liquid BCYE. All data were statistically analyzed to verify which genes were differentially expressed. In addition to exploring conditions for X. fastidiosa genome-wide transcriptome analysis, the present work observed the differential expression of several classes of genes (energy, protein, amino acid and nucleotide metabolism, transport, degradation of substances, toxins and hypothetical proteins, among others. The understanding of expressed genes in these two different media will be useful in comprehending the metabolic characteristics of X. fastidiosa, and in evaluating how important certain genes are for the functioning and survival of these bacteria in plants.

  14. 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.

  15. Fibrin-mediated lentivirus gene transfer: implications for lentivirus microarrays.

    Science.gov (United States)

    Raut, Shruti D; Lei, Pedro; Padmashali, Roshan M; Andreadis, Stelios T

    2010-06-01

    We employed fibrin hydrogel as a bioactive matrix for lentivirus mediated gene transfer. Fibrin-mediated gene transfer was highly efficient and exhibited strong dependence on fibrinogen concentration. Efficient gene transfer was achieved with fibrinogen concentration between 3.75 and 7.5mg/ml. Lower fibrinogen concentrations resulted in diffusion of virus out of the gel while higher concentrations led to ineffective fibrin degradation by target cells. Addition of fibrinolytic inhibitors decreased gene transfer in a dose-dependent manner suggesting that fibrin degradation by target cells may be necessary for successful gene delivery. Under these conditions transduction may be limited only to cells interacting with the matrix thereby providing a method for spatially-localized gene delivery. Indeed, when lentivirus-containing fibrin microgels were spotted in an array format gene transfer was confined to virus-containing fibrin spots with minimal cross-contamination between neighboring sites. Collectively, our data suggest that fibrin may provide an effective matrix for spatially-localized gene delivery with potential applications in high-throughput lentiviral microarrays and in regenerative medicine. PMID:20153386

  16. Computational method for reducing variance with Affymetrix microarrays

    Directory of Open Access Journals (Sweden)

    Brooks Andrew I

    2002-08-01

    Full Text Available Abstract Background Affymetrix microarrays are used by many laboratories to generate gene expression profiles. Generally, only large differences (> 1.7-fold between conditions have been reported. Computational methods to reduce inter-array variability might be of value when attempting to detect smaller differences. We examined whether inter-array variability could be reduced by using data based on the Affymetrix algorithm for pairwise comparisons between arrays (ratio method rather than data based on the algorithm for analysis of individual arrays (signal method. Six HG-U95A arrays that probed mRNA from young (21–31 yr old human muscle were compared with six arrays that probed mRNA from older (62–77 yr old muscle. Results Differences in mean expression levels of young and old subjects were small, rarely > 1.5-fold. The mean within-group coefficient of variation for 4629 mRNAs expressed in muscle was 20% according to the ratio method and 25% according to the signal method. The ratio method yielded more differences according to t-tests (124 vs. 98 differences at P Conclusion The ratio method reduces inter-array variance and thereby enhances statistical power.

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

    Science.gov (United States)

    Huyghe, Antoine; François, Patrice; Mombelli, Andrea; Tangomo, Manuela; Girard, Myriam; Baratti-Mayer, Denise; Bolivar, Ignacio; Pittet, Didier; Schrenzel, Jacques

    2013-01-01

    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.

  18. 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.

  19. Compressed sensing methods for DNA microarrays, RNA interference, and metagenomics.

    Science.gov (United States)

    Rao, Aditya; P, Deepthi; Renumadhavi, C H; Chandra, M Girish; Srinivasan, Rajgopal

    2015-02-01

    Compressed sensing (CS) is a sparse signal sampling methodology for efficiently acquiring and reconstructing a signal from relatively few measurements. Recent work shows that CS is well-suited to be applied to problems in genomics, including probe design in microarrays, RNA interference (RNAi), and taxonomic assignment in metagenomics. The principle of using different CS recovery methods in these applications has thus been established, but a comprehensive study of using a wide range of CS methods has not been done. For each of these applications, we apply three hitherto unused CS methods, namely, l1-magic, CoSaMP, and l1-homotopy, in conjunction with CS measurement matrices such as randomly generated CS m matrix, Hamming matrix, and projective geometry-based matrix. We find that, in RNAi, the l1-magic (the standard package for l1 minimization) and l1-homotopy methods show significant reduction in reconstruction error compared to the baseline. In metagenomics, we find that l1-homotopy as well as CoSaMP estimate concentration with significantly reduced time when compared to the GPSR and WGSQuikr methods.

  20. Particle-Based Microarrays of Oligonucleotides and Oligopeptides

    Directory of Open Access Journals (Sweden)

    Alexander Nesterov-Mueller

    2014-10-01

    Full Text Available In this review, we describe different methods of microarray fabrication based on the use of micro-particles/-beads and point out future tendencies in the development of particle-based arrays. First, we consider oligonucleotide bead arrays, where each bead is a carrier of one specific sequence of oligonucleotides. This bead-based array approach, appearing in the late 1990s, enabled high-throughput oligonucleotide analysis and had a large impact on genome research. Furthermore, we consider particle-based peptide array fabrication using combinatorial chemistry. In this approach, particles can directly participate in both the synthesis and the transfer of synthesized combinatorial molecules to a substrate. Subsequently, we describe in more detail the synthesis of peptide arrays with amino acid polymer particles, which imbed the amino acids inside their polymer matrix. By heating these particles, the polymer matrix is transformed into a highly viscous gel, and thereby, imbedded monomers are allowed to participate in the coupling reaction. Finally, we focus on combinatorial laser fusing of particles for the synthesis of high-density peptide arrays. This method combines the advantages of particles and combinatorial lithographic approaches.

  1. The tissue microarray data exchange specification: A community-based, open source tool for sharing tissue microarray data

    Directory of Open Access Journals (Sweden)

    Edgerton Mary E

    2003-05-01

    Full Text Available Abstract Background Tissue Microarrays (TMAs allow researchers to examine hundreds of small tissue samples on a single glass slide. The information held in a single TMA slide may easily involve Gigabytes of data. To benefit from TMA technology, the scientific community needs an open source TMA data exchange specification that will convey all of the data in a TMA experiment in a format that is understandable to both humans and computers. A data exchange specification for TMAs allows researchers to submit their data to journals and to public data repositories and to share or merge data from different laboratories. In May 2001, the Association of Pathology Informatics (API hosted the first in a series of four workshops, co-sponsored by the National Cancer Institute, to develop an open, community-supported TMA data exchange specification. Methods A draft tissue microarray data exchange specification was developed through workshop meetings. The first workshop confirmed community support for the effort and urged the creation of an open XML-based specification. This was to evolve in steps with approval for each step coming from the stakeholders in the user community during open workshops. By the fourth workshop, held October, 2002, a set of Common Data Elements (CDEs was established as well as a basic strategy for organizing TMA data in self-describing XML documents. Results The TMA data exchange specification is a well-formed XML document with four required sections: 1 Header, containing the specification Dublin Core identifiers, 2 Block, describing the paraffin-embedded array of tissues, 3Slide, describing the glass slides produced from the Block, and 4 Core, containing all data related to the individual tissue samples contained in the array. Eighty CDEs, conforming to the ISO-11179 specification for data elements constitute XML tags used in the TMA data exchange specification. A set of six simple semantic rules describe the complete data exchange

  2. Discovering gene expression patterns in time course microarray experiments by ANOVA-SCA

    NARCIS (Netherlands)

    Nueda, M.J.; Conesa, A.; Westerhuis, J.A.; Hoefsloot, H.C.J.; Smilde, A.K.; Talón, M.; Ferrer, A.

    2007-01-01

    Motivation: Designed microarray experiments are used to investigate the effects that controlled experimental factors have on gene expression and learn about the transcriptional responses associated with external variables. In these datasets, signals of interest coexist with varying sources of unwant

  3. Experimental genomics: The application of DNA microarrays in cellular and molecular biology studies

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    The genome sequence information in combination with DNA microarrays promises to revolutionize the way of cellular and molecular biological research by allowing complex mixtures of RNA and DNA to interrogated in a parallel and quant itative fashion. DNA microarrays can be used to measure levels of gene expressio n for tens of thousands of gene simultaneously and take advantage of all availab le sequence information for experimental design and data interpretation in pursu it of biological understanding. Recent progress in experimental genomics allows DNA microarrays not simply to provide a catalogue of all the genes and informati on about their function, but to understand how the components work together to comprise functioning cells and organisms. This brief review gives a survey of DNA microarrays technology and its applications in genome and gene function analysis, gene expression studies, biological signal and defense system, cell cyclereg ulation, mechanism of transcriptional regulation, proteomics, and the functional ity of food component.

  4. Evaluation of DNA microarray for detection of rifampin and isoniazid resistance in Mycobacterium tuberculosis isolates

    Institute of Scientific and Technical Information of China (English)

    王峰

    2013-01-01

    Objective To evaluate the performance of DNA microarray for rapid detection resistance to rifampin and isoniazid in Mycobacterium tuberculosis clinical isolates and identify suitable target sites for molecular genetic test. Methods Twenty-four clinical Mycobacterium

  5. LD-RTPCR:\tA NEW METHOD FOR LABELLING TRACE cDNA MICROARRAY PROBE

    Institute of Scientific and Technical Information of China (English)

    范保星; 孙敬芬; 梁好; 王升启; 周平坤; 吴德昌

    2002-01-01

    Objective: To explore the usefulness of long distance reverse transcript combining linear amplification (LD-RTPCR) in labeling slight trace probe used for cDNA microarray. Methods: Total RNA from BEP2D cells was extracted and labeled by two different methods, LD-RTPCR with Cy3-dCTP as fluorescent dye and traditionally used RNA reverse transcript (RT) with Cy5-dCTP as fluorescent dye. Then, the probes labeled by two methods were mixed equally and hybridized with the cDNA microarray. Results: Scan and analysis of the microarray showed that the two methods labeled probes had consistent results. Conclusion: LD-RTPCR was proved useful for labeling cDNA microarray probe, especially for limited RNA material.

  6. Hybridization kinetics analysis of an oligonucleotide microarray for microRNA detection

    Institute of Scientific and Technical Information of China (English)

    Botao Zhao; Shuo Ding; Wei Li; Youxin Jin

    2011-01-01

    MicroRNA (miRNA) microarrays have been successfully used for profiling miRNA expression in many physiological processes such as development, differentiation, oncogenesis,and other disease processes. Detecting miRNA by miRNA microarray is actually based on nucleic acid hybridization between target molecules and their corresponding complementary probes. Due to the small size and high degree of similarity among miRNA sequences, the hybridization condition must be carefully optimized to get specific and reliable signals. Previously, we reported a microarray platform to detect miRNA expression. In this study, we evaluated the sensitivity and specificity of our microarray platform. After systematic analysis, we determined an optimized hybridization condition with high sensitivity and specificity for miRNA detection. Our results would be helpful for other hybridization-based miRNA detection methods, such as northern blot and nuclease protection assay.

  7. Genotyping Cryptosporidium parvum with an hsp70 Single-Nucleotide Polymorphism Microarray

    Energy Technology Data Exchange (ETDEWEB)

    Straub, Tim M.(BATTELLE (PACIFIC NW LAB)); Daly, Don S.(BATTELLE (PACIFIC NW LAB)); Wunshel, Sharon (Metropolitan Water District of Southern California); Rochelle, Paul A.(VISITORS); Deleon, Ricardo (Metropolitan Water District of Southern California); Chandler, Darrell P.(Pacific Northwest National Laboratory)

    2002-03-26

    We investigated the application of an oligonucleotide microarray to (1) specifically detect Cryptosporidium spp., (2) differentiate between closely related C. parvum strains and Cryptosporidium species, and (3) differentiate between principle genotypes known to infect humans.

  8. Genomewide expression analysis in amino acid-producing bacteria using DNA microarrays.

    Science.gov (United States)

    Polen, Tino; Wendisch, Volker F

    2004-01-01

    DNA microarray technology has become an important research tool for biotechnology and microbiology. It is now possible to characterize genetic diversity and gene expression in a genomewide manner. DNA microarrays have been applied extensively to study the biology of many bacteria including Escherichia coli, but only recently have they been developed for the Gram-positive Corynebacterium glutamicum. Both bacteria are widely used for biotechnological amino acid production. In this article, in addition to the design and generation of microarrays as well as their use in hybridization experiments and subsequent data analysis, we describe recent applications of DNA microarray technology regarding amino acid production in C. glutamicum and E. coli. We also discuss the impact of functional genomics studies on fundamental as well as applied aspects of amino acid production with C. glutamicum and E. coli. PMID:15304751

  9. 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

    technology is a promising diagnostic tool that provides genomic information onmany genes simultaneously. However, standardization of DNA microarray analysis is needed before it can be used as a routine method for characterizing Salmonella isolates across borders and laboratories. A comparative study......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...... of the microarray technique as a first step towards standardization. The low-density array contains 281 57–60-mer oligonucleotide probes for detecting a wide range of specific genomic marker genes associated with antibiotic resistance, cell envelope structures,mobile genetic elements and pathogenicity. Several...

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

    NARCIS (Netherlands)

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

    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

  11. Unravelling microbial communities with DNA-microarrays: challenges and future directions

    NARCIS (Netherlands)

    Wagner, M.; Smidt, H.; Loy, A.; Zhou, J.

    2007-01-01

    High-throughput technologies are urgently needed for monitoring the formidable biodiversity and functional capabilities of microorganisms in the environment. Ten years ago, DNA microarrays, miniaturized platforms for highly parallel hybridization reactions, found their way into environmental microbi

  12. Annotation-Based Whole Genomic Prediction and Selection

    DEFF Research Database (Denmark)

    Kadarmideen, Haja; Do, Duy Ngoc; Janss, Luc;

    in their contribution to estimated genomic variances and in prediction of genomic breeding values by applying SNP annotation approaches to feed efficiency. Ensembl Variant Predictor (EVP) and Pig QTL database were used as the source of genomic annotation for 60K chip. Genomic prediction was performed using the Bayes...... prove useful for less heritable traits such as diseases and fertility...

  13. An annotation based approach to support design communication

    CERN Document Server

    Hisarciklilar, Onur

    2007-01-01

    The aim of this paper is to propose an approach based on the concept of annotation for supporting design communication. In this paper, we describe a co-operative design case study where we analyse some annotation practices, mainly focused on design minutes recorded during project reviews. We point out specific requirements concerning annotation needs. Based on these requirements, we propose an annotation model, inspired from the Speech Act Theory (SAT) to support communication in a 3D digital environment. We define two types of annotations in the engineering design context, locutionary and illocutionary annotations. The annotations we describe in this paper are materialised by a set of digital artefacts, which have a semantic dimension allowing express/record elements of technical justifications, traces of contradictory debates, etc. In this paper, we first clarify the semantic annotation concept, and we define general properties of annotations in the engineering design context, and the role of annotations in...

  14. Web Database Query Interface Annotation Based on User Collaboration

    Institute of Scientific and Technical Information of China (English)

    LIU Wei; LIN Can; MENG Xiaofeng

    2006-01-01

    A vision based query interface annotation method is used to relate attributes and form elements in form-based web query interfaces, this method can reach accuracy of 82%.And a user participation method is used to tune the result; user can answer "yes" or "no" for existing annotations, or manually annotate form elements.Mass feedback is added to the annotation algorithm to produce more accurate result.By this approach, query interface annotation can reach a perfect accuracy.

  15. Annotation-Based Whole Genomic Prediction and Selection

    DEFF Research Database (Denmark)

    Kadarmideen, Haja; Do, Duy Ngoc; Janss, Luc;

    using the BayesCπ method and applied to 1,272 Duroc pigs with both genotypic and phenotypic records including residual (RFI) and daily feed intake (DFI), average daily gain (ADG) and back fat (BF)). Records were split into a training (968 pigs) and a validation dataset (304 pigs). SNPs were annotated by...... 14 different classes. Predictive accuracy was 0.531, 0.532, 0.302, and 0.344 for DFI, RFI, ADG and BF, respectively. The contribution per SNP to total genomic variance was similar among annotated classes across different traits. Predictive performance of SNP classes did not significantly differ from...

  16. SNP annotation-based whole genomic prediction and selection

    DEFF Research Database (Denmark)

    Do, Duy Ngoc; Janss, Luc; Jensen, Just;

    2015-01-01

    into a training (968 pigs) and a validation dataset (304 pigs) by assigning records as before and after January 1, 2012, respectively. SNP were annotated by 14 different classes using Ensembl variant effect prediction. Predictive accuracy and prediction bias were calculated using Bayesian Power LASSO...... SNP to total genomic variance was similar among annotated classes across different traits. Predictive performance of SNP classes did not significantly differ from randomized SNP groups. Genomic prediction has accuracy comparable to observed phenotype, and use of genomic prediction can be cost...... effective by replacing feed intake measurement. Genomic annotation had less impact on predictive accuracy traits considered here but may be different for other traits. It is the first study to provide useful insights into biological classes of SNP driving the whole genomic prediction for complex traits in...

  17. Calling Biomarkers in Milk Using a Protein Microarray on Your Smartphone

    OpenAIRE

    Ludwig, S.K.J.; Tokarski, Christian; Stefan N Lang; 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 procedure, the 48 microspots were labelled with Quantum Dots (QD) depending on the protein biomarker levels in the sample. QD-fluorescence was subsequently detected by the smartphone camera under UV l...

