WorldWideScience

Sample records for a-madman annotation-based microarray

  1. Andrew Lees, a visionary mentored by a madman

    Directory of Open Access Journals (Sweden)

    Francisco Cardoso

    Full Text Available ABSTRACT Andrew Lees, Professor of Neurology at the National Hospital Queen Square (London, UK, has been recognized as the world’s most highly-cited researcher over the 200-year history of Parkinson’s Disease. Although he remains actively involved in the investigation of movement disorders, Prof. Lees embarked on a literary career that started in 2011 with the publication of a social history of his native Liverpool. His last work is Mentored by a Madman: The William Burroughs Experiment, which is reviewed here.

  2. Transculturation of Madness: The Double Origin of Lu Xun's "Diary of a Madman".

    Science.gov (United States)

    Ma, Xiaolu

    2015-01-01

    Over the years scholars have examined the allegorical features of the depiction of madness in Lu Xun's "Diary of a Madman," yet to date little research has taken into consideration the intercultural angle embedded in the narrative's intersection of three cultures, namely Russian, Japanese and Chinese. This paper traces the European-Japanese-Sino route of modern neologisms of madness to explore the introduction of such neologisms into the modern Chinese language and how it corresponds with changing patterns of knowledge and power. I use my study of transculturation on the macro scale to frame a reexamination of the lexicon in "Diary of a Madman." I focus especially on kuangren and pohaikuang, the two key words employed by Lu Xun, to see how they contribute to the ambiguity in his attitude towards the power struggle between the East and the West, the old and the new.

  3. 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.

  4. 论《红楼梦》与《狂人日记》的文化承继关系%On the Cultural Inheritance Between Dream of the Red Chamberand Diary of a Madman

    Institute of Scientific and Technical Information of China (English)

    陶徽希

    2012-01-01

    在中国文学史上,《红楼梦》作为古典文学的终点,《狂人日记》作为现代文学的开端,两者之间具有重要的文化承继关系。首先,《红楼梦》伤时骂世,《狂人日记》感时忧国,传承了中国文化的士人精神。其次,《红楼梦》第一次把"情"提高到形而上学的水平,以"女儿"作为理想世界的中心,对传统文化发起天翻地覆的革命;《狂人日记》则弃绝传统文化,渴望以"新文化"战胜"旧文化",把"孩子"看作"新文化"的希望。最后,《红楼梦》与《狂人日记》的主人公徘徊在传统文化和现代文化之间,前者进行精神探索,后者开始勇猛呐喊,孤独与分裂是他们的共同特征。%In the history of Chinese literature,Dream of the Red Chamber acted as the end of the classical literature,while Diary of a Madman was thought to be the beginning of the modern literature.However,there has been an important cultural inheritance between them.First,Dream of the Red Chamber heavily worried about and censured on the times,while Diary of a Madman showed the sense of obsession with China,both of which inherited the spirit of Chinese traditional scholars.Second,Dream of the Red Chamber was the first one that heightened "affection" to the metaphysical level and looked at "femininity" as the center of an ideal world,and launched tremendous changes on traditional culture.Diary of a Madman abandoned the traditional culture,and was eager to use "new culture" to defeat "old culture".The "child" was looked at as a metaphor of the hope of "new culture".Finally,the leading characters of both novels wandered between the culture of tradition and modernization,Dream of the Red Chamber explored spiritual world,while Diary of a Madman began to yell bravely.Loneliness and split are their common features.

  5. DisBlue+: A distributed annotation-based C# compiler

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    Samir E. AbdelRahman

    2010-06-01

    Full Text Available Many programming languages utilize annotations to add useful information to the program but they still result in more tokens to be compiled and hence slower compilation time. Any current distributed compiler breaks the program into scattered disjoint pieces to speed up the compilation. However, these pieces cooperate synchronously and depend highly on each other. This causes massive overhead since messages, symbols, or codes must be roamed throughout the network. This paper presents two promising compilers named annotation-based C# (Blue+ and distributed annotation-based C# (DisBlue+. The proposed Blue+ annotation is based on axiomatic semantics to replace the if/loop constructs. As the developer tends to use many (complex conditions and repeat them in the program, such annotations reduce the compilation scanning time and increases the whole code readability. Built on the top of Blue+, DisBlue+ presents its proposed distributed concept which is to divide each program class to its prototype and definition, as disjoint distributed pieces, such that each class definition is compiled with only its related compiled prototypes (interfaces. Such concept reduces the amount of code transferred over the network, minimizes the dependencies among the disjoint pieces, and removes any possible synchronization between them. To test their efficiencies, Blue+ and DisBlue+ were verified with large-size codes against some existing compilers namely Javac, DJavac, and CDjava.

  6. Carbohydrate microarrays

    DEFF Research Database (Denmark)

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

    2012-01-01

    In the last decade, carbohydrate microarrays have been core technologies for analyzing carbohydrate-mediated recognition events in a high-throughput fashion. A number of methods have been exploited for immobilizing glycans on the solid surface in a microarray format. This microarray-based technol...

  7. Carbohydrate microarrays

    DEFF Research Database (Denmark)

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

    2012-01-01

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

  8. 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.

  9. 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.

  10. Introduction to microarray technology.

    Science.gov (United States)

    Dufva, Martin

    2009-01-01

    DNA microarrays can be used for large number of application where high-throughput is needed. The ability to probe a sample for hundred to million different molecules at once has made DNA microarray one of the fastest growing techniques since its introduction about 15 years ago. Microarray technology can be used for large scale genotyping, gene expression profiling, comparative genomic hybridization and resequencing among other applications. Microarray technology is a complex mixture of numerous technology and research fields such as mechanics, microfabrication, chemistry, DNA behaviour, microfluidics, enzymology, optics and bioinformatics. This chapter will give an introduction to each five basic steps in microarray technology that includes fabrication, target preparation, hybridization, detection and data analysis. Basic concepts and nomenclature used in the field of microarray technology and their relationships will also be explained.