  18. Seasonal dynamics of harmful algae in outer Oslofjorden monitored by microarray, qPCR, and microscopy.

    Science.gov (United States)

    Dittami, Simon M; Hostyeva, Vladyslava; Egge, Elianne Sirnæs; Kegel, Jessica U; Eikrem, Wenche; Edvardsen, Bente

    2013-10-01

    Monitoring of marine microalgae is important to predict and manage harmful algal blooms. Microarray Detection of Toxic ALgae (MIDTAL) is an FP7-funded EU project aiming to establish a multi-species microarray as a tool to aid monitoring agencies. We tested the suitability of different prototype versions of the MIDTAL microarray for the monthly monitoring of a sampling station in outer Oslofjorden during a 1-year period. Microarray data from two different versions of the MIDTAL chip were compared to results from cell counts (several species) and quantitative real-time PCR (qPCR; only Pseudochattonella spp.). While results from generation 2.5 microarrays exhibited a high number of false positive signals, generation 3.3 microarray data generally correlated with microscopy and qPCR data, with three important limitations: (1) Pseudo-nitzschia cells were not reliably detected, possibly because cells were not sufficiently retained during filtration or lysed during the extraction, and because of low sensitivity of the probes; (2) in the case of samples with high concentrations of non-target species, the sensitivity of the arrays was decreased; (3) one occurrence of Alexandrium pseudogonyaulax was not detected due to a 1-bp mismatch with the genus probe represented on the microarray. In spite of these shortcomings our data demonstrate the overall progress made and the potential of the MIDTAL array. The case of Pseudochattonella - where two morphologically similar species impossible to separate by light microscopy were distinguished - in particular, underlines the added value of molecular methods such as microarrays in routine phytoplankton monitoring. PMID:23325054

  19. Recognition of cDNA microarray image Using Feedforward artificial neural network

    OpenAIRE

    R. M. Farouk; E. M. Badr; M. A. SayedElahl

    2014-01-01

    The complementary DNA (cDNA) sequence is considered to be the magic biometric technique for personal identification. In this paper, we present a new method for cDNA recognition based on the artificial neural network (ANN). Microarray imaging is used for the concurrent identification of thousands of genes. We have segmented the location of the spots in a cDNA microarray. Thus, a precise localization and segmenting of a spot are essential to obtain a more accurate intensity measurement, leading...

  20. SIMULATION AND VISUALIZATION OF FLOW PATTERN IN MICROARRAYS FOR LIQUID PHASE OLIGONUCLEOTIDE AND PEPTIDE SYNTHESIS

    OpenAIRE

    O-Charoen, Sirimon; Srivannavit, Onnop; Gulari, Erdogan

    2007-01-01

    Microfluidic microarrays have been developed for economical and rapid parallel synthesis of oligonucleotide and peptide libraries. For a synthesis system to be reproducible and uniform, it is crucial to have a uniform reagent delivery throughout the system. Computational fluid dynamics (CFD) is used to model and simulate the microfluidic microarrays to study geometrical effects on flow patterns. By proper design geometry, flow uniformity could be obtained in every microreactor in the microarr...

  1. FiRe and microarrays: a fast answer to burning questions

    OpenAIRE

    Garcion, Christophe; ApplimathFRI; Métraux, Jean-Pierre

    2006-01-01

    FiRe is a user-friendly Excel® macro designed to survey microarray data rapidly. This software interactively assembles data from different experiments and produces lists of candidate genes according to patterns of gene expression. Furthermore, macros bundled with FiRe can compare lists of genes, merge information from different spreadsheets, link candidates to information available from web-based databases, and produce heat-maps for easy visualization of microarray data. FiRe is freely availa...

  2. Microarray dataset of Jurkat cells following miR-93 over-expression.

    Science.gov (United States)

    Gioiosa, Silvia; Verduci, Lorena; Azzalin, Gianluca; Carissimi, Claudia; Fulci, Valerio; Macino, Giuseppe

    2016-09-01

    The dataset presented here represents a microarray experiment of Jurkat cell line over-expressing miR-93 after lentiviral transgenic construct transduction. Three biological replicates have been performed. We further provide normalized and processed data, log2 Fold Change based ranked list and GOterms resulting table. The raw microarray data are available in the ArrayExpress database (www.ebi.ac.uk/arrayexpress) under accession number ArrayExpress: E-MTAB-4588. PMID:27408928

  3. Detection bias in microarray and sequencing transcriptomic analysis identified by housekeeping genes

    OpenAIRE

    Yijuan Zhang; Oluwafemi S. Akintola; Liu, Ken J.A.; Bingyun Sun

    2015-01-01

    This work includes the original data used to discover the gene ontology bias in transcriptomic analysis conducted by microarray and high throughput sequencing (Zhang et al., 2015) [1]. In the analysis, housekeeping genes were used to examine the differential detection ability by microarray and sequencing because these genes are probably the most reliably detected. The genes included here were compiled from 15 human housekeeping gene studies. The provided tables here comprise of detailed chrom...

  4. Can subtle changes in gene expression be consistently detected with different microarray platforms?

    OpenAIRE

    Kuiper Rowan; de Hollander Mattias; Ariyurek Yavuz; Vossen Rolf HAM; Schenk Geert J; Vreugdenhil Erno; 't Hoen Peter AC; Pedotti Paola; van Ommen Gertjan JB; den Dunnen Johan T; Boer Judith M; Menezes Renée X

    2008-01-01

    Abstract Background The comparability of gene expression data generated with different microarray platforms is still a matter of concern. Here we address the performance and the overlap in the detection of differentially expressed genes for five different microarray platforms in a challenging biological context where differences in gene expression are few and subtle. Results Gene expression profiles in the hippocampus of five wild-type and five transgenic δC-doublecortin-like kinase mice were...

  5. Dynamic biclustering of microarray data by multi-objective immune optimization

    OpenAIRE

    Liu, Junwan; Li, Zhoujun; Hu, Xiaohua; Chen, Yiming; Park, EK

    2011-01-01

    Abstract Background Newly microarray technologies yield large-scale datasets. The microarray datasets are usually presented in 2D matrices, where rows represent genes and columns represent experimental conditions. Systematic analysis of those datasets provides the increasing amount of information, which is urgently needed in the post-genomic era. Biclustering, which is a technique developed to allow simultaneous clustering of rows and columns of a dataset, might be useful to extract more accu...

  6. A biclustering algorithm based on a Bicluster Enumeration Tree: application to DNA microarray data

    OpenAIRE

    Ayadi Wassim; Elloumi Mourad; Hao Jin-Kao

    2009-01-01

    Abstract Background In a number of domains, like in DNA microarray data analysis, we need to cluster simultaneously rows (genes) and columns (conditions) of a data matrix to identify groups of rows coherent with groups of columns. This kind of clustering is called biclustering. Biclustering algorithms are extensively used in DNA microarray data analysis. More effective biclustering algorithms are highly desirable and needed. Methods We introduce BiMine, a new enumeration algorithm for biclust...

  7. Prenatal Chromosomal Microarray Analysis and Identification of Genetic Variants in Congenital Diaphragmatic Hernia.

    OpenAIRE

    Brady, Paul

    2014-01-01

    Chromosomal microarray analysis has gradually replaced conventional karyotyping over recent years in the postnatal setting which has revolutionized whole genome screening for genomic imbalances in patients. We sought to evaluate the benefits and the challenges of applying chromosomal microarrays to prenatal diagnosis for referrals with abnormal ultrasound findings. Our findings, presented in Chapter 3, demonstrate a diagnostic yield of ~10%. Importantly, ~3% are caused by submicroscopic CN...

  8. Microarray Detection of Duplex and Triplex DNA Binders with DNA-Modified Gold Nanoparticles

    OpenAIRE

    Lytton-Jean, Abigail K. R.; Han, Min Su; Mirkin, Chad A.

    2007-01-01

    We have designed a chip-based assay, using microarray technology, for determining the relative binding affinities of duplex and triplex DNA binders. This assay combines the high discrimination capabilities afforded by DNA-modified Au nanoparticles with the high-throughput capabilities of DNA microarrays. The detection and screening of duplex DNA binders are important because these molecules, in many cases, are potential anticancer agents as well as toxins. Triplex DNA binders are also promisi...

  9. Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient

    OpenAIRE

    Loraine Ann; Hung Yeung; Salmi Mari L; Chang Chunqi; Yao Jianchao; Roux Stanley J

    2008-01-01

    Abstract Background Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An eff...

  10. 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.

  11. DNA nanostructure-based universal microarray platform for high-efficiency multiplex bioanalysis in biofluids.

    Science.gov (United States)

    Li, Zhenhua; Zhao, Bin; Wang, Dongfang; Wen, Yanli; Liu, Gang; Dong, Haoqing; Song, Shiping; Fan, Chunhai

    2014-10-22

    Microarrays of biomolecules have greatly promoted the development of the fields of genomics, proteomics, and clinical assays because of their remarkably parallel and high-throughput assay capability. Immobilization strategies for biomolecules on a solid support surface play a crucial role in the fabrication of high-performance biological microarrays. In this study, rationally designed DNA tetrahedra carrying three amino groups and one single-stranded DNA extension were synthesized by the self-assembly of four oligonucleotides, followed by high-performance liquid chromatography purification. We fabricated DNA tetrahedron-based microarrays by covalently coupling the DNA tetrahedron onto glass substrates. After their biorecognition capability was evaluated, DNA tetrahedron microarrays were utilized for the analysis of different types of bioactive molecules. The gap hybridization strategy, the sandwich configuration, and the engineering aptamer strategy were employed for the assay of miRNA biomarkers, protein cancer biomarkers, and small molecules, respectively. The arrays showed good capability to anchor capture biomolecules for improving biorecognition. Addressable and high-throughput analysis with improved sensitivity and specificity had been achieved. The limit of detection for let-7a miRNA, prostate specific antigen, and cocaine were 10 fM, 40 pg/mL, and 100 nM, respectively. More importantly, we demonstrated that the microarray platform worked well with clinical serum samples and showed good relativity with conventional chemical luminescent immunoassay. We have developed a novel approach for the fabrication of DNA tetrahedron-based microarrays and a universal DNA tetrahedron-based microarray platform for the detection of different types of bioactive molecules. The microarray platform shows great potential for clinical diagnosis.

  12. Robust Sequence Selection Method Used To Develop the FluChip Diagnostic Microarray for Influenza Virus

    OpenAIRE

    Mehlmann, Martin; Dawson, Erica D.; Townsend, Michael B.; Smagala, James A.; Moore, Chad L.; Smith, Catherine B.; Cox, Nancy J.; Kuchta, Robert D.; Rowlen, Kathy L.

    2006-01-01

    DNA microarrays have proven to be powerful tools for gene expression analyses and are becoming increasingly attractive for diagnostic applications, e.g., for virus identification and subtyping. The selection of appropriate sequences for use on a microarray poses a challenge, particularly for highly mutable organisms such as influenza viruses, human immunodeficiency viruses, and hepatitis C viruses. The goal of this work was to develop an efficient method for mining large databases in order to...

  13. Gene ARMADA: an integrated multi-analysis platform for microarray data implemented in MATLAB

    OpenAIRE

    Kolisis Fragiskos N; Moulos Panagiotis; Chatziioannou Aristotelis

    2009-01-01

    Abstract Background The microarray data analysis realm is ever growing through the development of various tools, open source and commercial. However there is absence of predefined rational algorithmic analysis workflows or batch standardized processing to incorporate all steps, from raw data import up to the derivation of significantly differentially expressed gene lists. This absence obfuscates the analytical procedure and obstructs the massive comparative processing of genomic microarray da...

  14. Microengineering Methods for Cell Based Microarrays and High-Throughput Drug Screening Applications

    OpenAIRE

    Xu, Feng; Wu, Jinhui; Wang, Shuqi; Durmus, Naside Gozde; Gurkan, Umut Atakan; Demirci, Utkan

    2011-01-01

    Screening for effective therapeutic agents from millions of drug candidates is costly, time-consuming and often face ethical concerns due to extensive use of animals. To improve cost-effectiveness, and to minimize animal testing in pharmaceutical research, in vitro monolayer cell microarrays with multiwell plate assays have been developed. Integration of cell microarrays with microfluidic systems have facilitated automated and controlled component loading, significantly reducing the consumpti...

  15. 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.

  16. Development and validation of a 2,000-gene microarray for the fathead minnow (Pimephales promelas)

    Energy Technology Data Exchange (ETDEWEB)

    Larkin, Patrick; Villeneuve, Daniel L.; Knoebl, Iris; Miracle, Ann L.; Carter, Barbara J.; Liu, Li; Denslow, Nancy D.; Ankley, Gerald T.

    2007-07-01

    Gene microarrays provide the field of ecotoxicology new tools to identify mechanisms of action of chemicals and chemical mixtures. Herein we describe the development and application of a 2,000-gene oligonucleotide microarray for the fathead minnow Pimephales promelas, a species commonly used in ecological risk assessments in North America. The microarrays were developed from various cDNA and subtraction libraries that we constructed. Consistency and reproducibility of the microarrays were documented by examining multiple technical replicates. To test application of the fathead minnow microarrays, gene expression profiles of fish exposed to 17-estradiol, a well-characterized estrogen receptor (ER) agonist, were examined. For these experiments, adult male fathead minnows were exposed for 24 h to waterborne 17-estradiol (40 or 100 ng/L) in a flow-through system, and gene expression in liver samples was characterized. Seventy-one genes were identified as differentially regulated by estradiol exposure. Examination of the gene ontology designations of these genes revealed patterns consistent with estradiol’s expected mechanisms of action and also provided novel insights as to molecular effects of the estrogen. Our studies indicate the feasibility and utility of microarrays as a basis for understanding biological responses to chemical exposure in a model ecotoxicology test species.

  17. Development of a DNA-based microarray for the detection of zoonotic pathogens in rodent species.

    Science.gov (United States)

    Giles, Timothy; Yon, Lisa; Hannant, Duncan; Barrow, Paul; Abu-Median, Abu-Bakr

    2015-12-01

    The demand for diagnostic tools that allow simultaneous screening of samples for multiple pathogens is increasing because they overcome the limitations of other methods, which can only screen for a single or a few pathogens at a time. Microarrays offer the advantages of being capable to test a large number of samples simultaneously, screening for multiple pathogen types per sample and having comparable sensitivity to existing methods such as PCR. Array design is often considered the most important process in any microarray experiment and can be the deciding factor in the success of a study. There are currently no microarrays for simultaneous detection of rodent-borne pathogens. The aim of this report is to explicate the design, development and evaluation of a microarray platform for use as a screening tool that combines ease of use and rapid identification of a number of rodent-borne pathogens of zoonotic importance. Nucleic acid was amplified by multiplex biotinylation PCR prior to hybridisation onto microarrays. The array sensitivity was comparable to standard PCR, though less sensitive than real-time PCR. The array presented here is a prototype microarray identification system for zoonotic pathogens that can infect rodent species. PMID:26188129

  18. A microarray system for Y chromosomal and mitochondrial single nucleotide polymorphism analysis in chimpanzee populations.

    Science.gov (United States)

    Andrés, Olga; Rönn, Ann-Charlotte; Bonhomme, Maxime; Kellermann, Thomas; Crouau-Roy, Brigitte; Doxiadis, Gaby; Verschoor, Ernst J; Goossens, Benoît; Domingo-Roura, Xavier; Bruford, Michael W; Bosch, Montserrat; Syvänen, Ann-Christine

    2008-05-01

    Chimpanzee populations are diminishing as a consequence of human activities, and as a result this species is now endangered. In the context of conservation programmes, genetic data can add vital information, for instance on the genetic diversity and structure of threatened populations. Single nucleotide polymorphisms (SNP) are biallelic markers that are widely used in human molecular studies and can be implemented in efficient microarray systems. This technology offers the potential of robust, multiplexed SNP genotyping at low reagent cost in other organisms than humans, but it is not commonly used yet in wild population studies. Here, we describe the characterization of new SNPs in Y-chromosomal intronic regions in chimpanzees and also identify SNPs from mitochondrial genes, with the aim of developing a microarray system that permits the simultaneous study of both paternal and maternal lineages. Our system consists of 42 SNPs for the Y chromosome and 45 SNPs for the mitochondrial genome. We demonstrate the applicability of this microarray in a captive population where genotypes accurately reflected its large pedigree. Two wild-living populations were also analysed and the results show that the microarray will be a useful tool alongside microsatellite markers, since it supplies complementary information about population structure and ecology. SNP genotyping using microarray technology, therefore, is a promising approach and may become an essential tool in conservation genetics to help in the management and study of captive and wild-living populations. Moreover, microarrays that combine SNPs from different genomic regions could replace microsatellite typing in the future. PMID:21585830

  19. Relationship between gene co-expression and probe localization on microarray slides

    Directory of Open Access Journals (Sweden)

    Qian Jiang

    2003-12-01

    Full Text Available Abstract Background Microarray technology allows simultaneous measurement of thousands of genes in a single experiment. This is a potentially useful tool for evaluating co-expression of genes and extraction of useful functional and chromosomal structural information about genes. Results In this work we studied the association between the co-expression of genes, their location on the chromosome and their location on the microarray slides by analyzing a number of eukaryotic expression datasets, derived from the S. cerevisiae, C. elegans, and D. melanogaster. We find that in several different yeast microarray experiments the distribution of the number of gene pairs with correlated expression profiles as a function of chromosomal spacing is peaked at short separations and has two superimposed periodicities. The longer periodicity has a spacing of 22 genes (~42 Kb, and the shorter periodicity is 2 genes (~4 Kb. Conclusion The relative positioning of DNA probes on microarray slides and source plates introduces subtle but significant correlations between pairs of genes. Careful consideration of this spatial artifact is important for analysis of microarray expression data. It is particularly relevant to recent microarray analyses that suggest that co-expressed genes cluster along chromosomes or are spaced by multiples of a fixed number of genes along the chromosome.

  20. 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.

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

    Science.gov (United States)

    Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

    2016-01-01

    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. PMID:27657141

  2. Application of Oligonucleotide Microarrays for Bacterial Source Tracking of Environmental Enterococcus sp. Isolates

    Directory of Open Access Journals (Sweden)

    John S. Furey

    2005-04-01

    Full Text Available In an effort towards adapting new and defensible methods for assessing and managing the risk posed by microbial pollution, we evaluated the utility of oligonucleotide microarrays for bacterial source tracking (BST of environmental Enterococcus sp. isolates derived from various host sources. Current bacterial source tracking approaches rely on various phenotypic and genotypic methods to identify sources of bacterial contamination resulting from point or non-point pollution. For this study Enterococcus sp. isolates originating from deer, bovine, gull, and human sources were examined using microarrays. Isolates were subjected to Box PCR amplification and the resulting amplification products labeled with Cy5. Fluorescent-labeled templates were hybridized to in-house constructed nonamer oligonucleotide microarrays consisting of 198 probes. Microarray hybridization profiles were obtained using the ArrayPro image analysis software. Principal Components Analysis (PCA and Hierarchical Cluster Analysis (HCA were compared for their ability to visually cluster microarray hybridization profiles based on the environmental source from which the Enterococcus sp. isolates originated. The PCA was visually superior at separating origin-specific clusters, even for as few as 3 factors. A Soft Independent Modeling (SIM classification confirmed the PCA, resulting in zero misclassifications using 5 factors for each class. The implication of these results for the application of random oligonucleotide microarrays for BST is that, given the reproducibility issues, factor-based variable selection such as in PCA and SIM greatly outperforms dendrogram-based similarity measures such as in HCA and K-Nearest Neighbor KNN.

  3. A microfluidic device for the automated electrical readout of low-density glass-slide microarrays.

    Science.gov (United States)

    Díaz-González, María; Salvador, J Pablo; Bonilla, Diana; Marco, M Pilar; Fernández-Sánchez, César; Baldi, Antoni

    2015-12-15

    Microarrays are a powerful platform for rapid and multiplexed analysis in a wide range of research fields. Electrical readout systems have emerged as an alternative to conventional optical methods for microarray analysis thanks to its potential advantages like low-cost, low-power and easy miniaturization of the required instrumentation. In this work an automated electrical readout system for low-cost glass-slide microarrays is described. The system enables the simultaneous conductimetric detection of up to 36 biorecognition events by incorporating an array of interdigitated electrode transducers. A polydimethylsiloxane microfluidic structure has been designed that creates microwells over the transducers and incorporates the microfluidic channels required for filling and draining them with readout and cleaning solutions, thus making the readout process fully automated. Since the capture biomolecules are not immobilized on the transducer surface this readout system is reusable, in contrast to previously reported electrochemical microarrays. A low-density microarray based on a competitive enzymatic immunoassay for atrazine detection was used to test the performance of the readout system. The electrical assay shows a detection limit of 0.22±0.03 μg L(-1) similar to that obtained with fluorescent detection and allows the direct determination of the pesticide in polluted water samples. These results proved that an electrical readout system such as the one presented in this work is a reliable and cost-effective alternative to fluorescence scanners for the analysis of low-density microarrays.

  4. A web-based platform for rice microarray annotation and data analysis

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Rice(Oryza sativa) feeds over half of the global population.A web-based integrated platform for rice microarray annotation and data analysis in various biological contexts is presented,which provides a convenient query for comprehensive annotation compared with similar databases.Coupled with existing rice microarray data,it provides online analysis methods from the perspective of bioinformatics.This comprehensive bioinformatics analysis platform is composed of five modules,including data retrieval,microarray annotation,sequence analysis,results visualization and data analysis.The BioChip module facilitates the retrieval of microarray data information via identifiers of "Probe Set ID","Locus ID" and "Analysis Name".The BioAnno module is used to annotate the gene or probe set based on the gene function,the domain information,the KEGG biochemical and regulatory pathways and the potential microRNA which regulates the genes.The BioSeq module lists all of the related sequence information by a microarray probe set.The BioView module provides various visual results for the microarray data.The BioAnaly module is used to analyze the rice microarray’s data set.

  5. 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.

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

    Directory of Open Access Journals (Sweden)

    Beau J Fenner

    Full Text Available 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.

  7. 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.

  8. Microarray-based sketches of the HERV transcriptome landscape.

    Science.gov (United States)

    Pérot, Philippe; Mugnier, Nathalie; Montgiraud, Cécile; Gimenez, Juliette; Jaillard, Magali; Bonnaud, Bertrand; Mallet, François

    2012-01-01

    Human endogenous retroviruses (HERVs) are spread throughout the genome and their long terminal repeats (LTRs) constitute a wide collection of putative regulatory sequences. Phylogenetic similarities and the profusion of integration sites, two inherent characteristics of transposable elements, make it difficult to study individual locus expression in a large-scale approach, and historically apart from some placental and testis-regulated elements, it was generally accepted that HERVs are silent due to epigenetic control. Herein, we have introduced a generic method aiming to optimally characterize individual loci associated with 25-mer probes by minimizing cross-hybridization risks. We therefore set up a microarray dedicated to a collection of 5,573 HERVs that can reasonably be assigned to a unique genomic position. We obtained a first view of the HERV transcriptome by using a composite panel of 40 normal and 39 tumor samples. The experiment showed that almost one third of the HERV repertoire is indeed transcribed. The HERV transcriptome follows tropism rules, is sensitive to the state of differentiation and, unexpectedly, seems not to correlate with the age of the HERV families. The probeset definition within the U3 and U5 regions was used to assign a function to some LTRs (i.e. promoter or polyA) and revealed that (i) autonomous active LTRs are broadly subjected to operational determinism (ii) the cellular gene density is substantially higher in the surrounding environment of active LTRs compared to silent LTRs and (iii) the configuration of neighboring cellular genes differs between active and silent LTRs, showing an approximately 8 kb zone upstream of promoter LTRs characterized by a drastic reduction in sense cellular genes. These gathered observations are discussed in terms of virus/host adaptive strategies, and together with the methods and tools developed for this purpose, this work paves the way for further HERV transcriptome projects.

  9. Microarray-based sketches of the HERV transcriptome landscape.

    Directory of Open Access Journals (Sweden)

    Philippe Pérot

    Full Text Available Human endogenous retroviruses (HERVs are spread throughout the genome and their long terminal repeats (LTRs constitute a wide collection of putative regulatory sequences. Phylogenetic similarities and the profusion of integration sites, two inherent characteristics of transposable elements, make it difficult to study individual locus expression in a large-scale approach, and historically apart from some placental and testis-regulated elements, it was generally accepted that HERVs are silent due to epigenetic control. Herein, we have introduced a generic method aiming to optimally characterize individual loci associated with 25-mer probes by minimizing cross-hybridization risks. We therefore set up a microarray dedicated to a collection of 5,573 HERVs that can reasonably be assigned to a unique genomic position. We obtained a first view of the HERV transcriptome by using a composite panel of 40 normal and 39 tumor samples. The experiment showed that almost one third of the HERV repertoire is indeed transcribed. The HERV transcriptome follows tropism rules, is sensitive to the state of differentiation and, unexpectedly, seems not to correlate with the age of the HERV families. The probeset definition within the U3 and U5 regions was used to assign a function to some LTRs (i.e. promoter or polyA and revealed that (i autonomous active LTRs are broadly subjected to operational determinism (ii the cellular gene density is substantially higher in the surrounding environment of active LTRs compared to silent LTRs and (iii the configuration of neighboring cellular genes differs between active and silent LTRs, showing an approximately 8 kb zone upstream of promoter LTRs characterized by a drastic reduction in sense cellular genes. These gathered observations are discussed in terms of virus/host adaptive strategies, and together with the methods and tools developed for this purpose, this work paves the way for further HERV transcriptome projects.

  10. Gene ordering in partitive clustering using microarray expressions

    Indian Academy of Sciences (India)

    Shubhra Sankar Ray; Sanghamitra Bandyopadhyay; Sankar K Pal

    2007-08-01

    A central step in the analysis of gene expression data is the identification of groups of genes that exhibit similar expression patterns. Clustering and ordering the genes using gene expression data into homogeneous groups was shown to be useful in functional annotation, tissue classification, regulatory motif identification, and other applications. Although there is a rich literature on gene ordering in hierarchical clustering framework for gene expression analysis, there is no work addressing and evaluating the importance of gene ordering in partitive clustering framework, to the best knowledge of the authors. Outside the framework of hierarchical clustering, different gene ordering algorithms are applied on the whole data set, and the domain of partitive clustering is still unexplored with gene ordering approaches. A new hybrid method is proposed for ordering genes in each of the clusters obtained from partitive clustering solution, using microarray gene expressions. Two existing algorithms for optimally ordering cities in travelling salesman problem (TSP), namely, FRAG_GALK and Concorde, are hybridized individually with self organizing MAP to show the importance of gene ordering in partitive clustering framework. We validated our hybrid approach using yeast and fibroblast data and showed that our approach improves the result quality of partitive clustering solution, by identifying subclusters within big clusters, grouping functionally correlated genes within clusters, minimization of summation of gene expression distances, and the maximization of biological gene ordering using MIPS categorization. Moreover, 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.

  11. EMAAS: An extensible grid-based Rich Internet Application for microarray data analysis and management

    Directory of Open Access Journals (Sweden)

    Aitman T

    2008-11-01

    Full Text Available Abstract Background Microarray experimentation requires the application of complex analysis methods as well as the use of non-trivial computer technologies to manage the resultant large data sets. This, together with the proliferation of tools and techniques for microarray data analysis, makes it very challenging for a laboratory scientist to keep up-to-date with the latest developments in this field. Our aim was to develop a distributed e-support system for microarray data analysis and management. Results EMAAS (Extensible MicroArray Analysis System is a multi-user rich internet application (RIA providing simple, robust access to up-to-date resources for microarray data storage and analysis, combined with integrated tools to optimise real time user support and training. The system leverages the power of distributed computing to perform microarray analyses, and provides seamless access to resources located at various remote facilities. The EMAAS framework allows users to import microarray data from several sources to an underlying database, to pre-process, quality assess and analyse the data, to perform functional analyses, and to track data analysis steps, all through a single easy to use web portal. This interface offers distance support to users both in the form of video tutorials and via live screen feeds using the web conferencing tool EVO. A number of analysis packages, including R-Bioconductor and Affymetrix Power Tools have been integrated on the server side and are available programmatically through the Postgres-PLR library or on grid compute clusters. Integrated distributed resources include the functional annotation tool DAVID, GeneCards and the microarray data repositories GEO, CELSIUS and MiMiR. EMAAS currently supports analysis of Affymetrix 3' and Exon expression arrays, and the system is extensible to cater for other microarray and transcriptomic platforms. Conclusion EMAAS enables users to track and perform microarray data

  12. A non-parametric meta-analysis approach for combining independent microarray datasets: application using two microarray datasets pertaining to chronic allograft nephropathy

    Directory of Open Access Journals (Sweden)

    Archer Kellie J

    2008-02-01

    Full Text Available Abstract Background With the popularity of DNA microarray technology, multiple groups of researchers have studied the gene expression of similar biological conditions. Different methods have been developed to integrate the results from various microarray studies, though most of them rely on distributional assumptions, such as the t-statistic based, mixed-effects model, or Bayesian model methods. However, often the sample size for each individual microarray experiment is small. Therefore, in this paper we present a non-parametric meta-analysis approach for combining data from independent microarray studies, and illustrate its application on two independent Affymetrix GeneChip studies that compared the gene expression of biopsies from kidney transplant recipients with chronic allograft nephropathy (CAN to those with normal functioning allograft. Results The simulation study comparing the non-parametric meta-analysis approach to a commonly used t-statistic based approach shows that the non-parametric approach has better sensitivity and specificity. For the application on the two CAN studies, we identified 309 distinct genes that expressed differently in CAN. By applying Fisher's exact test to identify enriched KEGG pathways among those genes called differentially expressed, we found 6 KEGG pathways to be over-represented among the identified genes. We used the expression measurements of the identified genes as predictors to predict the class labels for 6 additional biopsy samples, and the predicted results all conformed to their pathologist diagnosed class labels. Conclusion We present a new approach for combining data from multiple independent microarray studies. This approach is non-parametric and does not rely on any distributional assumptions. The rationale behind the approach is logically intuitive and can be easily understood by researchers not having advanced training in statistics. Some of the identified genes and pathways have been

  13. Application of restriction display PCR technique in the preparation of cDNA microarray probes

    Institute of Scientific and Technical Information of China (English)

    Zhao-Hui Sun; Wen-Li Ma; Bao Zhang; Yi-Fei Peng; Wen-Ling Zheng

    2005-01-01

    AIM: To develop a simplified and efficient method for the preparation of hepatitis C virus (HCV) cDNA microarray probes.METHODS: With the technique of restriction display PCR (RD-PCR), restriction enzyme Sau3A I was chosen to digest the full-length HCV cDNAs. The products were classified and re-amplified by RD-PCR. We separated the differential genes by polyacrylamide gel electrophoresis and silver staining. Single bands cut out from the polyacrylamide gel were isolated. The third-round PCR was performed using the single bands as PCR template.The RD-PCR fragments were purified and cloned into the pMD18-T vector. The recombinant plasmids were extracted from positive clones, and the target gene fragments were sequenced. The cDNA microarray was prepared by spotting RD-PCR products to the surface of amino-modified glass slides using a robot. We validated the detection of microarray by hybridization and sequence analysis.RESULTS: A total of 24 different cDNA fragments ranging from 200 to 800 bp were isolated and sequenced,which were the specific gene fragments of HCV. These fragments could be further used as probes in microarray preparation. The diagnostic capability of the microarray was evaluated after the washing and scanning steps. The results of hybridization and sequence analysis showed that the specificity, sensitivity, accuracy, reproducibility,and linearity in detecting HCV RNA were satisfactory.CONCLUSION: The RD-PCR technique is of great value in obtaining a large number of size-comparable gene probes, which provides a speedy protocol in generating probes for the preparation of microarrays. Microarray prepared as such could be further optimized and applied in the clinical diagnosis of HCV.

  14. M-BISON: Microarray-based integration of data sources using networks

    Directory of Open Access Journals (Sweden)

    Altman Russ B

    2008-04-01

    Full Text Available Abstract Background The accurate detection of differentially expressed (DE genes has become a central task in microarray analysis. Unfortunately, the noise level and experimental variability of microarrays can be limiting. While a number of existing methods partially overcome these limitations by incorporating biological knowledge in the form of gene groups, these methods sacrifice gene-level resolution. This loss of precision can be inappropriate, especially if the desired output is a ranked list of individual genes. To address this shortcoming, we developed M-BISON (Microarray-Based Integration of data SOurces using Networks, a formal probabilistic model that integrates background biological knowledge with microarray data to predict individual DE genes. Results M-BISON improves signal detection on a range of simulated data, particularly when using very noisy microarray data. We also applied the method to the task of predicting heat shock-related differentially expressed genes in S. cerevisiae, using an hsf1 mutant microarray dataset and conserved yeast DNA sequence motifs. Our results demonstrate that M-BISON improves the analysis quality and makes predictions that are easy to interpret in concert with incorporated knowledge. Specifically, M-BISON increases the AUC of DE gene prediction from .541 to .623 when compared to a method using only microarray data, and M-BISON outperforms a related method, GeneRank. Furthermore, by analyzing M-BISON predictions in the context of the background knowledge, we identified YHR124W as a potentially novel player in the yeast heat shock response. Conclusion This work provides a solid foundation for the principled integration of imperfect biological knowledge with gene expression data and other high-throughput data sources.

  15. Microarrays for genotyping human group a rotavirus by multiplex capture and type-specific primer extension.

    Science.gov (United States)

    Lovmar, Lovisa; Fock, Caroline; Espinoza, Felix; Bucardo, Filemon; Syvänen, Ann-Christine; Bondeson, Kåre

    2003-11-01

    Human group A rotavirus (HRV) is the major cause of severe gastroenteritis in infants worldwide. HRV shares the feature of a high degree of genetic diversity with many other RNA viruses, and therefore, genotyping of this organism is more complicated than genotyping of more stable DNA viruses. We describe a novel microarray-based method that allows high-throughput genotyping of RNA viruses with a high degree of polymorphism by multiplex capture and type-specific extension on microarrays. Denatured reverse transcription (RT)-PCR products derived from two outer capsid genes of clinical isolates of HRV were hybridized to immobilized capture oligonucleotides representing the most commonly occurring P and G genotypes on a microarray. Specific primer extension of the type-specific capture oligonucleotides was applied to incorporate the fluorescent nucleotide analogue cyanine 5-labeled dUTP as a detectable label. Laser scanning and fluorescence detection of the microarrays was followed by visual or computer-assisted interpretation of the fluorescence patterns generated on the microarrays. Initially, the method detected HRV in all 40 samples and correctly determined both the G and the P genotypes of 35 of the 40 strains analyzed. After modification by inclusion of additional capture oligonucleotides specific for the initially unassigned genotypes, all genotypes could be correctly defined. The results of genotyping with the microarray fully agreed with the results obtained by nucleotide sequence analysis and sequence-specific multiplex RT-PCR. Owing to its robustness, simplicity, and general utility, the microarray-based method may gain wide applicability for the genotyping of microorganisms, including highly variable RNA and DNA viruses.