  11. 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.

  12. Microarray Analysis in Glioblastomas

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    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

  13. Maize microarray annotation database

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    Berger Dave K

    2011-10-01

    Full Text Available Abstract Background Microarray technology has matured over the past fifteen years into a cost-effective solution with established data analysis protocols for global gene expression profiling. The Agilent-016047 maize 44 K microarray was custom-designed from EST sequences, but only reporter sequences with EST accession numbers are publicly available. The following information is lacking: (a reporter - gene model match, (b number of reporters per gene model, (c potential for cross hybridization, (d sense/antisense orientation of reporters, (e position of reporter on B73 genome sequence (for eQTL studies, and (f functional annotations of genes represented by reporters. To address this, we developed a strategy to annotate the Agilent-016047 maize microarray, and built a publicly accessible annotation database. Description Genomic annotation of the 42,034 reporters on the Agilent-016047 maize microarray was based on BLASTN results of the 60-mer reporter sequences and their corresponding ESTs against the maize B73 RefGen v2 "Working Gene Set" (WGS predicted transcripts and the genome sequence. The agreement between the EST, WGS transcript and gDNA BLASTN results were used to assign the reporters into six genomic annotation groups. These annotation groups were: (i "annotation by sense gene model" (23,668 reporters, (ii "annotation by antisense gene model" (4,330; (iii "annotation by gDNA" without a WGS transcript hit (1,549; (iv "annotation by EST", in which case the EST from which the reporter was designed, but not the reporter itself, has a WGS transcript hit (3,390; (v "ambiguous annotation" (2,608; and (vi "inconclusive annotation" (6,489. Functional annotations of reporters were obtained by BLASTX and Blast2GO analysis of corresponding WGS transcripts against GenBank. The annotations are available in the Maize Microarray Annotation Database http://MaizeArrayAnnot.bi.up.ac.za/, as well as through a GBrowse annotation file that can be uploaded to

  14. 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.

  15. Microarray Applications in Cancer Research

    Science.gov (United States)

    Kim, Il-Jin; Kang, Hio Chung

    2004-01-01

    DNA microarray technology permits simultaneous analysis of thousands of DNA sequences for genomic research and diagnostics applications. Microarray technology represents the most recent and exciting advance in the application of hybridization-based technology for biological sciences analysis. This review focuses on the classification (oligonucleotide vs. cDNA) and application (mutation-genotyping vs. gene expression) of microarrays. Oligonucleotide microarrays can be used both in mutation-genotyping and gene expression analysis, while cDNA microarrays can only be used in gene expression analysis. We review microarray mutation analysis, including examining the use of three oligonucleotide microarrays developed in our laboratory to determine mutations in RET, β-catenin and K-ras genes. We also discuss the use of the Affymetrix GeneChip in mutation analysis. We review microarray gene expression analysis, including the classifying of such studies into four categories: class comparison, class prediction, class discovery and identification of biomarkers. PMID:20368836

  16. Biolog phenotype microarrays.

    Science.gov (United States)

    Shea, April; Wolcott, Mark; Daefler, Simon; Rozak, David A

    2012-01-01

    Phenotype microarrays nicely complement traditional genomic, transcriptomic, and proteomic analysis by offering opportunities for researchers to ground microbial systems analysis and modeling in a broad yet quantitative assessment of the organism's physiological response to different metabolites and environments. Biolog phenotype assays achieve this by coupling tetrazolium dyes with minimally defined nutrients to measure the impact of hundreds of carbon, nitrogen, phosphorous, and sulfur sources on redox reactions that result from compound-induced effects on the electron transport chain. Over the years, we have used Biolog's reproducible and highly sensitive assays to distinguish closely related bacterial isolates, to understand their metabolic differences, and to model their metabolic behavior using flux balance analysis. This chapter describes Biolog phenotype microarray system components, reagents, and methods, particularly as they apply to bacterial identification, characterization, and metabolic analysis.

  17. Analyzing Microarray Data.

    Science.gov (United States)

    Hung, Jui-Hung; Weng, Zhiping

    2017-03-01

    Because there is no widely used software for analyzing RNA-seq data that has a graphical user interface, this protocol provides an example of analyzing microarray data using Babelomics. This analysis entails performing quantile normalization and then detecting differentially expressed genes associated with the transgenesis of a human oncogene c-Myc in mice. Finally, hierarchical clustering is performed on the differentially expressed genes using the Cluster program, and the results are visualized using TreeView.

  18. 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.

  19. 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.

  20. Carbohydrate Microarrays in Plant Science

    DEFF Research Database (Denmark)

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

    2012-01-01

    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......-throughput analysis of nucleotides, proteins, and increasingly carbohydrates. Using microarrays, the abundance of and interactions between hundreds and thousands of molecules can be assessed simultaneously using very small amounts of analytes. Here we show that carbohydrate microarrays are multifunctional tools...... 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....

  1. Transfection microarray and the applications.

    Science.gov (United States)

    Miyake, Masato; Yoshikawa, Tomohiro; Fujita, Satoshi; Miyake, Jun

    2009-05-01

    Microarray transfection has been extensively studied for high-throughput functional analysis of mammalian cells. However, control of efficiency and reproducibility are the critical issues for practical use. By using solid-phase transfection accelerators and nano-scaffold, we provide a highly efficient and reproducible microarray-transfection device, "transfection microarray". The device would be applied to the limited number of available primary cells and stem cells not only for large-scale functional analysis but also reporter-based time-lapse cellular event analysis.

  2. Microarray Scanner for Fluorescence Detection

    Institute of Scientific and Technical Information of China (English)

    Wang Liqiang; Lu zukang; Li Yingsheng; Zheng Xufeng

    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.

  3. Microarray Technologies in Fungal Diagnostics.

    Science.gov (United States)

    Rupp, Steffen

    2017-01-01

    Microarray technologies have been a major research tool in the last decades. In addition they have been introduced into several fields of diagnostics including diagnostics of infectious diseases. Microarrays are highly parallelized assay systems that initially were developed for multiparametric nucleic acid detection. From there on they rapidly developed towards a tool for the detection of all kind of biological compounds (DNA, RNA, proteins, cells, nucleic acids, carbohydrates, etc.) or their modifications (methylation, phosphorylation, etc.). The combination of closed-tube systems and lab on chip devices with microarrays further enabled a higher automation degree with a reduced contamination risk. Microarray-based diagnostic applications currently complement and may in the future replace classical methods in clinical microbiology like blood cultures, resistance determination, microscopic and metabolic analyses as well as biochemical or immunohistochemical assays. In addition, novel diagnostic markers appear, like noncoding RNAs and miRNAs providing additional room for novel nucleic acid based biomarkers. Here I focus an microarray technologies in diagnostics and as research tools, based on nucleic acid-based arrays.

  4. Carbohydrate microarrays in plant science.

    Science.gov (United States)

    Fangel, Jonatan U; Pedersen, Henriette L; Vidal-Melgosa, Silvia; Ahl, Louise I; Salmean, Armando Asuncion; Egelund, Jack; Rydahl, Maja Gro; Clausen, Mads H; Willats, William G T

    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-throughput analysis of nucleotides, proteins, and increasingly carbohydrates. Using microarrays, the abundance of and interactions between hundreds and thousands of molecules can be assessed simultaneously using very small amounts of analytes. Here we show that carbohydrate microarrays are multifunctional tools 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.

  5. Glass slides to DNA microarrays

    Directory of Open Access Journals (Sweden)

    Samuel D Conzone

    2004-03-01

    Full Text Available A tremendous interest in deoxyribonucleic acid (DNA characterization tools was spurred by the mapping and sequencing of the human genome. New tools were needed, beginning in the early 1990s, to cope with the unprecedented amount of genomic information that was being discovered. Such needs led to the development of DNA microarrays; tiny gene-based sensors traditionally prepared on coated glass microscope slides. The following review is intended to provide historical insight into the advent of the DNA microarray, followed by a description of the technology from both the application and fabrication points of view. Finally, the unmet challenges and needs associated with DNA microarrays will be described to define areas of potential future developments for the materials researcher.

  6. Phenotypic MicroRNA Microarrays

    OpenAIRE

    2013-01-01

    Microarray technology has become a very popular approach in cases where multiple experiments need to be conducted repeatedly or done with a variety of samples. In our lab, we are applying our high density spots microarray approach to microscopy visualization of the effects of transiently introduced siRNA or cDNA on cellular morphology or phenotype. In this publication, we are discussing the possibility of using this micro-scale high throughput process to study the role of microRNAs in the bio...

  7. Combining microarrays and genetic analysis

    NARCIS (Netherlands)

    Alberts, Rudi; Fu, Jingyuan; Swertz, Morris A.; Lubbers, L. Alrik; Albers, Casper J.; Jansen, Ritsert C.

    2005-01-01

    Gene expression can be studied at a genome-wide scale with the aid of modern microarray technologies. Expression profiling of tens to hundreds of individuals in a genetic population can reveal the consequences of genetic variation. In this paper it is argued that the design and analysis of such a

  8. Combining microarrays and genetic analysis

    NARCIS (Netherlands)

    Alberts, Rudi; Fu, Jingyuan; Swertz, Morris A.; Lubbers, L. Alrik; Albers, Casper J.; Jansen, Ritsert C.

    2005-01-01

    Gene expression can be studied at a genome-wide scale with the aid of modern microarray technologies. Expression profiling of tens to hundreds of individuals in a genetic population can reveal the consequences of genetic variation. In this paper it is argued that the design and analysis of such a st

  9. Picky: oligo microarray design for large genomes

    National Research Council Canada - National Science Library

    Chou, Hui-Hsien; Hsia, An-Ping; Mooney, Denise L; Schnable, Patrick S

    2004-01-01

    Many large genomes are getting sequenced nowadays. Biologists are eager to start microarray analysis taking advantage of all known genes of a species, but existing microarray design tools were very inefficient for large genomes...

  10. 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.

  11. Biclustering of time series microarray data.

    Science.gov (United States)

    Meng, Jia; Huang, Yufei

    2012-01-01

    Clustering is a popular data exploration technique widely used in microarray data analysis. In this chapter, we review ideas and algorithms of bicluster and its applications in time series microarray analysis. We introduce first the concept and importance of biclustering and its different variations. We then focus our discussion on the popular iterative signature algorithm (ISA) for searching biclusters in microarray dataset. Next, we discuss in detail the enrichment constraint time-dependent ISA (ECTDISA) for identifying biologically meaningful temporal transcription modules from time series microarray dataset. In the end, we provide an example of ECTDISA application to time series microarray data of Kaposi's Sarcoma-associated Herpesvirus (KSHV) infection.

  12. The Current Status of DNA Microarrays

    Science.gov (United States)

    Shi, Leming; Perkins, Roger G.; Tong, Weida

    DNA microarray technology that allows simultaneous assay of thousands of genes in a single experiment has steadily advanced to become a mainstream method used in research, and has reached a stage that envisions its use in medical applications and personalized medicine. Many different strategies have been developed for manufacturing DNA microarrays. In this chapter, we discuss the manufacturing characteristics of seven microarray platforms that were used in a recently completed large study by the MicroArray Quality Control (MAQC) consortium, which evaluated the concordance of results across these platforms. The platforms can be grouped into three categories: (1) in situ synthesis of oligonucleotide probes on microarrays (Affymetrix GeneChip® arrays based on photolithography synthesis and Agilent's arrays based on inkjet synthesis); (2) spotting of presynthesized oligonucleotide probes on microarrays (GE Healthcare's CodeLink system, Applied Biosystems' Genome Survey Microarrays, and the custom microarrays printed with Operon's oligonucleotide set); and (3) deposition of presynthesized oligonucleotide probes on bead-based microarrays (Illumina's BeadChip microarrays). We conclude this chapter with our views on the challenges and opportunities toward acceptance of DNA microarray data in clinical and regulatory settings.