  16. Microarrays for Genotyping Human Group A Rotavirus by Multiplex Capture and Type-Specific Primer Extension

    Science.gov (United States)

    Lovmar, Lovisa; Fock, Caroline; Espinoza, Felix; Bucardo, Filemon; Syvänen, Ann-Christine; Bondeson, Kåre

    2003-01-01

    Human group A rotavirus (HRV) is the major cause of severe gastroenteritis in infants worldwide. HRV shares the feature of a high degree of genetic diversity with many other RNA viruses, and therefore, genotyping of this organism is more complicated than genotyping of more stable DNA viruses. We describe a novel microarray-based method that allows high-throughput genotyping of RNA viruses with a high degree of polymorphism by multiplex capture and type-specific extension on microarrays. Denatured reverse transcription (RT)-PCR products derived from two outer capsid genes of clinical isolates of HRV were hybridized to immobilized capture oligonucleotides representing the most commonly occurring P and G genotypes on a microarray. Specific primer extension of the type-specific capture oligonucleotides was applied to incorporate the fluorescent nucleotide analogue cyanine 5-labeled dUTP as a detectable label. Laser scanning and fluorescence detection of the microarrays was followed by visual or computer-assisted interpretation of the fluorescence patterns generated on the microarrays. Initially, the method detected HRV in all 40 samples and correctly determined both the G and the P genotypes of 35 of the 40 strains analyzed. After modification by inclusion of additional capture oligonucleotides specific for the initially unassigned genotypes, all genotypes could be correctly defined. The results of genotyping with the microarray fully agreed with the results obtained by nucleotide sequence analysis and sequence-specific multiplex RT-PCR. Owing to its robustness, simplicity, and general utility, the microarray-based method may gain wide applicability for the genotyping of microorganisms, including highly variable RNA and DNA viruses. PMID:14605152

  17. Splicing-Sensitive DNA-Microarrays: Peculiarities and Applicationin Biomedical Research (Review

    Directory of Open Access Journals (Sweden)

    D.I. Knyazev

    2015-12-01

    Full Text Available Alternative splicing (АS provides a variety of protein and mature mRNA isoforms encoded by a single gene, and is the essential component of cell and tissue differentiation and functioning. DNA-microarrays are highly productive transcriptome research technique both at the level of total gene expression assessment and alternatively spliced mRNA isoforms exploration. The study of AS patterns requires thorough probe design to achieve appropriate accuracy of the analysis. There are two types of splicing-sensitive DNA-microarrays. The first type contain probes targeted to internal exonic sequences (exon bodies; the second type contain probes targeted to exon bodies and exon–exon and exon–intron junctions. So, the first section focused on probe sequence design, general features of splicing-sensitive DNA-microarrays and their main advantages and limitations. The results of AS research obtained using DNA-microarrays have been reviewed in special section. In particular, DNA-microarrays were used to reveal a number pre-mRNA processing and splicing mechanisms, to investigate AS patterns associated with cancer, cell and tissue differentiation. Splicing machinery regulation was demonstrated to be an essential step during carcinogenesis and differentiation. The examples of application of splicing-sensitive DNA-microarrays for diagnostic markers discovering and pathology mechanism elucidation were also reviewed. Investigations of AS role in pluripotency, stem cell commitment, immune and infected cells functioning during immune response are the promising future directions. Splicing-sensitive DNA-microarrays are relatively inexpensive but powerful research tool that give reason to suppose their introduction in clinical practice within the next few years.

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

    Directory of Open Access Journals (Sweden)

    Kogenaru Sunitha

    2012-11-01

    Full Text Available Abstract 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  20. Filtering for increased power for microarray data analysis

    Directory of Open Access Journals (Sweden)

    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

  1. A novel biclustering algorithm of binary microarray data: BiBinCons and BiBinAlter

    OpenAIRE

    Saber, Haifa Ben; Elloumi, Mourad

    2015-01-01

    The biclustering of microarray data has been the subject of a large research. No one of the existing biclustering algorithms is perfect. The construction of biologically significant groups of biclusters for large microarray data is still a problem that requires a continuous work. Biological validation of biclusters of microarray data is one of the most important open issues. So far, there are no general guidelines in the literature on how to validate biologically extracted biclusters. In this...

  2. DNA microarrays immobilized on unmodified plastics in a microfluidic biochip for rapid typing of Avian Influenza Virus

    DEFF Research Database (Denmark)

    Yi, Sun; Perch-Nielsen, Ivan R.; Dufva, Martin;

    2011-01-01

    Polymers are widely used for microfluidic systems, but fabrication of microarrays on such materials often requires complicated chemical surface modifications, which hinders the integration of microarrays into microfluidic systems. In this paper, we demonstrate that UV irradiation can be used......, a portable cyclic olefin copolymer (COC) microarray device containing eight individually addressable microfluidic channels was developed for fast identification of Avian Influenza Virus (AIV) by DNA hybridization. This plastic biochip offers benefits of low fabrication cost and parallel processing...

  3. 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.

  4. Science Letters: Application of new tissue microarrayer-ZM-1 without recipient paraffin block

    Institute of Scientific and Technical Information of China (English)

    MENG Pan-qing; HOU Gang; ZHOU Gui-ying; PENG Jia-ping; DONG Qi; ZHENG Shu

    2005-01-01

    The ZM-1 tissue microarrayer designed by our groups is manufactured in stainless steel and brass and contains many features that make TMA (tissue microarray) paraffin blocks construction faster and more convenient. By means of ZM-1 tissue microarrayer, biopsy needles are used to punch the donor tissue specimens respectively. All the needles with the punched specimen cylinders are arrayed into the array-board, with an array of small holes dug to fit the needles. All the specimen cylinders arraying and the TMA paraffin block shaping are finished in only one step so that the specimen cylinders and the paraffin of the TMA block can very easily be incorporated and the recipient paraffin blocks need not be made in advance, and the paraffin used is the same as that for conventional pathology purpose. ZM-1 tissue microarrayer is easy to be manufactured, does not need any precision location system, and so is much cheaper than the currently used instrument. Our method's relatively cheap and simple ZM- 1 tissue microarrayer technique of constructing TMA paraffin block may facilitate popularization of the TMA technology.

  5. 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. PMID:26397421

  6. 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.

  7. A proposed metric for assessing the measurement quality of individual microarrays

    Directory of Open Access Journals (Sweden)

    Scheirer Katherine E

    2006-01-01

    Full Text Available Abstract Background High-density microarray technology is increasingly applied to study gene expression levels on a large scale. Microarray experiments rely on several critical steps that may introduce error and uncertainty in analyses. These steps include mRNA sample extraction, amplification and labeling, hybridization, and scanning. In some cases this may be manifested as systematic spatial variation on the surface of microarray in which expression measurements within an individual array may vary as a function of geographic position on the array surface. Results We hypothesized that an index of the degree of spatiality of gene expression measurements associated with their physical geographic locations on an array could indicate the summary of the physical reliability of the microarray. We introduced a novel way to formulate this index using a statistical analysis tool. Our approach regressed gene expression intensity measurements on a polynomial response surface of the microarray's Cartesian coordinates. We demonstrated this method using a fixed model and presented results from real and simulated datasets. Conclusion We demonstrated the potential of such a quantitative metric for assessing the reliability of individual arrays. Moreover, we showed that this procedure can be incorporated into laboratory practice as a means to set quality control specifications and as a tool to determine whether an array has sufficient quality to be retained in terms of spatial correlation of gene expression measurements.

  8. Construction and evaluation of a whole genome microarray of Chlamydomonas reinhardtii

    Directory of Open Access Journals (Sweden)

    Toepel Jörg

    2011-11-01

    Full Text Available Abstract Background Chlamydomonas reinhardtii is widely accepted as a model organism regarding photosynthesis, circadian rhythm, cell mobility, phototaxis, and biotechnology. The complete annotation of the genome allows transcriptomic studies, however a new microarray platform was needed. Based on the completed annotation of Chlamydomonas reinhardtii a new microarray on an Agilent platform was designed using an extended JGI 3.1 genome data set which included 15000 transcript models. Results In total 44000 probes were determined (3 independent probes per transcript model covering 93% of the transcriptome. Alignment studies with the recently published AUGUSTUS 10.2 annotation confirmed 11000 transcript models resulting in a very good coverage of 70% of the transcriptome (17000. Following the estimation of 10000 predicted genes in Chlamydomonas reinhardtii our new microarray, nevertheless, covers the expected genome by 90-95%. Conclusions To demonstrate the capabilities of the new microarray, we analyzed transcript levels for cultures grown under nitrogen as well as sulfate limitation, and compared the results with recently published microarray and RNA-seq data. We could thereby confirm previous results derived from data on nutrient-starvation induced gene expression of a group of genes related to protein transport and adaptation of the metabolism as well as genes related to efficient light harvesting, light energy distribution and photosynthetic electron transport.

  9. Development and application of the active surveillance of pathogens microarray to monitor bacterial gene flux

    Directory of Open Access Journals (Sweden)

    Hinds Jason

    2008-10-01

    Full Text Available Abstract Background Human and animal health is constantly under threat by emerging pathogens that have recently acquired genetic determinants that enhance their survival, transmissibility and virulence. We describe the construction and development of an Active Surveillance of Pathogens (ASP oligonucleotide microarray, designed to 'actively survey' the genome of a given bacterial pathogen for virulence-associated genes. Results The microarray consists of 4958 reporters from 151 bacterial species and include genes for the identification of individual bacterial species as well as mobile genetic elements (transposons, plasmid and phage, virulence genes and antibiotic resistance genes. The ASP microarray was validated with nineteen bacterial pathogens species, including Francisella tularensis, Clostridium difficile, Staphylococcus aureus, Enterococcus faecium and Stenotrophomonas maltophilia. The ASP microarray identified these bacteria, and provided information on potential antibiotic resistance (eg sufamethoxazole resistance and sulfonamide resistance and virulence determinants including genes likely to be acquired by horizontal gene transfer (e.g. an alpha-haemolysin. Conclusion The ASP microarray has potential in the clinic as a diagnostic tool, as a research tool for both known and emerging pathogens, and as an early warning system for pathogenic bacteria that have been recently modified either naturally or deliberately.

  10. Fish and chips: Various methodologies demonstrate utility of a 16,006-gene salmonid microarray

    Directory of Open Access Journals (Sweden)

    Nelson Colleen C

    2005-09-01

    Full Text Available Abstract Background We have developed and fabricated a salmonid microarray containing cDNAs representing 16,006 genes. The genes spotted on the array have been stringently selected from Atlantic salmon and rainbow trout expressed sequence tag (EST databases. The EST databases presently contain over 300,000 sequences from over 175 salmonid cDNA libraries derived from a wide variety of tissues and different developmental stages. In order to evaluate the utility of the microarray, a number of hybridization techniques and screening methods have been developed and tested. Results We have analyzed and evaluated the utility of a microarray containing 16,006 (16K salmonid cDNAs in a variety of potential experimental settings. We quantified the amount of transcriptome binding that occurred in cross-species, organ complexity and intraspecific variation hybridization studies. We also developed a methodology to rapidly identify and confirm the contents of a bacterial artificial chromosome (BAC library containing Atlantic salmon genomic DNA. Conclusion We validate and demonstrate the usefulness of the 16K microarray over a wide range of teleosts, even for transcriptome targets from species distantly related to salmonids. We show the potential of the use of the microarray in a variety of experimental settings through hybridization studies that examine the binding of targets derived from different organs and tissues. Intraspecific variation in transcriptome expression is evaluated and discussed. Finally, BAC hybridizations are demonstrated as a rapid and accurate means to identify gene content.

  11. poolMC: Smart pooling of mRNA samples in microarray experiments

    Directory of Open Access Journals (Sweden)

    Schiefelbein John

    2010-06-01

    Full Text Available Abstract Background Typically, pooling of mRNA samples in microarray experiments implies mixing mRNA from several biological-replicate samples before hybridization onto a microarray chip. Here we describe an alternative smart pooling strategy in which different samples, not necessarily biological replicates, are pooled in an information theoretic efficient way. Further, each sample is tested on multiple chips, but always in pools made up of different samples. The end goal is to exploit the compressibility of microarray data to reduce the number of chips used and increase the robustness to noise in measurements. Results A theoretical framework to perform smart pooling of mRNA samples in microarray experiments was established and the software implementation of the pooling and decoding algorithms was developed in MATLAB. A proof-of-concept smart pooled experiment was performed using validated biological samples on commercially available gene chips. Differential-expression analysis of the smart pooled data was performed and compared against the unpooled control experiment. Conclusions The theoretical developments and experimental demonstration in this paper provide a useful starting point to investigate smart pooling of mRNA samples in microarray experiments. Although the smart pooled experiment did not compare favorably with the control, the experiment highlighted important conditions for the successful implementation of smart pooling - linearity of measurements, sparsity in data, and large experiment size.

  12. 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.

  13. Microarray for Identification of the Chiropteran Host Species of Rabies Virus in Canada

    Directory of Open Access Journals (Sweden)

    Tara Furukawa-Stoffer

    2013-05-01

    Full Text Available Species identification through genetic barcoding can augment traditional taxonomic methods, which rely on morphological features of the specimen. Such approaches are especially valuable when specimens are in poor condition or comprise very limited material, a situation that often applies to chiropteran (bat specimens submitted to the Canadian Food Inspection Agency for rabies diagnosis. Coupled with phenotypic plasticity of many species and inconclusive taxonomic keys, species identification using only morphological traits can be challenging. In this study, a microarray assay with associated PCR of the mitochondrial cytochrome c oxidase subunit I (COI gene was developed for differentiation of 14 bat species submitted to the Canadian Food Inspection Agency from 1985–2012 for rabies diagnosis. The assay was validated with a reference collection of DNA from 153 field samples, all of which had been barcoded previously. The COI gene from 152 samples which included multiple specimens of each target species were successfully amplified by PCR and accurately identified by the microarray. One sample that was severely decomposed failed to amplify with PCR primers developed in this study, but amplified weakly after switching to alternate primers and was accurately typed by the microarray. Thus, the chiropteran microarray was able to accurately differentiate between the 14 species of Canadian bats targeted. This PCR and microarray assay would allow unequivocal identification to species of most, if not all, bat specimens submitted for rabies diagnosis in Canada.

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

    Directory of Open Access Journals (Sweden)

    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.

  15. Innovative instrumentation for microarray scanning and analysis: application for characterization of oligonucleotide duplexes behavior.

    Science.gov (United States)

    Khomyakova, E B; Dreval, E V; Tran-Dang, M; Potier, M C; Soussaline, F P

    2004-05-01

    Accuracy in microarray technology requires new approaches to microarray reader development. A microarray reader system (optical scanning array or OSA reader) based on automated microscopy with large field of view, high speed 3 axis scanning at multiple narrow-band spectra of excitation light has been developed. It allows fast capture of high-resolution, multi-fluorescence images and is characterized by a linear dynamic range and sensitivity comparable to commonly used photo-multiplier tube (PMT)-based laser scanner. Controlled by high performance software, the instrument can be used for scanning and quantitative analysis of any type of dry microarray. Studies implying temperature-controlled hybridization chamber containing a microarray can also be performed. This enables the registration of kinetics and melting curves. This feature is required in a wide range of on-chip chemical and enzymatic reactions including on-chip PCR amplification. We used the OSA reader for the characterization of hybridization and melting behaviour of oligonucleotide:oligonucleotide duplexes on three-dimensional Code Link slides. PMID:15209342

  16. Application of Microarray Technology and Softcomputing in Cancer Biology : A Review

    Directory of Open Access Journals (Sweden)

    P.K.Vaishali & Dr. A.vinayababu

    2011-10-01

    Full Text Available DNA microarray technology has emerged as a boon to the scientific community in understanding thegrowth and development of life as well as in widening their knowledge in exploring the geneticcauses of anomalies occurring in the working of the human body. microarray technology makesbiologists be capable of monitoring expression of thousands of genes in a single experiment on asmall chip. Extracting useful knowledge and info from these microarray has attracted the attention ofmany biologists and computer scientists. Knowledge engineering has revolutionalized the way inwhich the medical data is being looked at. Soft computing is a branch of computer science capable ofanalyzing complex medical data. Advances in the area of microarray –based expression analysishave led to the promise of cancer diagnosis using new molecular based approaches. Many studiesand methodologies have come up which analyszes the gene espression data by using thetechniques in data mining such as feature selection, classification, clustering etc. emboiding the softcomputing methods for more accuracy. This review is an attempt to look at the recent advances incancer research with DNA microarray technology , data mining and soft computing techniques.

  17. affyPara-a Bioconductor Package for Parallelized Preprocessing Algorithms of Affymetrix Microarray Data.

    Science.gov (United States)

    Schmidberger, Markus; Vicedo, Esmeralda; Mansmann, Ulrich

    2009-07-22

    Microarray data repositories as well as large clinical applications of gene expression allow to analyse several hundreds of microarrays at one time. The preprocessing of large amounts of microarrays is still a challenge. The algorithms are limited by the available computer hardware. For example, building classification or prognostic rules from large microarray sets will be very time consuming. Here, preprocessing has to be a part of the cross-validation and resampling strategy which is necessary to estimate the rule's prediction quality honestly.This paper proposes the new Bioconductor package affyPara for parallelized preprocessing of Affymetrix microarray data. Partition of data can be applied on arrays and parallelization of algorithms is a straightforward consequence. The partition of data and distribution to several nodes solves the main memory problems and accelerates preprocessing by up to the factor 20 for 200 or more arrays.affyPara is a free and open source package, under GPL license, available form the Bioconductor project at www.bioconductor.org. A user guide and examples are provided with the package.

  18. 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.

  19. A tiling microarray for global analysis of chloroplast genome expression in cucumber and other plants

    Directory of Open Access Journals (Sweden)

    Pląder Wojciech

    2011-09-01

    Full Text Available Abstract Plastids are small organelles equipped with their own genomes (plastomes. Although these organelles are involved in numerous plant metabolic pathways, current knowledge about the transcriptional activity of plastomes is limited. To solve this problem, we constructed a plastid tiling microarray (PlasTi-microarray consisting of 1629 oligonucleotide probes. The oligonucleotides were designed based on the cucumber chloroplast genomic sequence and targeted both strands of the plastome in a non-contiguous arrangement. Up to 4 specific probes were designed for each gene/exon, and the intergenic regions were covered regularly, with 70-nt intervals. We also developed a protocol for direct chemical labeling and hybridization of as little as 2 micrograms of chloroplast RNA. We used this protocol for profiling the expression of the cucumber chloroplast plastome on the PlasTi-microarray. Owing to the high sequence similarity of plant plastomes, the newly constructed microarray can be used to study plants other than cucumber. Comparative hybridization of chloroplast transcriptomes from cucumber, Arabidopsis, tomato and spinach showed that the PlasTi-microarray is highly versatile.

  20. Signal oscillation is another reason for variability in microarray-based gene expression quantification.

    Directory of Open Access Journals (Sweden)

    Raghvendra Singh

    Full Text Available Microarrays have been widely used for various biological applications, such as, gene expression profiling, determination of SNPs, and disease profiling. However, quantification and analysis of microarray data have been a challenge. Previously, by taking into account translational and rotational diffusion of the target DNA, we have shown that the rate of hybridization depends on its size. Here, by mathematical modeling of surface diffusion of transcript, we show that the dynamics of hybridization on DNA microarray surface is inherently oscillatory and the amplitude of oscillation depends on fluid velocity. We found that high fluid velocity enhances the signal without affecting the background, and reduces the oscillation, thereby reducing likelihood of inter- and intra-experiment variability. We further show that a strong probe reduces dependence of signal-to-noise ratio on probe strength, decreasing inter-microarray variability. On the other hand, weaker probes are required for SNP detection. Therefore, we recommend high fluid velocity and strong probes for all microarray applications except determination of SNPs. For SNP detection, we recommend high fluid velocity with weak probe on the spot. We also recommend a surface with high adsorption and desorption rates of transcripts.

  1. An event-specific DNA microarray to identify genetically modified organisms in processed foods.

    Science.gov (United States)

    Kim, Jae-Hwan; Kim, Su-Youn; Lee, Hyungjae; Kim, Young-Rok; Kim, Hae-Yeong

    2010-05-26

    We developed an event-specific DNA microarray system to identify 19 genetically modified organisms (GMOs), including two GM soybeans (GTS-40-3-2 and A2704-12), thirteen GM maizes (Bt176, Bt11, MON810, MON863, NK603, GA21, T25, TC1507, Bt10, DAS59122-7, TC6275, MIR604, and LY038), three GM canolas (GT73, MS8xRF3, and T45), and one GM cotton (LLcotton25). The microarray included 27 oligonucleotide probes optimized to identify endogenous reference targets, event-specific targets, screening targets (35S promoter and nos terminator), and an internal target (18S rRNA gene). Thirty-seven maize-containing food products purchased from South Korean and US markets were tested for the presence of GM maize using this microarray system. Thirteen GM maize events were simultaneously detected using multiplex PCR coupled with microarray on a single chip, at a limit of detection of approximately 0.5%. Using the system described here, we detected GM maize in 11 of the 37 food samples tested. These results suggest that an event-specific DNA microarray system can reliably detect GMOs in processed foods.

  2. Microarray-based genomic profiling as a diagnostic tool in acute lymphoblastic leukemia.

    Science.gov (United States)

    Simons, Annet; Stevens-Kroef, Marian; El Idrissi-Zaynoun, Najat; van Gessel, Sabine; Weghuis, Daniel Olde; van den Berg, Eva; Waanders, Esmé; Hoogerbrugge, Peter; Kuiper, Roland; van Kessel, Ad Geurts

    2011-12-01

    In acute lymphoblastic leukemia (ALL) specific genomic abnormalities provide important clinical information. In most routine clinical diagnostic laboratories conventional karyotyping, in conjunction with targeted screens using e.g., fluorescence in situ hybridization (FISH), is currently considered as the gold standard to detect such aberrations. Conventional karyotyping, however, is limited in its resolution and yield, thus hampering the genetic diagnosis of ALL. We explored whether microarray-based genomic profiling would be feasible as an alternative strategy in a routine clinical diagnostic setting. To this end, we compared conventional karyotypes with microarray-deduced copy number aberration (CNA) karyotypes in 60 ALL cases. Microarray-based genomic profiling resulted in a CNA detection rate of 90%, whereas for conventional karyotyping this was 61%. In addition, many small (< 5 Mb) genetic lesions were encountered, frequently harboring clinically relevant ALL-related genes such as CDKN2A/B, ETV6, PAX5, and IKZF1. From our data we conclude that microarray-based genomic profiling serves as a robust tool in the genetic diagnosis of ALL, outreaching conventional karyotyping in CNA detection both in terms of sensitivity and specificity. We also propose a practical workflow for a comprehensive and objective interpretation of CNAs obtained through microarray-based genomic profiling, thereby facilitating its application in a routine clinical diagnostic setting.

  3. A conceptual and practical overview of cDNA microarray technology: implications for basic and clinical sciences

    Directory of Open Access Journals (Sweden)

    V. de Mello-Coelho

    2005-10-01

    Full Text Available cDNA microarray is an innovative technology that facilitates the analysis of the expression of thousands of genes simultaneously. The utilization of this methodology, which is rapidly evolving, requires a combination of expertise from the biological, mathematical and statistical sciences. In this review, we attempt to provide an overview of the principles of cDNA microarray technology, the practical concerns of the analytical processing of the data obtained, the correlation of this methodology with other data analysis methods such as immunohistochemistry in tissue microarrays, and the cDNA microarray application in distinct areas of the basic and clinical sciences.

  4. StressDB: A Locally Installable Web-Based Relational Microarray Database Designed for Small User Communities

    OpenAIRE

    Madhusmita Mitra; Nigam Shah; Lukas Mueller; Scuth Pin; Nina Fedoroff

    2002-01-01

    We have built a microarray database, StressDB, for management of microarray data from our studies on stress-modulated genes in Arabidopsis. StressDB provides small user groups with a locally installable web-based relational microarray database. It has a simple and intuitive architecture and has been designed for cDNA microarray technology users. StressDB uses Windows™ 2000 as the centralized database server with Oracle™ 8i as the relational database management system. It allows users to manag...

  5. Fluidic and air-stable supported lipid bilayer and cell-mimicking microarrays.

    Science.gov (United States)

    Deng, Yang; Wang, Yini; Holtz, Bryan; Li, Jingyi; Traaseth, Nathan; Veglia, Gianluigi; Stottrup, Benjamin J; Elde, Robert; Pei, Duanqing; Guo, Athena; Zhu, X-Y

    2008-05-14

    As drug delivery, therapy, and medical imaging are becoming increasingly cell-specific, there is a critical need for high fidelity and high-throughput screening methods for cell surface interactions. Cell membrane-mimicking surfaces, i.e., supported lipid bilayers (SLBs), are currently not sufficiently robust to meet this need. Here we describe a method of forming fluidic and air-stable SLBs through tethered and dispersed cholesterol groups incorporated into the bottom leaflet. Achieving air stability allows us to easily fabricate SLB microarrays from direct robotic spotting of vesicle solutions. We demonstrate their application as cell membrane-mimicking microarrays by reconstituting peripheral as well as integral membrane components that can be recognized by their respective targets. These demonstrations establish the viability of the fluidic and air-stable SLB platform for generating content microarrays in high throughput studies, e.g., the screening of drugs and nanomedicine targeting cell surface receptors.

  6. A Hybrid Reduction Approach for Enhancing Cancer Classification of Microarray Data

    Directory of Open Access Journals (Sweden)

    Abeer M. Mahmoud

    2014-10-01

    Full Text Available This paper presents a novel hybrid machine learning (MLreduction approach to enhance cancer classification accuracy of microarray data based on two ML gene ranking techniques (T-test and Class Separability (CS. The proposed approach is integrated with two ML classifiers; K-nearest neighbor (KNN and support vector machine (SVM; for mining microarray gene expression profiles. Four public cancer microarray databases are used for evaluating the proposed approach and successfully accomplish the mining process. These are Lymphoma, Leukemia SRBCT, and Lung Cancer. The strategy to select genes only from the training samples and totally excluding the testing samples from the classifier building process is utilized for more accurate and validated results. Also, the computational experiments are illustrated in details and comprehensively presented with literature related results. The results showed that the proposed reduction approach reached promising results of the number of genes supplemented to the classifiers as well as the classification accuracy.

  7. 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

  8. How the RNA isolation method can affect microRNA microarray results

    DEFF Research Database (Denmark)

    Podolska, Agnieszka; Kaczkowski, Bogumil; Litman, Thomas;

    2011-01-01

    RNA 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...... 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.......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 micro...

  9. A Hybrid Multi Objective Particle Swarm Optimization Method to Discover Biclusters in Microarray Data

    CERN Document Server

    lashkargir, Mohsen; Dastjerdi, Ahmad Baraani

    2009-01-01

    In recent years, with the development of microarray technique, discovery of useful knowledge from microarray data has become very important. Biclustering is a very useful data mining technique for discovering genes which have similar behavior. In microarray data, several objectives have to be optimized simultaneously and often these objectives are in conflict with each other. A Multi Objective model is capable of solving such problems. Our method proposes a Hybrid algorithm which is based on the Multi Objective Particle Swarm Optimization for discovering biclusters in gene expression data. In our method, we will consider a low level of overlapping amongst the biclusters and try to cover all elements of the gene expression matrix. Experimental results in the bench mark database show a significant improvement in both overlap among biclusters and coverage of elements in the gene expression matrix.

  10. Minimum Information About a Microarray Experiment (MIAME – Successes, Failures, Challenges

    Directory of Open Access Journals (Sweden)

    Alvis Brazma

    2009-01-01

    Full Text Available The Minimum Information About a Microarray Experiment (known as MIAME guidelines describe information that needs to be provided to enable the interpretation of the results of a microarray-based experiment unambiguously. The MIAME guidelines were developed by the Microarray Gene Expression Data (MGED Society. Since the MIAME position paper was published in 2001, it has been cited in the scientific literature well over a thousand times. MIAME has been replicated for many other technologies, the major data repositories are supporting MIAME, and most scientific journals have adopted MIAME guidelines as a requirement for publishing. With the advent of new-generation sequencing technology, MIAME faces new challenges. To address this, the MGED Society has proposed new guidelines, i.e., Minimum Information about a high-throughput SeQuencing Experiment (MINSEQE. Here we present analysis of the reasons for the success of MIAME, as well as discuss where it has failed, and the challenges it faces.

  11. A novel approach to the clustering of microarray data via nonparametric density estimation

    Directory of Open Access Journals (Sweden)

    Risso Davide

    2011-02-01

    Full Text Available Abstract Background Cluster analysis is a crucial tool in several biological and medical studies dealing with microarray data. Such studies pose challenging statistical problems due to dimensionality issues, since the number of variables can be much higher than the number of observations. Results Here, we present a general framework to deal with the clustering of microarray data, based on a three-step procedure: (i gene filtering; (ii dimensionality reduction; (iii clustering of observations in the reduced space. Via a nonparametric model-based clustering approach we obtain promising results both in simulated and real data. Conclusions The proposed algorithm is a simple and effective tool for the clustering of microarray data, in an unsupervised setting.

  12. 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.

  13. DNA Microarray Assay Helps to Identify Functional Genes Specific for Leukemia Stem Cells

    Directory of Open Access Journals (Sweden)

    Haojian Zhang

    2013-01-01

    Full Text Available Chronic myeloid leukemia (CML is a myeloproliferative disease derived from an abnormal hematopoietic stem cell (HSC and is consistently associated with the formation of Philadelphia (Ph chromosome. Tyrosine kinase inhibitors (TKIs are highly effective in treating chronic phase CML but do not eliminate leukemia stem cells (LSCs, which are believed to be related to disease relapse. Therefore, one major challenge in the current CML research is to understand the biology of LSCs and to identify the molecular difference between LSCs and its normal stem cell counterparts. Comparing the gene expression profiles between LSCs and normal HSCs by DNA microarray assay is a systematic and unbiased approach to address this issue. In this paper, we present a DNA microarray dataset for CML LSCs and normal HSCs to show that the microarray assay will benefit the current and future studies of the biology of CML stem cells.

  14. The Potentials and Pitfalls of Microarrays in Neglected Tropical Diseases: A Focus on Human Filarial Infections.

    Science.gov (United States)

    Kwarteng, Alexander; Ahuno, Samuel Terkper

    2016-01-01

    Data obtained from expression microarrays enables deeper understanding of the molecular signatures of infectious diseases. It provides rapid and accurate information on how infections affect the clustering of gene expression profiles, pathways and networks that are transcriptionally active during various infection states compared to conventional diagnostic methods, which primarily focus on single genes or proteins. Thus, microarray technologies offer advantages in understanding host-parasite interactions associated with filarial infections. More importantly, the use of these technologies can aid diagnostics and helps translate current genomic research into effective treatment and interventions for filarial infections. Studying immune responses via microarray following infection can yield insight into genetic pathways and networks that can have a profound influence on the development of anti-parasitic vaccines. PMID:27600086

  15. 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

    Several preprocessing algorithms for Affymetrix gene expression microarrays have been developed, and their performance on spike-in data sets has been evaluated previously. However, a comprehensive comparison of preprocessing algorithms on samples taken under research conditions has not been...... that were most consistent with RT-PCR measurements, although the difference in performance between most of the algorithms was not statistically significant. CONCLUSIONS/SIGNIFICANCE: Our results support the choice of PLIER+16 for the preprocessing of clinical Affymetrix microarray data. However, other...... 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...

  16. 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.

  17. Empirical Bayes ranking and selection methods via semiparametric hierarchical mixture models in microarray studies.

    Science.gov (United States)

    Noma, Hisashi; Matsui, Shigeyuki

    2013-05-20

    The main purpose of microarray studies is screening of differentially expressed genes as candidates for further investigation. Because of limited resources in this stage, prioritizing genes are relevant statistical tasks in microarray studies. For effective gene selections, parametric empirical Bayes methods for ranking and selection of genes with largest effect sizes have been proposed (Noma et al., 2010; Biostatistics 11: 281-289). The hierarchical mixture model incorporates the differential and non-differential components and allows information borrowing across differential genes with separation from nuisance, non-differential genes. In this article, we develop empirical Bayes ranking methods via a semiparametric hierarchical mixture model. A nonparametric prior distribution, rather than parametric prior distributions, for effect sizes is specified and estimated using the "smoothing by roughening" approach of Laird and Louis (1991; Computational statistics and data analysis 12: 27-37). We present applications to childhood and infant leukemia clinical studies with microarrays for exploring genes related to prognosis or disease progression.

  18. Improved statistical analysis of budding yeast TAG microarrays revealed by defined spike-in pools.

    Science.gov (United States)

    Peyser, Brian D; Irizarry, Rafael A; Tiffany, Carol W; Chen, Ou; Yuan, Daniel S; Boeke, Jef D; Spencer, Forrest A

    2005-09-15

    Saccharomyces cerevisiae knockout collection TAG microarrays are an emergent platform for rapid, genome-wide functional characterization of yeast genes. TAG arrays report abundance of unique oligonucleotide 'TAG' sequences incorporated into each deletion mutation of the yeast knockout collection, allowing measurement of relative strain representation across experimental conditions for all knockout mutants simultaneously. One application of TAG arrays is to perform genome-wide synthetic lethality screens, known as synthetic lethality analyzed by microarray (SLAM). We designed a fully defined spike-in pool to resemble typical SLAM experiments and performed TAG microarray hybridizations. We describe a method for analyzing two-color array data to efficiently measure the differential knockout strain representation across two experimental conditions, and use the spike-in pool to show that the sensitivity and specificity of this method exceed typical current approaches.

  19. Perspectives of DNA microarray and next-generation DNA sequencing technologies

    Institute of Scientific and Technical Information of China (English)

    TENG XiaoKun; XIAO HuaSheng

    2009-01-01

    DNA microarray and next-generation DNA sequencing technologies are important tools for high-throughput genome research, in revealing both the structural and functional characteristics of genomes. In the past decade the DNA microarray technologies have been widely applied in the studies of functional genomics, systems biology and pharmacogenomics. The next-generation DNA sequenc-ing method was first introduced by the 454 Company in 2003, immediately followed by the establish-ment of the Solexa and Solid techniques by other biotech companies. Though it has not been long since the first emergence of this technology, with the fast and impressive improvement, the application of this technology has extended to almost all fields of genomics research, as a rival challenging the existing DNA microarray technology. This paper briefly reviews the working principles of these two technologies as well as their application and perspectives in genome research.

  20. Multiplex giant magnetoresistive biosensor microarrays identify interferon-associated autoantibodies in systemic lupus erythematosus

    Science.gov (United States)

    Lee, Jung-Rok; Haddon, D. James; Wand, Hannah E.; Price, Jordan V.; Diep, Vivian K.; Hall, Drew A.; Petri, Michelle; Baechler, Emily C.; Balboni, Imelda M.; Utz, Paul J.; Wang, Shan X.