  13. Microarray Inspector: tissue cross contamination detection tool for microarray data.

    Science.gov (United States)

    Stępniak, Piotr; Maycock, Matthew; Wojdan, Konrad; Markowska, Monika; Perun, Serhiy; Srivastava, Aashish; Wyrwicz, Lucjan S; Świrski, Konrad

    2013-01-01

    Microarray technology changed the landscape of contemporary life sciences by providing vast amounts of expression data. Researchers are building up repositories of experiment results with various conditions and samples which serve the scientific community as a precious resource. Ensuring that the sample is of high quality is of utmost importance to this effort. The task is complicated by the fact that in many cases datasets lack information concerning pre-experimental quality assessment. Transcription profiling of tissue samples may be invalidated by an error caused by heterogeneity of the material. The risk of tissue cross contamination is especially high in oncological studies, where it is often difficult to extract the sample. Therefore, there is a need of developing a method detecting tissue contamination in a post-experimental phase. We propose Microarray Inspector: customizable, user-friendly software that enables easy detection of samples containing mixed tissue types. The advantage of the tool is that it uses raw expression data files and analyses each array independently. In addition, the system allows the user to adjust the criteria of the analysis to conform to individual needs and research requirements. The final output of the program contains comfortable to read reports about tissue contamination assessment with detailed information about the test parameters and results. Microarray Inspector provides a list of contaminant biomarkers needed in the analysis of adipose tissue contamination. Using real data (datasets from public repositories) and our tool, we confirmed high specificity of the software in detecting contamination. The results indicated the presence of adipose tissue admixture in a range from approximately 4% to 13% in several tested surgical samples.

  14. Surface characterization of carbohydrate microarrays.

    Science.gov (United States)

    Scurr, David J; Horlacher, Tim; Oberli, Matthias A; Werz, Daniel B; Kroeck, Lenz; Bufali, Simone; Seeberger, Peter H; Shard, Alexander G; Alexander, Morgan R

    2010-11-16

    Carbohydrate microarrays are essential tools to determine the biological function of glycans. Here, we analyze a glycan array by time-of-flight secondary ion mass spectrometry (ToF-SIMS) to gain a better understanding of the physicochemical properties of the individual spots and to improve carbohydrate microarray quality. The carbohydrate microarray is prepared by piezo printing of thiol-terminated sugars onto a maleimide functionalized glass slide. The hyperspectral ToF-SIMS imaging data are analyzed by multivariate curve resolution (MCR) to discern secondary ions from regions of the array containing saccharide, linker, salts from the printing buffer, and the background linker chemistry. Analysis of secondary ions from the linker common to all of the sugar molecules employed reveals a relatively uniform distribution of the sugars within the spots formed from solutions with saccharide concentration of 0.4 mM and less, whereas a doughnut shape is often formed at higher-concentration solutions. A detailed analysis of individual spots reveals that in the larger spots the phosphate buffered saline (PBS) salts are heterogeneously distributed, apparently resulting in saccharide concentrated at the rim of the spots. A model of spot formation from the evaporating sessile drop is proposed to explain these observations. Saccharide spot diameters increase with saccharide concentration due to a reduction in surface tension of the saccharide solution compared to PBS. The multivariate analytical partial least squares (PLS) technique identifies ions from the sugars that in the complex ToF-SIMS spectra correlate with the binding of galectin proteins.

  15. Integrated Amplification Microarrays for Infectious Disease Diagnostics

    Directory of Open Access Journals (Sweden)

    Darrell P. Chandler

    2012-11-01

    Full Text Available This overview describes microarray-based tests that combine solution-phase amplification chemistry and microarray hybridization within a single microfluidic chamber. The integrated biochemical approach improves microarray workflow for diagnostic applications by reducing the number of steps and minimizing the potential for sample or amplicon cross-contamination. Examples described herein illustrate a basic, integrated approach for DNA and RNA genomes, and a simple consumable architecture for incorporating wash steps while retaining an entirely closed system. It is anticipated that integrated microarray biochemistry will provide an opportunity to significantly reduce the complexity and cost of microarray consumables, equipment, and workflow, which in turn will enable a broader spectrum of users to exploit the intrinsic multiplexing power of microarrays for infectious disease diagnostics.

  16. Spotting effect in microarray experiments

    Directory of Open Access Journals (Sweden)

    Mary-Huard Tristan

    2004-05-01

    Full Text Available Abstract Background Microarray data must be normalized because they suffer from multiple biases. We have identified a source of spatial experimental variability that significantly affects data obtained with Cy3/Cy5 spotted glass arrays. It yields a periodic pattern altering both signal (Cy3/Cy5 ratio and intensity across the array. Results Using the variogram, a geostatistical tool, we characterized the observed variability, called here the spotting effect because it most probably arises during steps in the array printing procedure. Conclusions The spotting effect is not appropriately corrected by current normalization methods, even by those addressing spatial variability. Importantly, the spotting effect may alter differential and clustering analysis.

  17. Living Cell Microarrays: An Overview of Concepts

    Directory of Open Access Journals (Sweden)

    Rebecca Jonczyk

    2016-05-01

    Full Text Available Living cell microarrays are a highly efficient cellular screening system. Due to the low number of cells required per spot, cell microarrays enable the use of primary and stem cells and provide resolution close to the single-cell level. Apart from a variety of conventional static designs, microfluidic microarray systems have also been established. An alternative format is a microarray consisting of three-dimensional cell constructs ranging from cell spheroids to cells encapsulated in hydrogel. These systems provide an in vivo-like microenvironment and are preferably used for the investigation of cellular physiology, cytotoxicity, and drug screening. Thus, many different high-tech microarray platforms are currently available. Disadvantages of many systems include their high cost, the requirement of specialized equipment for their manufacture, and the poor comparability of results between different platforms. In this article, we provide an overview of static, microfluidic, and 3D cell microarrays. In addition, we describe a simple method for the printing of living cell microarrays on modified microscope glass slides using standard DNA microarray equipment available in most laboratories. Applications in research and diagnostics are discussed, e.g., the selective and sensitive detection of biomarkers. Finally, we highlight current limitations and the future prospects of living cell microarrays.

  18. "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.

  19. 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

  20. Pineal function: impact of microarray analysis

    DEFF Research Database (Denmark)

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

    2009-01-01

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

  1. The EADGENE Microarray Data Analysis Workshop

    NARCIS (Netherlands)

    Koning, de D.J.; Jaffrezic, F.; Lund, M.S.; Watson, M.; Channing, C.; Hulsegge, B.; Pool, M.H.; Buitenhuis, B.; Hedegaard, J.; Hornshoj, H.; Sorensen, P.; Marot, G.; Delmas, C.; Lê Cao, K.A.; San Cristobal, M.; Baron, M.D.; Malinverni, R.; Stella, A.; Brunner, R.M.; Seyfert, H.M.; Jensen, K.; Mouzaki, D.; Waddington, D.; Jiménez-Marín, A.; Perez-Alegre, M.; Perez-Reinado, E.; Closset, R.; Detilleux, J.C.; Dovc, P.; Lavric, M.; Nie, H.; Janss, L.

    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

  2. In control: systematic assessment of microarray performance.

    Science.gov (United States)

    van Bakel, Harm; Holstege, Frank C P

    2004-10-01

    Expression profiling using DNA microarrays is a powerful technique that is widely used in the life sciences. How reliable are microarray-derived measurements? The assessment of performance is challenging because of the complicated nature of microarray experiments and the many different technology platforms. There is a mounting call for standards to be introduced, and this review addresses some of the issues that are involved. Two important characteristics of performance are accuracy and precision. The assessment of these factors can be either for the purpose of technology optimization or for the evaluation of individual microarray hybridizations. Microarray performance has been evaluated by at least four approaches in the past. Here, we argue that external RNA controls offer the most versatile system for determining performance and describe how such standards could be implemented. Other uses of external controls are discussed, along with the importance of probe sequence availability and the quantification of labelled material.

  3. 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...

  4. Chaotic mixer improves microarray hybridization.

    Science.gov (United States)

    McQuain, Mark K; Seale, Kevin; Peek, Joel; Fisher, Timothy S; Levy, Shawn; Stremler, Mark A; Haselton, Frederick R

    2004-02-15

    Hybridization is an important aspect of microarray experimental design which influences array signal levels and the repeatability of data within an array and across different arrays. Current methods typically require 24h and use target inefficiently. In these studies, we compare hybridization signals obtained in conventional static hybridization, which depends on diffusional target delivery, with signals obtained in a dynamic hybridization chamber, which employs a fluid mixer based on chaotic advection theory to deliver targets across a conventional glass slide array. Microarrays were printed with a pattern of 102 identical probe spots containing a 65-mer oligonucleotide capture probe. Hybridization of a 725-bp fluorescently labeled target was used to measure average target hybridization levels, local signal-to-noise ratios, and array hybridization uniformity. Dynamic hybridization for 1h with 1 or 10ng of target DNA increased hybridization signal intensities approximately threefold over a 24-h static hybridization. Similarly, a 10- or 60-min dynamic hybridization of 10ng of target DNA increased hybridization signal intensities fourfold over a 24h static hybridization. In time course studies, static hybridization reached a maximum within 8 to 12h using either 1 or 10ng of target. In time course studies using the dynamic hybridization chamber, hybridization using 1ng of target increased to a maximum at 4h and that using 10ng of target did not vary over the time points tested. In comparison to static hybridization, dynamic hybridization reduced the signal-to-noise ratios threefold and reduced spot-to-spot variation twofold. Therefore, we conclude that dynamic hybridization based on a chaotic mixer design improves both the speed of hybridization and the maximum level of hybridization while increasing signal-to-noise ratios and reducing spot-to-spot variation.

  5. 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.

  6. 基于彩色描述子和主题模型的新闻标注%News Annotation Based on Color Descriptors and Topic Models

    Institute of Scientific and Technical Information of China (English)

    杨明; 康南南; 赵玉芳

    2014-01-01

    In order to reduce the workload of journalists and to improve the accuracy of information annota-tion ,this paper addresses the semantic annotation based on images which integrate color descriptors and topic models .The algorithm uses the color scale invariant feature transform (RGB-SIFT) to get the low-level visual feature descriptor and then using K-means algorithm to obtain the image dictionary and visual words .Term frequency-inverse document frequency (TF-IDF) is used to filter the news text .The latent Dirichlet allocation (LDA ) model successfully reflects the high level features and the mixed features , which integrate the RGB and SIFT features with the filtered news text .An experiment shows that our method achieves higher effectiveness compared to some traditional approaches applied to image annotation .%为了减轻新闻工作者的负担以及提高信息标注的准确性,本文针对新闻及相关图片提出了融合彩色描述子和主题模型的自动标注算法。该算法利用彩色的尺度不变特征转换(RGB-SIFT )得到图像的底层特征描述子,通过K均值聚类算法得到图像的视觉单词及词典,利用词频逆向文件频率(T F-ID F )对新闻的文本信息进行过滤。同时将视觉单词和过滤后的文本信息看作混合文档,利用改进的主题模型对该文档新闻进行自动标注。实验表明该算法提高了对新闻标注的准确率。

  7. Review: DNA microarray technology and drug development

    Directory of Open Access Journals (Sweden)