    2016-06-01

    High titer, class-switched autoantibodies are a hallmark of systemic lupus erythematosus (SLE). Dysregulation of the interferon (IFN) pathway is observed in individuals with active SLE, although the association of specific autoantibodies with chemokine score, a combined measurement of three IFN-regulated chemokines, is not known. To identify autoantibodies associated with chemokine score, we developed giant magnetoresistive (GMR) biosensor microarrays, which allow the parallel measurement of multiple serum antibodies to autoantigens and peptides. We used the microarrays to analyze serum samples from SLE patients and found individuals with high chemokine scores had significantly greater reactivity to 13 autoantigens than individuals with low chemokine scores. Our findings demonstrate that multiple autoantibodies, including antibodies to U1-70K and modified histone H2B tails, are associated with IFN dysregulation in SLE. Further, they show the microarrays are capable of identifying autoantibodies associated with relevant clinical manifestations of SLE, with potential for use as biomarkers in clinical practice.

  1. Perspectives of DNA microarray and next-generation DNA sequencing technologies

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    DNA microarray and next-generation DNA sequencing technologies are important tools for high-throughput genome research,in revealing both the structural and functional characteristics of genomes.In the past decade the DNA microarray technologies have been widely applied in the studies of functional genomics,systems biology and pharmacogenomics.The next-generation DNA sequencing method was first introduced by the 454 Company in 2003,immediately followed by the establishment of the Solexa and Solid techniques by other biotech companies.Though it has not been long since the first emergence of this technology,with the fast and impressive improvement,the application of this technology has extended to almost all fields of genomics research,as a rival challenging the existing DNA microarray technology.This paper briefly reviews the working principles of these two technologies as well as their application and perspectives in genome research.

  2. Detection of the specific binding on protein microarrays by oblique-incidence reflectivity difference method

    Science.gov (United States)

    Lu, Heng; Wen, Juan; Wang, Xu; Yuan, Kun; Li, Wei; Lu, Huibin; Zhou, Yueliang; Jin, Kuijuan; Ruan, Kangcheng; Yang, Guozhen

    2010-09-01

    The specific binding between Cy5-labeled goat anti-mouse Immunoglobulin G (IgG) and mouse IgG with a concentration range from 625 to 104 µg ml - 1 has been detected successfully by the oblique-incidence reflectivity difference (OI-RD) method in each procedure of microarray fabrication. The experimental data prove that the OI-RD method can be employed not only to distinguish the different concentrations in label-free fashion but also to detect the antibody-antigen capture. In addition, the differential treatment of the OI-RD signals can decrease the negative influences of glass slide as the microarray upholder. Therefore the OI-RD technique has promising applications for the label-free and high-throughput detection of protein microarrays.

  3. Detection of the specific binding on protein microarrays by oblique-incidence reflectivity difference method

    International Nuclear Information System (INIS)

    The specific binding between Cy5-labeled goat anti-mouse Immunoglobulin G (IgG) and mouse IgG with a concentration range from 625 to 104 µg ml−1 has been detected successfully by the oblique-incidence reflectivity difference (OI-RD) method in each procedure of microarray fabrication. The experimental data prove that the OI-RD method can be employed not only to distinguish the different concentrations in label-free fashion but also to detect the antibody–antigen capture. In addition, the differential treatment of the OI-RD signals can decrease the negative influences of glass slide as the microarray upholder. Therefore the OI-RD technique has promising applications for the label-free and high-throughput detection of protein microarrays

  4. Quality Control Usage in High-Density Microarrays Reveals Differential Gene Expression Profiles in Ovarian Cancer.

    Science.gov (United States)

    Villegas-Ruiz, Vanessa; Moreno, Jose; Jacome-Lopez, Karina; Zentella-Dehesa, Alejandro; Juarez-Mendez, Sergio

    2016-01-01

    There are several existing reports of microarray chip use for assessment of altered gene expression in different diseases. In fact, there have been over 1.5 million assays of this kind performed over the last twenty years, which have influenced clinical and translational research studies. The most commonly used DNA microarray platforms are Affymetrix GeneChip and Quality Control Software along with their GeneChip Probe Arrays. These chips are created using several quality controls to confirm the success of each assay, but their actual impact on gene expression profiles had not been previously analyzed until the appearance of several bioinformatics tools for this purpose. We here performed a data mining analysis, in this case specifically focused on ovarian cancer, as well as healthy ovarian tissue and ovarian cell lines, in order to confirm quality control results and associated variation in gene expression profiles. The microarray data used in our research were downloaded from ArrayExpress and Gene Expression Omnibus (GEO) and analyzed with Expression Console Software using RMA, MAS5 and Plier algorithms. The gene expression profiles were obtained using Partek Genomics Suite v6.6 and data were visualized using principal component analysis, heat map, and Venn diagrams. Microarray quality control analysis showed that roughly 40% of the microarray files were false negative, demonstrating over- and under-estimation of expressed genes. Additionally, we confirmed the results performing second analysis using independent samples. About 70% of the significant expressed genes were correlated in both analyses. These results demonstrate the importance of appropriate microarray processing to obtain a reliable gene expression profile. PMID:27268623

  5. Protein microarrays based on polymer brushes prepared via surface-initiated atom transfer radical polymerization.

    Science.gov (United States)

    Barbey, Raphael; Kauffmann, Ekkehard; Ehrat, Markus; Klok, Harm-Anton

    2010-12-13

    Polymer brushes represent an interesting platform for the development of high-capacity protein binding surfaces. Whereas the protein binding properties of polymer brushes have been investigated before, this manuscript evaluates the feasibility of poly(glycidyl methacrylate) (PGMA) and PGMA-co-poly(2-(diethylamino)ethyl methacrylate) (PGMA-co-PDEAEMA) (co)polymer brushes grown via surface-initiated atom transfer radical polymerization (SI-ATRP) as protein reactive substrates in a commercially available microarray system using tantalum-pentoxide-coated optical waveguide-based chips. The performance of the polymer-brush-based protein microarray chips is assessed using commercially available dodecylphosphate (DDP)-modified chips as the benchmark. In contrast to the 2D planar, DDP-coated chips, the polymer-brush-covered chips represent a 3D sampling volume. This was reflected in the results of protein immobilization studies, which indicated that the polymer-brush-based coatings had a higher protein binding capacity as compared to the reference substrates. The protein binding capacity of the polymer-brush-based coatings was found to increase with increasing brush thickness and could also be enhanced by copolymerization of 2-(diethylamino)ethyl methacrylate (DEAEMA), which catalyzes epoxide ring-opening of the glycidyl methacrylate (GMA) units. The performance of the polymer-brush-based microarray chips was evaluated in two proof-of-concept microarray experiments, which involved the detection of biotin-streptavidin binding as well as a model TNFα reverse assay. These experiments revealed that the use of polymer-brush-modified microarray chips resulted not only in the highest absolute fluorescence readouts, reflecting the 3D nature and enhanced sampling volume provided by the brush coating, but also in significantly enhanced signal-to-noise ratios. These characteristics make the proposed polymer brushes an attractive alternative to commercially available, 2D microarray

  6. 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.

  7. 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

  8. A novel hepatitis C virus genotyping method based on liquid microarray.

    Directory of Open Access Journals (Sweden)

    Cesar A B Duarte

    Full Text Available The strategy used to treat HCV infection depends on the genotype involved. An accurate and reliable genotyping method is therefore of paramount importance. We describe here, for the first time, the use of a liquid microarray for HCV genotyping. This liquid microarray is based on the 5'UTR - the most highly conserved region of HCV - and the variable region NS5B sequence. The simultaneous genotyping of two regions can be used to confirm findings and should detect inter-genotypic recombination. Plasma samples from 78 patients infected with viruses with genotypes and subtypes determined in the Versant™ HCV Genotype Assay LiPA (version I; Siemens Medical Solutions, Diagnostics Division, Fernwald, Germany were tested with our new liquid microarray method. This method successfully determined the genotypes of 74 of the 78 samples previously genotyped in the Versant™ HCV Genotype Assay LiPA (74/78, 95%. The concordance between the two methods was 100% for genotype determination (74/74. At the subtype level, all 3a and 2b samples gave identical results with both methods (17/17 and 7/7, respectively. Two 2c samples were correctly identified by microarray, but could only be determined to the genotype level with the Versant™ HCV assay. Genotype "1" subtypes (1a and 1b were correctly identified by the Versant™ HCV assay and the microarray in 68% and 40% of cases, respectively. No genotype discordance was found for any sample. HCV was successfully genotyped with both methods, and this is of prime importance for treatment planning. Liquid microarray assays may therefore be added to the list of methods suitable for HCV genotyping. It provides comparable results and may readily be adapted for the detection of other viruses frequently co-infecting HCV patients. Liquid array technology is thus a reliable and promising platform for HCV genotyping.

  9. 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.

  10. Immunohistochemistry - Microarray Analysis of Patients with Peritoneal Metastases of Appendiceal or Colorectal Origin

    Directory of Open Access Journals (Sweden)

    Danielle E Green

    2015-01-01

    Full Text Available BackgroundThe value of immunohistochemistry (IHC-microarray analysis of pathological specimens in the management of patients is controversial although preliminary data suggests 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.MethodsWe retrospectively analyzed consecutive patients with pathologically confirmed PM from appendiceal or colorectal primary who underwent Caris Molecular IntelligenceTM testing. IHC, microarray, FISH and mutational analysis were included and stratified by PCI score, histology and treatment characteristics. Statistical analysis was performed using non-parametric tests.ResultsOur 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 (HIPEC 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.ConclusionsIn a small sample of patients with peritoneal metastases, 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.

  11. 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.

  12. Microarray testing for the presence of toxic algae monitoring programme in Galicia (NW Spain).

    Science.gov (United States)

    Dittami, Simon M; Pazos, Yolanda; Laspra, Melchor; Medlin, Linda K

    2013-10-01

    Rapid and reliable detection of harmful algae in coastal areas and shellfish farms is an important requirement of monitoring programmes. Monitoring of toxic algae by means of traditional methods, i.e., light microscopy, can be time consuming when many samples have to be routinely analysed. Reliable species identification requires expensive equipment and trained personnel to carry out the analyses. However, all techniques for the monitoring of harmful algae usually require transportation of samples to specialised laboratories. In many monitoring laboratories, results are usually obtained within five working days after receiving the sample and therefore preventative measures are not always possible. Molecular technologies are rapidly improving the detection of phytoplankton and their toxins and the speed at which the results can be obtained. Assays are based on the discrimination of the genetic differences of the different species and species-specific probes can be designed. Such probes have been adapted to a microarray or phylochip format and assessed in several EU monitoring sites. Microarray results are presented for 1 year of field samples validated with cell counts from concentrated samples taken during toxic events from the weekly sampling of the Galician Monitoring Programme done by INTECMAR. The Galician monitoring laboratory does their own counting and their results are posted on their web site within 24 h. There was good correlation between cells present and microarray signals. In the few cases of false negatives, these can be attributed to poor RNA extraction of the target species, viz. Prorocentrum or Dinophysis. Where potential false positives were encountered, the smaller volume taken for cell counts as compared to the upto 300 times more volume taken for RNA extraction for the microarray is likely the cause for these differences, making the microarray more sensitive. The microarray was able to provide better species resolution in Alexandrium and Pseudo

  13. A Network Partition Algorithm for Mining Gene Functional Modules of Colon Cancer from DNA Microarray Data

    Institute of Scientific and Technical Information of China (English)

    Xiao-Gang Ruan; Jin-Lian Wang; Jian-Geng Li

    2006-01-01

    Computational analysis is essential for transforming the masses of microarray data into a mechanistic understanding of cancer. Here we present a method for finding gene functional modules of cancer from microarray data and have applied it to colon cancer. First, a colon cancer gene network and a normal colon tissue gene network were constructed using correlations between the genes. Then the modules that tended to have a homogeneous functional composition were identified by splitting up the network. Analysis of both networks revealed that they are scale-free.Comparison of the gene functional modules for colon cancer and normal tissues showed that the modules' functions changed with their structures.

  14. Bioinformatic Tools for Inferring Functional Information from Plant Microarray Data: Tools for the First Steps

    OpenAIRE

    Page, Grier P.; Coulibaly, Issa

    2008-01-01

    Microarrays are a very powerful tool for quantifying the amount of RNA in samples; however, their ability to query essentially every gene in a genome, which can number in the tens of thousands, presents analytical and interpretative problems. As a result, a variety of software and web-based tools have been developed to help with these issues. This article highlights and reviews some of the tools for the first steps in the analysis of a microarray study. We have tried for a balance between fre...

  15. Microarray background correction: maximum likelihood estimation for the normal-exponential convolution

    DEFF Research Database (Denmark)

    Silver, Jeremy D; Ritchie, Matthew E; Smyth, Gordon K

    2009-01-01

    Background correction is an important preprocessing step for microarray data that attempts to adjust the data for the ambient intensity surrounding each feature. The "normexp" method models the observed pixel intensities as the sum of 2 random variables, one normally distributed and the other...... exponentially distributed, representing background noise and signal, respectively. Using a saddle-point approximation, Ritchie and others (2007) found normexp to be the best background correction method for 2-color microarray data. This article develops the normexp method further by improving the estimation...

  16. 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.

  17. Identification of c-Src tyrosine kinase substrates using mass spectrometry and peptide microarrays

    DEFF Research Database (Denmark)

    Amanchy, Ramars; Zhong, Jun; Molina, Henrik;

    2008-01-01

    that are phosphorylated by c-Src on the novel c-Src substrates, we designed custom peptide microarrays containing all possible tyrosine-containing peptides (312 unique peptides) and their mutant counterparts containing a Tyr --> Phe substitution from 14 of the identified substrates. Using this platform, we identified 34...... peptides that are phosphorylated by c-Src. We have demonstrated that SILAC-based quantitative proteomics approach is suitable for identification of substrates of nonreceptor tyrosine kinases and can be coupled with peptide microarrays for high-throughput identification of substrate phosphopeptides....

  18. Application of lectin microarray to crude samples: differential glycan profiling of lec mutants.

    Science.gov (United States)

    Ebe, Youji; Kuno, Atsushi; Uchiyama, Noboru; Koseki-Kuno, Shiori; Yamada, Masao; Sato, Takashi; Narimatsu, Hisashi; Hirabayashi, Jun

    2006-03-01

    We recently developed a novel system for lectin microarray based on the evanescent-field fluorescence-detection principle, by which even weak lectin-oligosaccharide interactions are detectable without a washing procedure. For its practical application, cell glycan analysis was performed for Chinese hamster ovary (CHO) cells and their glycan profile was compared with those of their glycosylation-defective Lec mutants. Each of the cell surface extracts gave a significantly different profile from that of the parental CHO cells in a manner reflecting denoted biosynthetic features. Hence, the developed lectin microarray system is considered to be fully applicable for differential glycan profiling of crude samples.

  19. Development and Clinical Evaluation of a Highly Sensitive DNA Microarray for Detection and Genotyping of Human Papillomaviruses

    Science.gov (United States)

    Oh, TaeJeong; Kim, ChangJin; Woo, SukKyung; Kim, TaeSeung; Jeong, DongJun; Kim, MyungSoon; Lee, Sunwoo; Cho, HyunSill; An, Sungwhan

    2004-01-01

    Human papillomavirus (HPV) has been found in cervical cancer, tonsillar cancer, and certain types of head and neck cancers. We report on a DNA microarray-based method for the simultaneous detection and typing of HPVs. The genotype spectrum discriminated by this HPV DNA microarray includes 15 high-risk HPV genotypes and 12 low-risk HPV genotypes. The HPV DNA microarray showed high degrees of specificity and reproducibility. We evaluated the performance of the HPV DNA microarray by application to three HPV-positive cell lines (HeLa, Caski, and SiHa cells) and two HPV-negative cell lines (C33A and A549 cells). The HPV DNA microarray successfully identified the known types of HPV present in the cell lines. The detection limit of the HPV DNA microarray was at least 100-fold higher than that of PCR. To assess the clinical applicability of the HPV DNA microarray, we performed the HPV genotyping assay with 73 nonmalignant and malignant samples from 39 tonsillar cancer patients. Twenty-five of the 39 (64.1%) malignant samples were positive for HPV, whereas 3 of 34 (8.8%) nonmalignant samples were positive for HPV. This result shows a preferential association of HPV with tonsillar carcinomas. The correlations of the presence of HPV with the grade of differentiation and risk factors were not significant. Our data show that the HPV DNA microarray may be useful for the diagnosis and typing of HPV in large-scale epidemiological studies. PMID:15243092

  20. Evaluating the Information Management and Collaboration of “Bench to Bedside” Microarray Research Computing with Qualitative Methods

    OpenAIRE

    Anderson, Nicholas

    2006-01-01

    This research is a qualitative longitudinal evaluation of the information management, collaboration and analysis of microarray gene expression analysis in use in basic science and clinical settings. Methods of qualitative observation and in-depth open-ended interviews are used within a theoretical framework to explore and contrast information use in small and medium sized laboratories involved in translational microarray research.

  1. Suspension Microarray with Dendrimer Signal Amplification Allows Direct and High-Throughput Subtyping of Listeria monocytogenes from Genomic DNA

    OpenAIRE

    Borucki, Monica K.; Reynolds, James; Douglas R Call; Ward, Todd J.; Page, Brent; Kadushin, James

    2005-01-01

    Listeria monocytogenes is a significant cause of food-borne disease and mortality; therefore, epidemiological investigations of this pathogen require subtyping methods that are rapid, discriminatory, and reproducible. Although conventional microarray subtyping analysis has been shown to be both high resolution and genetically informative, it is still relatively low throughput and technically challenging. Suspension microarray technology eliminates the technical issues associated with planar m...