    Sana Khan

    2010-01-01

    Full Text Available On the contrary to slow and non specific traditional drug discovery methods, DNA microarray technology could accelerate the identification of potential drugs for treating diseases like cancer, AIDS and provide fruitful results in the drug discovery. The technique provides efficient automation and maximum flexibility to the researchers and can test thousand compounds at a time. Scientists find DNA microarray useful in disease diagnosis, monitoring desired and adverse outcomes of therapeutic interventions, as well as, in the selection, assessment and quality con-trol of the potential drugs. In the current scenario, where new pathogens are expected every year, DNA microarray promises as an efficient technology to detect new organisms in a short time. Classification of carcinomas at the molecular level and prediction of how various types of tumor respond to different therapeutic agents can be made possible with the use of microarray analysis. Also, microarray technique can prove instrumental in personalized medicines development by providing microarray data of a patient which could be used for identifying diseases, treatment specific to individual and trailing disease prognosis. Microarray analysis could be beneficial in the area of molecular medicines for analysis of genetic variations and functions of genes in normal individuals and diseased conditions. The technique can give satisfactory results in single nucleotide polymorphism (SNP analysis and pharmacogenomics studies. The challenges that arise with the technology are high degree of variability with data obtained, frequent up gradation of methods and machines and lack of trained manpower. Despite this, DNA micro-array promises to be the next generation sequencer which could explain how organisms evolve and adapt looking at the whole genome. In a nutshell, Microarray technology makes it possible for molecular biologists to analyze simultaneously thousands of DNA samples and monitor their

  8. Diagnostic and analytical applications of protein microarrays

    DEFF Research Database (Denmark)

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

    2005-01-01

    years. A genome-scale protein microarray has been demonstrated for identifying protein-protein interactions as well as for rapid identification of protein binding to a particular drug. Furthermore, protein microarrays have been shown as an efficient tool in cancer profiling, detection of bacteria...... and toxins, identification of allergen reactivity and autoantibodies. They have also demonstrated the ability to measure the absolute concentration of small molecules. Besides their capacity for parallel diagnostics, microarrays can be more sensitive than traditional methods such as enzyme...... and be amenable to automation or integrated into easy-to-use systems, such as micrototal analysis systems or point-of-care devices....

  9. Microarrays--analysis of signaling pathways.

    Science.gov (United States)

    Ramachandran, Anassuya; Black, Michael A; Shelling, Andrew N; Love, Donald R

    2008-01-01

    Microarrays provide a powerful means of analyzing the expression level of multiple transcripts in two sample populations. In this study, we have used microarray technology to identify genes that are differentially regulated in response to activin-treated ovarian cancer cells. We find a number of biologically relevant genes that are involved in regulating activin signaling and genes potentially contributing to activin-mediated growth arrest appear to be differentially regulated. Thus, microarrays are an important tool for dissecting gene expression changes in normal physiological processes and disease.

  10. 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.

  11. 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...

  12. Quality Visualization of Microarray Datasets Using Circos

    Directory of Open Access Journals (Sweden)

    Martin Koch

    2012-08-01

    Full Text Available Quality control and normalization is considered the most important step in the analysis of microarray data. At present there are various methods available for quality assessments of microarray datasets. However there seems to be no standard visualization routine, which also depicts individual microarray quality. Here we present a convenient method for visualizing the results of standard quality control tests using Circos plots. In these plots various quality measurements are drawn in a circular fashion, thus allowing for visualization of the quality and all outliers of each distinct array within a microarray dataset. The proposed method is intended for use with the Affymetrix Human Genome platform (i.e., GPL 96, GPL570 and GPL571. Circos quality measurement plots are a convenient way for the initial quality estimate of Affymetrix datasets that are stored in publicly available databases.

  13. PATMA: parser of archival tissue microarray

    Directory of Open Access Journals (Sweden)

    Lukasz Roszkowiak

    2016-12-01

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

  14. PATMA: parser of archival tissue microarray.

    Science.gov (United States)

    Roszkowiak, Lukasz; Lopez, Carlos

    2016-01-01

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

  15. 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.

  16. A Method of Microarray Data Storage Using Array Data Type

    OpenAIRE

    Tsoi, Lam C.; Zheng, W Jim

    2007-01-01

    A well-designed microarray database can provide valuable information on gene expression levels. However, designing an efficient microarray database with minimum space usage is not an easy task since designers need to integrate the microarray data with the information of genes, probe annotation, and the descriptions of each microarray experiment. Developing better methods to store microarray data can greatly improve the efficiency and usefulness of such data. A new schema is proposed to store ...

  17. Chromosomal microarray versus karyotyping for prenatal diagnosis.

    Science.gov (United States)

    Wapner, Ronald J; Martin, Christa Lese; Levy, Brynn; Ballif, Blake C; Eng, Christine M; Zachary, Julia M; Savage, Melissa; Platt, Lawrence D; Saltzman, Daniel; Grobman, William A; Klugman, Susan; Scholl, Thomas; Simpson, Joe Leigh; McCall, Kimberly; Aggarwal, Vimla S; Bunke, Brian; Nahum, Odelia; Patel, Ankita; Lamb, Allen N; Thom, Elizabeth A; Beaudet, Arthur L; Ledbetter, David H; Shaffer, Lisa G; Jackson, Laird

    2012-12-06

    Chromosomal microarray analysis has emerged as a primary diagnostic tool for the evaluation of developmental delay and structural malformations in children. We aimed to evaluate the accuracy, efficacy, and incremental yield of chromosomal microarray analysis as compared with karyotyping for routine prenatal diagnosis. Samples from women undergoing prenatal diagnosis at 29 centers were sent to a central karyotyping laboratory. Each sample was split in two; standard karyotyping was performed on one portion and the other was sent to one of four laboratories for chromosomal microarray. We enrolled a total of 4406 women. Indications for prenatal diagnosis were advanced maternal age (46.6%), abnormal result on Down's syndrome screening (18.8%), structural anomalies on ultrasonography (25.2%), and other indications (9.4%). In 4340 (98.8%) of the fetal samples, microarray analysis was successful; 87.9% of samples could be used without tissue culture. Microarray analysis of the 4282 nonmosaic samples identified all the aneuploidies and unbalanced rearrangements identified on karyotyping but did not identify balanced translocations and fetal triploidy. In samples with a normal karyotype, microarray analysis revealed clinically relevant deletions or duplications in 6.0% with a structural anomaly and in 1.7% of those whose indications were advanced maternal age or positive screening results. In the context of prenatal diagnostic testing, chromosomal microarray analysis identified additional, clinically significant cytogenetic information as compared with karyotyping and was equally efficacious in identifying aneuploidies and unbalanced rearrangements but did not identify balanced translocations and triploidies. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and others; ClinicalTrials.gov number, NCT01279733.).

  18. Review: DNA Microarray Technology and Drug Development

    Directory of Open Access Journals (Sweden)

    Sushma Drabu

    2010-01-01

    Full Text Available

    On the contrary to slow and non specific traditional drug discovery methods, DNA microarray technology could
    accelerate the identification of potential drugs for treating diseases like cancer, AIDS and provide fruitful results in
    the drug discovery. The technique provides efficient automation and maximum flexibility to the researchers and
    can test thousand compounds at a time. Scientists find DNA microarray useful in disease diagnosis, monitoring
    desired and adverse outcomes of therapeutic interventions, as well as, in the selection, assessment and quality control
    of the potential drugs. In the current scenario, where new pathogens are expected every year, DNA microarray
    promises as an efficient technology to detect new organisms in a short time. Classification of carcinomas at the
    molecular level and prediction of how various types of tumor respond to different therapeutic agents can be made
    possible with the use of microarray analysis. Also, microarray technique can prove instrumental in personalized
    medicines development by providing microarray data of a patient which could be used for identifying diseases,
    treatment specific to individual and trailing disease prognosis. Microarray analysis could be beneficial in the area
    of molecular medicines for analysis of genetic variations and functions of genes in normal individuals and diseased
    conditions. The technique can give satisfactory results in single nucleotide polymorphism (SNP analysis and
    pharmacogenomics studies. The challenges that arise with the technology are high degree of variability with data
    obtained, frequent up gradation of methods and machines and lack of trained manpower. Despite this, DNA microarray
    promises to be the next generation sequencer which could explain how organisms evolve and adapt looking
    at the whole

  19. Posttranslational Modification Assays on Functional Protein Microarrays.

    Science.gov (United States)

    Neiswinger, Johnathan; Uzoma, Ijeoma; Cox, Eric; Rho, HeeSool; Jeong, Jun Seop; Zhu, Heng

    2016-10-03

    Protein microarray technology provides a straightforward yet powerful strategy for identifying substrates of posttranslational modifications (PTMs) and studying the specificity of the enzymes that catalyze these reactions. Protein microarray assays can be designed for individual enzymes or a mixture to establish connections between enzymes and substrates. Assays for four well-known PTMs-phosphorylation, acetylation, ubiquitylation, and SUMOylation-have been developed and are described here for use on functional protein microarrays. Phosphorylation and acetylation require a single enzyme and are easily adapted for use on an array. The ubiquitylation and SUMOylation cascades are very similar, and the combination of the E1, E2, and E3 enzymes plus ubiquitin or SUMO protein and ATP is sufficient for in vitro modification of many substrates.

  20. 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

  1. Hybridization and Selective Release of DNA Microarrays

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-11-29

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

  2. 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

  3. 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.

  4. Diagnostic and analytical applications of protein microarrays

    DEFF Research Database (Denmark)

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

    2005-01-01

    -linked immunosorbent assay, mass spectrometry or high-performance liquid chromatography-based assays. However, for protein and antibody arrays to be successfully introduced into diagnostics, the biochemistry of immunomicroarrays must be better characterized and simplified, they must be validated in a clinical setting...... years. A genome-scale protein microarray has been demonstrated for identifying protein-protein interactions as well as for rapid identification of protein binding to a particular drug. Furthermore, protein microarrays have been shown as an efficient tool in cancer profiling, detection of bacteria...

  5. Microarrays - A Key Technology for Glycobiology

    Science.gov (United States)

    Liu, Yan; Feizi, Ten

    Carbohydrate chains of glycoproteins , glycolipids , and proteoglycans can mediate processes of biological and medical importance through their interactions with complementary proteins. The unraveling of these interactions is a priority therefore in biomedical sciences. Carbohydrate microarray technology is a new development at the frontiers of glycomics that has revolutionized the study of carbohydrate-protein interactions and the elucidation of their specificities in endogenous biological processes, immune defense mechanisms, and microbe-host interactions. In this chapter we briefly touch upon the principles of numerous platforms since the introduction of carbohydrate microarrays in 2002, and we highlight platforms that are beyond proof-of-concept, and have provided new biological information.

  6. Development and application of a microarray meter tool to optimize microarray experiments

    Directory of Open Access Journals (Sweden)

    Rouse Richard JD

    2008-07-01

    Full Text Available Abstract Background Successful microarray experimentation requires a complex interplay between the slide chemistry, the printing pins, the nucleic acid probes and targets, and the hybridization milieu. Optimization of these parameters and a careful evaluation of emerging slide chemistries are a prerequisite to any large scale array fabrication effort. We have developed a 'microarray meter' tool which assesses the inherent variations associated with microarray measurement prior to embarking on large scale projects. Findings The microarray meter consists of nucleic acid targets (reference and dynamic range control and probe components. Different plate designs containing identical probe material were formulated to accommodate different robotic and pin designs. We examined the variability in probe quality and quantity (as judged by the amount of DNA printed and remaining post-hybridization using three robots equipped with capillary printing pins. Discussion The generation of microarray data with minimal variation requires consistent quality control of the (DNA microarray manufacturing and experimental processes. Spot reproducibility is a measure primarily of the variations associated with printing. The microarray meter assesses array quality by measuring the DNA content for every feature. It provides a post-hybridization analysis of array quality by scoring probe performance using three metrics, a a measure of variability in the signal intensities, b a measure of the signal dynamic range and c a measure of variability of the spot morphologies.