  2. Rasch-based high-dimensionality data reduction and class prediction with applications to microarray gene expression data

    CERN Document Server

    Kastrin, Andrej

    2010-01-01

    Class prediction is an important application of microarray gene expression data analysis. The high-dimensionality of microarray data, where number of genes (variables) is very large compared to the number of samples (obser- vations), makes the application of many prediction techniques (e.g., logistic regression, discriminant analysis) difficult. An efficient way to solve this prob- lem is by using dimension reduction statistical techniques. Increasingly used in psychology-related applications, Rasch model (RM) provides an appealing framework for handling high-dimensional microarray data. In this paper, we study the potential of RM-based modeling in dimensionality reduction with binarized microarray gene expression data and investigate its prediction ac- curacy in the context of class prediction using linear discriminant analysis. Two different publicly available microarray data sets are used to illustrate a general framework of the approach. Performance of the proposed method is assessed by re-randomization s...

  3. Erratum: Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing.

    Science.gov (United States)

    2015-01-01

    The author's email has been corrected in the publication of Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing. There was an error with the author, Jerry Zhou's, email. The author's email has been updated to: j.zhou@uws.edu.au from: jzho7551@mail.usyd.edu.au. PMID:26167960

  4. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  6. 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 . PMID:22767354

  7. A robust measure of correlation between two genes on a microarray

    Directory of Open Access Journals (Sweden)

    Hicks Leanne

    2007-06-01

    Full Text Available Abstract Background The underlying goal of microarray experiments is to identify gene expression patterns across different experimental conditions. Genes that are contained in a particular pathway or that respond similarly to experimental conditions could be co-expressed and show similar patterns of expression on a microarray. Using any of a variety of clustering methods or gene network analyses we can partition genes of interest into groups, clusters, or modules based on measures of similarity. Typically, Pearson correlation is used to measure distance (or similarity before implementing a clustering algorithm. Pearson correlation is quite susceptible to outliers, however, an unfortunate characteristic when dealing with microarray data (well known to be typically quite noisy. Results We propose a resistant similarity metric based on Tukey's biweight estimate of multivariate scale and location. The resistant metric is simply the correlation obtained from a resistant covariance matrix of scale. We give results which demonstrate that our correlation metric is much more resistant than the Pearson correlation while being more efficient than other nonparametric measures of correlation (e.g., Spearman correlation. Additionally, our method gives a systematic gene flagging procedure which is useful when dealing with large amounts of noisy data. Conclusion When dealing with microarray data, which are known to be quite noisy, robust methods should be used. Specifically, robust distances, including the biweight correlation, should be used in clustering and gene network analysis.

  8. 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.

  9. 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.

  10. Optimization of single-base-pair mismatch discrimination in oligonucleotide microarrays

    NARCIS (Netherlands)

    Urakawa, H.; Fantroussi, El S.; Smidt, H.; Smoot, J.C.; Tribou, E.H.; Kelly, J.J.; Noble, P.A.; Stahl, D.A.

    2003-01-01

    The discrimination between perfect-match and single-base-pair-mismatched nucleic acid duplexes was investigated by using oligonucleotide DNA microarrays and nonequilibrium dissociation rates (melting profiles). DNA and RNA versions of two synthetic targets corresponding to the 16S rRNA sequences of

  11. 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...

  12. A microarray approach for simultaneous detection of multiple pathogens in food

    Science.gov (United States)

    A pathogen detection microarray was developed for simultaneous detection of the four most prominent foodborne pathogens including Escherichia coli O157:H7, Salmonella enterica, Listeria monocytogenes and Campylobacter jejuni. The approach utilized 14 species-specific gene targets to design a variety...

  13. Use of the cDNA microarray technology in the safety assessment of GM food plants

    NARCIS (Netherlands)

    Kok, E.J.; Kleter, G.A.; Dijk, van J.P.

    2003-01-01

    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 the

  14. 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

  15. A novel parametric approach to mine gene regulatory relationship from microarray datasets

    Directory of Open Access Journals (Sweden)

    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.

  16. Study on Wusan Granule Anti-tumor Related Target Gene Screened by Cdna Microarray

    Institute of Scientific and Technical Information of China (English)

    YOU Zi-li; SHI Jin-ping; CHEN Hai-hong

    2006-01-01

    To screen Wusan Granule anti-tumor related target gene using cDNA microarray technique, both mRNA from Lewis lung carcinoma tissues treated by Wusan Granule and untreated control are reversibly transcribed to prepare cDNA probes which are labeled by Cy5 and Cy3. Then, the probes are hybridized to the mice cDNA microarray type MGEC-20S. After hybridization, the cDNA microarray is scanned by ScanArray 3 000 scanner and the data is analyzed by ImaGene 3 software to screen the differentially expressed genes. There are 45 differentially expressed genes including 18 known genes and 27 unknown genes between the two groups, and among them, 20 elevated genes and 25 reduced genes are identified. Additionally, the genes related to invasion and metastasis of malignant carcinomas are down-regulated and the genes related to apoptosis are up-regulated. The cDNA microarray technique is a high-throughput approach to screen the Wusan Granule anti-tumor related target genes, which allow us to explore the molecular biological mechanism on a genomic scale.

  17. Establishment and Application of a Visual DNA Microarray for the Detection of Food-borne Pathogens.

    Science.gov (United States)

    Li, Yongjin

    2016-01-01

    The accurate detection and identification of food-borne pathogenic microorganisms is critical for food safety nowadays. In the present work, a visual DNA microarray was established and applied to detect pathogens commonly found in food, including Salmonella enterica, Shigella flexneri, E. coli O157:H7 and Listeria monocytogenes in food samples. Multiplex PCR (mPCR) was employed to simultaneously amplify specific gene fragments, fimY for Salmonella, ipaH for Shigella, iap for L. monocytogenes and ECs2841 for E. coli O157:H7, respectively. Biotinylated PCR amplicons annealed to the microarray probes were then reacted with a streptavidin-alkaline phosphatase conjugate and nitro blue tetrazolium/5-bromo-4-chloro-3'-indolylphosphate, p-toluidine salt (NBT/BCIP); the positive results were easily visualized as blue dots formatted on the microarray surface. The performance of a DNA microarray was tested against 14 representative collection strains and mock-contamination food samples. The combination of mPCR and a visual micro-plate chip specifically and sensitively detected Salmonella enterica, Shigella flexneri, E. coli O157:H7 and Listeria monocytogenes in standard strains and food matrices with a sensitivity of ∼10(2) CFU/mL of bacterial culture. Thus, the developed method is advantageous because of its high throughput, cost-effectiveness and ease of use. PMID:26860568

  18. 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.

  19. "On-chip magnetic bead microarray using hydrodynamic focusing in a passive magnetic separator"

    DEFF Research Database (Denmark)

    Smistrup, Kristian; Kjeldsen, B.; Reimers, R.L.;

    2005-01-01

    Implementing DNA and protein microarrays into lab-on-a-chip systems can be problematic since these are sensitive to heat and strong chemicals. Here, we describe the functionalization of a microchannel with two types of magnetic beads using hydrodynamic focusing combined with a passive magnetic...

  20. A Bifidobacterium mixed-species microarray for high resolution discrimination between intestinal bifidobacteria

    NARCIS (Netherlands)

    Boesten, R.J.; Schuren, F.H.; Vos, de W.M.

    2009-01-01

    A genomic DNA-based microarray was constructed containing over 6000 randomly cloned genomic fragments of approximately 1-2 kb from six mammalian intestinal Bifidobacterium spp. including B. adolescentis, B. animalis, B. bifidum, B. catenulatum, B. longum and B. pseudolongum. This Bifidobacterium Mix

  1. Antibody microarray profiling of osteosarcoma cell serum for identifying potential biomarkers.

    Science.gov (United States)

    Zhu, Zi-Qiang; Tang, Jin-Shan; Gang, Duan; Wang, Ming-Xing; Wang, Jian-Qiang; Lei, Zhou; Feng, Zhou; Fang, Ming-Liang; Yan, Lin

    2015-07-01

    The aim of the present study was to identify biomarkers in osteosarcoma (OS) cell serum by antibody microarray profiling, which may be used for OS diagnosis and therapy. An antibody microarray was used to detect the expression levels of cytokines in serum samples from 20 patients with OS and 20 healthy individuals. Significantly expressed cytokines in OS serum were selected when P2. An enzyme-linked immunosorbent assay (ELISA) was used to validate the antibody microarray results. Finally, classification accuracy was calculated by cluster analysis. Twenty one cytokines were significantly upregulated in OS cell serum samples compared with control samples. Expression of interleukin-6, monocyte chemoattractant protein-1, tumor growth factor-β, growth-related oncogene, hepatocyte growth factor, chemokine ligand 16, Endoglin, matrix metalloproteinase-9 and platelet-derived growth factor-AA was validated by ELISAs. OS serum samples and control samples were distinguished by significantly expressed cytokines with an accuracy of 95%. The results demonstrated that expressed cytokines identified by antibody microarray may be used as biomarkers for OS diagnosis and therapy.

  2. Comparison of three microarray probe annotation pipelines: differences in strategies and their effect on downstream analysis

    NARCIS (Netherlands)

    Neerincx, P.B.T.; Casel, P.; Prickett, D.; Nie, H.; Watson, M.; Leunissen, J.A.M.; Groenen, M.A.M.; Klopp, C.

    2009-01-01

    Background - Reliable annotation linking oligonucleotide probes to target genes is essential for functional biological analysis of microarray experiments. We used the IMAD, OligoRAP and sigReannot pipelines to update the annotation for the ARK-Genomics Chicken 20 K array as part of a joined EADGENE/

  3. Robust Feature Selection from Microarray Data Based on Cooperative Game Theory and Qualitative Mutual Information.

    Science.gov (United States)

    Mortazavi, Atiyeh; Moattar, Mohammad Hossein

    2016-01-01

    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.

  4. Development of a sandwiched microarray platform for studying the interactions of antibiotics with Staphylococcus aureus.

    Science.gov (United States)

    Liu, Xia; Lei, Zhen; Liu, Dianjun; Wang, Zhenxin

    2016-04-21

    It still confronts an outstanding challenge to screen efficient antibacterial drugs from millions of potential antibiotic candidates. In this regard, a sandwiched microarray platform has been developed to culture live bacteria and carry out high-throughput screening antibacterial drugs. The optimized lectin-hydrogel microarray can be used as an efficient bacterial capturing and culturing platform, which is beneficial to identify spots and collect data. At the same time, a matching drug-laden polyacrylamide microarray with Luria-Bertani (LB) culture medium can be generated automatically and accurately by using a standard non-contacting procedure. A large number of microscale culture chambers (more than 100 individual samples) between two microarrays can be formed by linking two aligned hydrogel spots using LB culture medium, where live bacteria can be co-cultured with drug candidates. Using Staphylococcus aureus (S. aureus) and four well-known antibiotics (amoxicillin, vancomycin, streptomycin and chloramphenicol) as model system, the MIC (minimum inhibitory concentration) values of the antibiotics can be determined by the drug induced change of bacterial growth, and the results demonstrate that the MIC values of amoxicillin, vancomycin and streptomycin are 1.7 μg mL(-1), 3.3 μg mL(-1) and 10.3 μg mL(-1), respectively. PMID:27026605

  5. Comparative genomics in chicken and Pekin duck using FISH mapping and microarray analysis

    NARCIS (Netherlands)

    Skinner, M.; Robertson, L.B.; Tempest, H.G.; Langley, E.J.; Ioannou, D.; Fowler, K.E.; Crooijmans, R.P.M.A.

    2009-01-01

    Background: The availability of the complete chicken (Gallus gallus) genome sequence as well as a large number of chicken probes for fluorescent in-situ hybridization (FISH) and microarray resources facilitate comparative genomic studies between chicken and other bird species. In a previous study, w

  6. Microarray profiling of lymphocytes in internal diseases with an altered immune response : Potential and methodology

    NARCIS (Netherlands)

    Gladkevich, A; Nelemans, SA; Kauffman, HF; Korf, J

    2005-01-01

    Recently it has become possible to investigate expression of all human genes with microarray technique. The authors provide arguments to consider peripheral white blood cells and in particular lymphocytes as a model for the investigation of pathophysiology of asthma, RA, and SLE diseases in which in

  7. Microarray-based identification of clinically relevant vaginal bacteria in relation to bacterial vaginosis

    NARCIS (Netherlands)

    Dols, J.A.M.; Smit, P.W.; Kort, R.; Reid, G.; Schuren, F.H.J.; Tempelman, H.; Bontekoe, T.R.; Korporaal, H.; Boon, M.E.

    2011-01-01

    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 cyt

  8. 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.

  9. Optimization of the BLASTN substitution matrix for prediction of non-specific DNA microarray hybridization

    DEFF Research Database (Denmark)

    Eklund, Aron Charles; Friis, Pia; Wernersson, Rasmus;

    2010-01-01

    DNA microarray measurements are susceptible to error caused by non-specific hybridization between a probe and a target (cross-hybridization), or between two targets (bulk-hybridization). Search algorithms such as BLASTN can quickly identify potentially hybridizing sequences. We set out to improve...

  10. 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 s...

  11. 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.

  12. A biclustering algorithm based on a Bicluster Enumeration Tree: application to DNA microarray data

    Directory of Open Access Journals (Sweden)

    Ayadi Wassim

    2009-12-01

    Full Text Available Abstract Background In a number of domains, like in DNA microarray data analysis, we need to cluster simultaneously rows (genes and columns (conditions of a data matrix to identify groups of rows coherent with groups of columns. This kind of clustering is called biclustering. Biclustering algorithms are extensively used in DNA microarray data analysis. More effective biclustering algorithms are highly desirable and needed. Methods We introduce BiMine, a new enumeration algorithm for biclustering of DNA microarray data. The proposed algorithm is based on three original features. First, BiMine relies on a new evaluation function called Average Spearman's rho (ASR. Second, BiMine uses a new tree structure, called Bicluster Enumeration Tree (BET, to represent the different biclusters discovered during the enumeration process. Third, to avoid the combinatorial explosion of the search tree, BiMine introduces a parametric rule that allows the enumeration process to cut tree branches that cannot lead to good biclusters. Results The performance of the proposed algorithm is assessed using both synthetic and real DNA microarray data. The experimental results show that BiMine competes well with several other biclustering methods. Moreover, we test the biological significance using a gene annotation web-tool to show that our proposed method is able to produce biologically relevant biclusters. The software is available upon request from the authors to academic users.

  13. 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

    been sequenced so far. Conclusion: This high-density microarray provides an excellent tool for characterizing the genetic makeup of unknown E. coli strains and can also deliver insights into phylogenetic relationships. Its design poses a considerably larger challenge and involves different...

  14. Development of a biosensor microarray towards food screening using imaging surface plasmon resonance

    NARCIS (Netherlands)

    Rebe, S.; Bremer, M.G.E.G.; Giesbers, M.; Norde, W.

    2008-01-01

    In this study we examined the possibilities of implementing direct and competitive immunoassay formats for small and large molecule detection on a microarray, using IBIS imaging surface plasmon resonance (iSPR) system. First, IBIS iSPR optics performance was evaluated. Using a glycerol calibration c

  15. Development of a biosensor microarray towards food screening, using imaging surface plasmon resonance

    NARCIS (Netherlands)

    Raz, Sabina Rebe; Bremer, Maria G. E. G.; Giesbers, Marcel; Norde, Willem

    2008-01-01

    In this study we examined the possibilities of implementing direct and competitive immunoassay formats for small and large molecule detection on a microarray, using IBIS imaging surface plasmon resonance (iSPR) system. First, IBIS iSPR optics performance was evaluated. Using a glycerol calibration c

  16. Measuring information flow in cellular networks by the systems biology method through microarray data.

    Science.gov (United States)

    Chen, Bor-Sen; Li, Cheng-Wei

    2015-01-01

    In general, it is very difficult to measure the information flow in a cellular network directly. In this study, based on an information flow model and microarray data, we measured the information flow in cellular networks indirectly by using a systems biology method. First, we used a recursive least square parameter estimation algorithm to identify the system parameters of coupling signal transduction pathways and the cellular gene regulatory network (GRN). Then, based on the identified parameters and systems theory, we estimated the signal transductivities of the coupling signal transduction pathways from the extracellular signals to each downstream protein and the information transductivities of the GRN between transcription factors in response to environmental events. According to the proposed method, the information flow, which is characterized by signal transductivity in coupling signaling pathways and information transductivity in the GRN, can be estimated by microarray temporal data or microarray sample data. It can also be estimated by other high-throughput data such as next-generation sequencing or proteomic data. Finally, the information flows of the signal transduction pathways and the GRN in leukemia cancer cells and non-leukemia normal cells were also measured to analyze the systematic dysfunction in this cancer from microarray sample data. The results show that the signal transductivities of signal transduction pathways change substantially from normal cells to leukemia cancer cells.

  17. 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.

  18. 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...

  19. Point-of-care vertical flow allergen microarray assay: proof of concept

    NARCIS (Netherlands)

    Chinnasamy, Thiruppathiraja; Segerink, Loes I.; Nystrand, Mats; Gantelius, Jesper; Andersson Svahn, Helene

    2014-01-01

    BACKGROUND: Sophisticated equipment, lengthy protocols, and skilled operators are required to perform protein microarray-based affinity assays. Consequently, novel tools are needed to bring biomarkers and biomarker panels into clinical use in different settings. Here, we describe a novel paper-based

  20. Detection of protein microarrays by oblique-incidence reflectivity difference technique

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Biological microarrays with different proteins and different protein concentrations are detected without external labeling by an oblique-incidence reflectivity difference (OIRD) technique. The initial experiment results reveal that the intensities of OIRD signals can distinguish the different proteins and concentrations of protein. The OIRD technique promises feasible applications to life sciences for label-free and high-throughput detection.

  1. Chromosomal imbalances in malignant peripheral nerve sheath tumor detected by metaphase and microarray comparative genomic hybridization.

    Science.gov (United States)

    Nakagawa, Yasuko; Yoshida, Aki; Numoto, Kunihiko; Kunisada, Toshiyuki; Wai, Daniel; Ohata, Norihide; Takeda, Ken; Kawai, Akira; Ozaki, Toshifumi

    2006-02-01

    Malignant peripheral nerve sheath tumors (MPNSTs) are highly malignant tumors affecting adolescents and adults. There have been a few reports on chromosomal aberrations of MPNSTs; however, the tumor-specific alteration remains unknown. We characterized the genomic alterations in 8 MPNSTs and 8 schwannomas by metaphase comparative genomic hybridization (CGH). In 5 of 8 MPNSTs, microarray CGH was added for more detailed analyses. Frequent gains were identified on 3q13-26, 5p13-14, and 12q11-23 and frequent losses were at 1p31, 10p, 11q24-qter, 16, and 17. Microarray CGH revealed frequent gains of EGFR, DAB2, MSH2, KCNK12, DDX15, CDK6, and LAMA3, and losses of CDH1, GLTSCR2, EGR1, CTSB, GATA3, and SULT2A1. These genes seem to be responsible for developing MPNSTs. The concordance rate between metaphase CGH and microarray CGH was 66%. Metaphase CGH was useful for identifying chromosomal alterations before applying microarray CGH. PMID:16391845

  2. 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…

  3. Characterization of an inexpensive, non-toxic and highly sensitive microarray substrate

    DEFF Research Database (Denmark)

    Dufva, Hans Martin; Petronis, Sarunas; Jensen, L. B.;

    2004-01-01

    was replaced with a wash in 0.1x standard saline citrate (SSC) and 0.5% sodium dodecyl sulfate (SDS) without decreasing the performance of the produced microarrays. Characterization of the grafted agarose film using atomic force microscopy (AFM) and scanning electron microscopy (SEM) showed that the agarose...

  4. 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. PMID:16879879

  5. Assessment of fusion gene status in sarcomas using a custom made fusion gene microarray.

    Directory of Open Access Journals (Sweden)

    Marthe Løvf

    Full Text Available Sarcomas are relatively rare malignancies and include a large number of histological subgroups. Based on morphology alone, the differential diagnoses of sarcoma subtypes can be challenging, but the identification of specific fusion genes aids correct diagnostication. The presence of individual fusion products are routinely investigated in Pathology labs. However, the methods used are time-consuming and based on prior knowledge about the expected fusion gene and often the most likely break-point. In this study, 16 sarcoma samples, representing seven different sarcoma subtypes with known fusion gene status from a diagnostic setting, were investigated using a fusion gene microarray. The microarray was designed to detect all possible exon-exon breakpoints between all known fusion genes in a single analysis. An automated scoring of the microarray data from the 38 known sarcoma-related fusion genes identified the correct fusion gene among the top-three hits in 11 of the samples. The analytical sensitivity may be further optimised, but we conclude that a sarcoma-fusion gene microarray is suitable as a time-saving screening tool to identify the majority of the correct fusion genes.

  6. 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 he

  7. Detection and analysis system for hybridization images of lab-in-a-tube microarray

    Institute of Scientific and Technical Information of China (English)

    LIU Quanjun; ZHOU Qin; BAI Yunfei; GE Qinyu; LU Zuhong

    2005-01-01

    A lab-in-a-tube microarray system is developed for sample inspection and signal detection by fabricating a flat transparent window cap of the Eppendorf tube. The oli- gonucleotide microarray is immobilized on the inner surface of the cap. A small vessel is placed in an Eppendorf tube for storing hybridization solutions. With the microarray system, the full biochemical processes, including gene fragment amplification, fluorescence labeling, hybridization, and fluorescence detection, have been performed in the sealed tube without opening the cap. The images are obtained from a fluorescence microscope and captured by a CCD, and the data are transported to a computer through the universal serial bus (USB). After noise reduction, signal intensity is determined from hybridization image and the presence of gene fragments is identified. The final data output includes sample information, process steps, and hybridization results. A lab-in- a-tube microarray system for detecting ten respiratory viruses at a single detection is designed. High detection throug- hput and accuracy have been demonstrated with the system.

  8. Chromosomal Microarrays in Prenatal Diagnosis: Time for a Change of Policy?

    Directory of Open Access Journals (Sweden)

    Peter Miny

    2013-12-01

    Full Text Available Microarrays have replaced conventional karyotyping as a first-tier test for unbalanced chromosome anomalies in postnatal cytogenetics mainly due to their unprecedented resolution facilitating the detection of submicroscopic copy number changes at a rate of 10–20% depending on indication for testing. A number of studies have addressed the performance of microarrays for chromosome analyses in high risk pregnancies due to abnormal ultrasound findings and reported an excess detection rate between 5% and 10%. In low risk pregnancies, clear pathogenic copy number changes at the submicroscopic level were encountered in 1% or less. Variants of unclear clinical significance, unsolicited findings, and copy number changes with variable phenotypic consequences are the main issues of concern in the prenatal setting posing difficult management questions. The benefit of microarray testing may be limited in pregnancies with only moderately increased risks (advanced maternal age, positive first trimester test. It is suggested to not change the current policy of microarray application in prenatal diagnosis until more data on the clinical significance of copy number changes are available.

  9. Microarray Glycoprofiling of CA125 Improves Differential Diagnosis of Ovarian Cancer

    DEFF Research Database (Denmark)

    Chen, Kowa; Gentry-Maharaj, Aleksandra; Burnell, Matthew;

    2013-01-01

    neoplasms and endometriosis. Aberrant O-glycosylation is an inherent and specific property of cancer cells and could potentially aid in differentiating cancer from these benign conditions, thereby improving specificity of the assay. We report on the development of a novel microarray-based platform...

  10. LNA-modified isothermal oligonucleotide microarray for differentiating bacilli of similar origin

    Indian Academy of Sciences (India)

    Jing Yan; Ying Yuan; Runqing Mu; Hong Shang; Yifu Guan

    2014-12-01

    Oligonucleotide microarray has been one of the most powerful tools in the ‘Post-Genome Era’ for its high sensitivity, high throughput and parallel processing capability. To achieve high detection specificity, we fabricated an isothermal microarray using locked nucleic acid (LNA)-modified oligonucleotide probes, since LNA has demonstrated the advanced ability to enhance the binding affinity toward their complementary nucleotides. After designing the nucleotide sequences of these oligonucleotide probes for gram-positive bacilli of similar origin (Bacillus subtilis, Bacillus licheniformis, Bacillus pumilus, Bacillus megaterium and Bacillus circulans), we unified the melting temperatures of these oligonucleotide probes by modifying some nucleotides using LNA. Furthermore, we optimized the experimental procedures of hydrating microarray slides, blocking side surface as well as labelling the PCR products. Experimental results revealed that KOD Dash DNA polymerase could efficiently incorporate Cy3-dCTP into the PCR products, and the LNA-isothermal oligonucleotide microarray were able to distinguish the bacilli of similar origin with a high degree of accuracy and specificity under the optimized experimental condition.

  11. Discovering gene expression patterns in time course microarray experiments by ANOVA-SCA.

    NARCIS (Netherlands)

    M.J. Nueda; A. Conessa; J.A. Westerhuis; H.C.J. Hoefsloot; A.K. Smilde; M. Talon; A. Ferrer

    2007-01-01

    In this work, we develop the application of the Analysis of variance-simultaneous component analysis (ANOVA-SCA) Smilde et al. Bioinformatics, (2005) to the analysis of multiple series time course microarray data as an example of multifactorial gene expression profiling experiments. We denoted this

  12. Gene expression analysis of strawberry achene and receptacle maturation using DNA microarrays

    NARCIS (Netherlands)

    Aharoni, A.; O'Connell, A.P.

    2002-01-01

    Large-scale, single pass sequencing and parallel gene expression analysis using DNA microarrays were employed for the comprehensive investigation of ripening in strawberry fruit. A total of 1701 cDNA clones (comprising 1100 strawberry ESTs and 601 unsequenced cDNAs) obtained from a strawberry (Fraga

  13. Surface-activated microtiter-plate microarray for simultaneous CRP quantification and viral antibody detection.

    Science.gov (United States)

    Viitala, Sari M; Jääskeläinen, Anne J; Kelo, Eira; Sirola, Helena; Moilanen, Kirsi; Suni, Jukka; Vaheri, Antti; Vapalahti, Olli; Närvänen, Ale

    2013-02-01

    Microarrays are widely used in high-throughput DNA and RNA hybridization tests and recently adopted to protein and small molecule interaction studies in basic research and diagnostics. Parallel detection of serum antibodies and antigens has several potential applications in epidemiologic research, vaccine development, and in the diagnosis of allergies, autoimmunity, and infectious diseases. This study demonstrates an immobilization method for immunoassay-based microarray in conventional 96-well polystyrene plates for a serologic diagnostic method combined with quantitative C-reactive protein (CRP) assay. A synthetic peptide (HIV-1), a recombinant protein (Puumala hantavirus nucleocapsid), and purified virus preparations (Sindbis and adenoviruses) were used as antigens for virus-specific antibody detection and monoclonal anti-CRP antibody for antigen detection. The microarray was based on conventional enzyme immunoassays and densitometry from photographed results. Peptide and recombinant antigens functioned well, while whole virus antigens gave discrepant results in 1 out of 23 samples from the reference method, tested with human sera with various antibody responses. The CRP results were in concordance in the concentration range 0.5-150 mg/L with 2 commercially available CRP assays: ReaScan rapid test (R(2) = 0.9975) and Cobas 6000 analyzer (R(2) =0.9595). The results indicate that microtiter plates provide a promising platform for further development of microarrays for parallel antibody and antigen detection. PMID:23219230

  14. Usefulness of the SNP microarray technology to identify rare mutations in the case of perinatal death

    DEFF Research Database (Denmark)

    Hoeffding, L. K.; Kock, K. F.; Johnsen, Iben Birgit Gade;

    2015-01-01

    The single nucleotide polymorphism (SNP) microarray technology has emerged as a powerful tool to screen the whole genome for sub-microscopic duplications and deletions that are not detectable by traditional cytogenetic analysis. Case: We report a case of a female twin born at 27th week of gestation...

  15. Discovery of a quorum sensing modulator pharmacophore by 3D small-molecule microarray screening

    DEFF Research Database (Denmark)

    Marsden, David M; Nicholson, Rebecca L; Skindersoe, Mette E;

    2010-01-01

    ligand-binding domains of the LuxR homolog CarR from Erwinia carotovora subsp. carotovora. The 3D microarray platform was used to discover the biologically active chloro-pyridine pharmacophore, which was validated using a fluorometric ligand binding assay and ITC. Analogs containing the chloro...

  16. 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…

  17. Development and validation of a flax (Linum usitatissimum L. gene expression oligo microarray

    Directory of Open Access Journals (Sweden)

    Gutierrez Laurent

    2010-10-01

    Full Text Available Abstract Background Flax (Linum usitatissimum L. has been cultivated for around 9,000 years and is therefore one of the oldest cultivated species. Today, flax is still grown for its oil (oil-flax or linseed cultivars and its cellulose-rich fibres (fibre-flax cultivars used for high-value linen garments and composite materials. Despite the wide industrial use of flax-derived products, and our actual understanding of the regulation of both wood fibre production and oil biosynthesis more information must be acquired in both domains. Recent advances in genomics are now providing opportunities to improve our fundamental knowledge of these complex processes. In this paper we report the development and validation of a high-density oligo microarray platform dedicated to gene expression analyses in flax. Results Nine different RNA samples obtained from flax inner- and outer-stems, seeds, leaves and roots were used to generate a collection of 1,066,481 ESTs by massive parallel pyrosequencing. Sequences were assembled into 59,626 unigenes and 48,021 sequences were selected for oligo design and high-density microarray (Nimblegen 385K fabrication with eight, non-overlapping 25-mers oligos per unigene. 18 independent experiments were used to evaluate the hybridization quality, precision, specificity and accuracy and all results confirmed the high technical quality of our microarray platform. Cross-validation of microarray data was carried out using quantitative qRT-PCR. Nine target genes were selected on the basis of microarray results and reflected the whole range of fold change (both up-regulated and down-regulated genes in different samples. A statistically significant positive correlation was obtained comparing expression levels for each target gene across all biological replicates both in qRT-PCR and microarray results. Further experiments illustrated the capacity of our arrays to detect differential gene expression in a variety of flax tissues as well

  18. Identification of listeria species isolated in Tunisia by Microarray based assay : results of a preliminary study

    International Nuclear Information System (INIS)

    Microarray-based assay is a new molecular approach for genetic screening and identification of microorganisms. We have developed a rapid microarray-based assay for the reliable detection and discrimination of Listeria spp. in food and clinical isolates from Tunisia. The method used in the present study is based on the PCR amplification of a virulence factor gene (iap gene). the PCR mixture contained cyanine Cy5labeled dCTP. Therefore, The PCR products were fluorescently labeled. The presence of multiple species-specific sequences within the iap gene enabled us to design different oligoprobes per species. The species-specific sequences of the iap gene used in this study were obtained from genBank and then aligned for phylogenetic analysis in order to identify and retrieve the sequences of homologues of the amplified iap gene analysed. 20 probes were used for detection and identification of 22 food isolates and clinical isolates of Listeria spp (L. monocytogenes, L. ivanovi), L. welshimeri, L. seeligeri, and L. grayi). Each bacterial gene was identified by hybridization to oligoprobes specific for each Listeria species and immobilized on a glass surface. The microarray analysis showed that 5 clinical isolates and 2 food isolates were identified listeria monocytogenes. Concerning the remaining 15 food isolates; 13 were identified listeria innocua and 2 isolates could not be identified by microarray based assay. Further phylogenetic and molecular analysis are required to design more species-specific probes for the identification of Listeria spp. Microarray-based assay is a simple and rapid method used for Listeria species discrimination

  19. DNA methylation analysis using CpG microarrays is impaired in benzopyrene exposed cells

    International Nuclear Information System (INIS)

    Epigenetic alterations have emerged as a key mechanism involved in tumorigenesis. These disruptions are partly due to environmental factors that change normal DNA methylation patterns necessary for transcriptional regulation and chromatin compaction. Microarray technologies are allowing environmentally susceptible epigenetic patterns to be mapped and the precise targets of environmentally induced alterations to be identified. Previously, we observed BaP-induced epigenetic events and cell cycle disruptions in breast cancer cell lines that included time- and concentration-dependent loss of proliferation as well as sequence-specific hypo- and hypermethylation events. In this present report, we further characterized epigenetic changes in BaP-exposed MCF-7 cells. We analyzed DNA methylation on a CpG island microarray platform with over 5400 unique genomic regions. Depleted and enriched microarray targets, representative of putative DNA methylation changes, were identified across the genome; however, subsequent sodium bisulfite analyses revealed no changes in DNA methylation at a number of these loci. Instead, we found that the identification of DNA methylation changes using this restriction enzyme-based microarray approach corresponded with the regions of DNA bound by the BaP derived DNA adducts. This DNA adduct formation occurs at both methylated and unmethylated CpG dinucleotides and affects PCR amplification during sample preparation. Our data suggest that caution should be exercised when interpreting data from comparative microarray experiments that rely on enzymatic reactions. These results are relevant to genome screening approaches involving environmental exposures in which DNA adduct formation at specific nucleotide sites may bias target acquisition and compromise the correct identification of epigenetically responsive genes

  20. Augmenting microarray data with literature-based knowledge to enhance gene regulatory network inference.

    Directory of Open Access Journals (Sweden)

    Guocai Chen

    2014-06-01

    Full Text Available Gene regulatory networks are a crucial aspect of systems biology in describing molecular mechanisms of the cell. Various computational models rely on random gene selection to infer such networks from microarray data. While incorporation of prior knowledge into data analysis has been deemed important, in practice, it has generally been limited to referencing genes in probe sets and using curated knowledge bases. We investigate the impact of augmenting microarray data with semantic relations automatically extracted from the literature, with the view that relations encoding gene/protein interactions eliminate the need for random selection of components in non-exhaustive approaches, producing a more accurate model of cellular behavior. A genetic algorithm is then used to optimize the strength of interactions using microarray data and an artificial neural network fitness function. The result is a directed and weighted network providing the individual contribution of each gene to its target. For testing, we used invasive ductile carcinoma of the breast to query the literature and a microarray set containing gene expression changes in these cells over several time points. Our model demonstrates significantly better fitness than the state-of-the-art model, which relies on an initial random selection of genes. Comparison to the component pathways of the KEGG Pathways in Cancer map reveals that the resulting networks contain both known and novel relationships. The p53 pathway results were manually validated in the literature. 60% of non-KEGG relationships were supported (74% for highly weighted interactions. The method was then applied to yeast data and our model again outperformed the comparison model. Our results demonstrate the advantage of combining gene interactions extracted from the literature in the form of semantic relations with microarray analysis in generating contribution-weighted gene regulatory networks. This methodology can make a