  7. 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.

  8. 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.

  9. Microarray Assisted Gene Discovery in Ulcerative Colitis

    DEFF Research Database (Denmark)

    Brusgaard, Klaus

    ), and microarray based expression studies. In IBD the increased production of chemo attractants from the inflamed microenvironment results in recruitment of activated CD4+ T lymphocytes which results in tissue damage. Where Th1 cell-derived cytokines has been reported to be essential mediators in CD with high (IFN...

  10. 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.

  11. Pineal function : Impact of microarray analysis

    NARCIS (Netherlands)

    Klein, David C.; Bailey, Michael J.; Carter, David A.; Kim, Jong-so; Shi, Qiong; Ho, Anthony K.; Chik, Constance L.; Gaildrat, Pascaline; Morin, Fabrice; Ganguly, Surajit; Rath, Martin F.; Moller, Morten; Sugden, David; Rangel, Zoila G.; Munson, Peter J.; Weller, Joan L.; Coon, Steven L.

    2010-01-01

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

  12. Design of a covalently bonded glycosphingolipid microarray

    DEFF Research Database (Denmark)

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

    2012-01-01

    -mercaptoethylamine, was also tested. Underivatized or linker-derivatized lyso-GSL were then immobilized on N-hydroxysuccinimide- or epoxide-activated glass microarray slides and probed with carbohydrate binding proteins of known or partially known specificities (i.e., cholera toxin B-chain; peanut agglutinin...

  13. A Method of Microarray Data Storage Using Array Data Type

    Science.gov (United States)

    Tsoi, Lam C.; Zheng, W. Jim

    2009-01-01

    A well-designed microarray database can provide valuable information on gene expression levels. However, designing an efficient microarray database with minimum space usage is not an easy task since designers need to integrate the microarray data with the information of genes, probe annotation, and the descriptions of each microarray experiment. Developing better methods to store microarray data can greatly improve the efficiency and usefulness of such data. A new schema is proposed to store microarray data by using array data type in an object-relational database management system – PostgreSQL. The implemented database can store all the microarray data from the same chip in an array data structure. The variable length array data type in PostgreSQL can store microarray data from same chip. The implementation of our schema can help to increase the data retrieval and space efficiency. PMID:17392028

  14. Examining microarray slide quality for the EPA using SNL's hyperspectral microarray scanner.

    Energy Technology Data Exchange (ETDEWEB)

    Rohde, Rachel M.; Timlin, Jerilyn Ann

    2005-11-01

    This report summarizes research performed at Sandia National Laboratories (SNL) in collaboration with the Environmental Protection Agency (EPA) to assess microarray quality on arrays from two platforms of interest to the EPA. Custom microarrays from two novel, commercially produced array platforms were imaged with SNL's unique hyperspectral imaging technology and multivariate data analysis was performed to investigate sources of emission on the arrays. No extraneous sources of emission were evident in any of the array areas scanned. This led to the conclusions that either of these array platforms could produce high quality, reliable microarray data for the EPA toxicology programs. Hyperspectral imaging results are presented and recommendations for microarray analyses using these platforms are detailed within the report.

  15. 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

  16. Design of a covalently bonded glycosphingolipid microarray.

    Science.gov (United States)

    Arigi, Emma; Blixt, Ola; Buschard, Karsten; Clausen, Henrik; Levery, Steven B

    2012-01-01

    Glycosphingolipids (GSLs) are well known ubiquitous constituents of all eukaryotic cell membranes, yet their normal biological functions are not fully understood. As with other glycoconjugates and saccharides, solid phase display on microarrays potentially provides an effective platform for in vitro study of their functional interactions. However, with few exceptions, the most widely used microarray platforms display only the glycan moiety of GSLs, which not only ignores potential modulating effects of the lipid aglycone, but inherently limits the scope of application, excluding, for example, 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 of the fatty acyl moiety of the ceramide aglycone of selected mammalian GSLs with sphingolipid N-deacylase (SCDase). Derivatization of the free amino group of a typical lyso-GSL, lyso-G(M1), with a prototype linker assembled from succinimidyl-[(N-maleimidopropionamido)-diethyleneglycol] ester and 2-mercaptoethylamine, was also tested. Underivatized or linker-derivatized lyso-GSL were then immobilized on N-hydroxysuccinimide- or epoxide-activated glass microarray slides and probed with carbohydrate binding proteins of known or partially known specificities (i.e., cholera toxin B-chain; peanut agglutinin, 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 that incorporate GSLs for serodiagnosis is discussed.

  17. Microarray BASICA: Background Adjustment, Segmentation, Image Compression and Analysis of Microarray Images

    Directory of Open Access Journals (Sweden)

    Jianping Hua

    2004-01-01

    Full Text Available This paper presents microarray BASICA: an integrated image processing tool for background adjustment, segmentation, image compression, and analysis of cDNA microarray images. BASICA uses a fast Mann-Whitney test-based algorithm to segment cDNA microarray images, and performs postprocessing to eliminate the segmentation irregularities. The segmentation results, along with the foreground and background intensities obtained with the background adjustment, are then used for independent compression of the foreground and background. We introduce a new distortion measurement for cDNA microarray image compression and devise a coding scheme by modifying the embedded block coding with optimized truncation (EBCOT algorithm (Taubman, 2000 to achieve optimal rate-distortion performance in lossy coding while still maintaining outstanding lossless compression performance. Experimental results show that the bit rate required to ensure sufficiently accurate gene expression measurement varies and depends on the quality of cDNA microarray images. For homogeneously hybridized cDNA microarray images, BASICA is able to provide from a bit rate as low as 5 bpp the gene expression data that are 99% in agreement with those of the original 32 bpp images.

  18. Post-normalization quality assessment visualization of microarray data

    NARCIS (Netherlands)

    McClure, John; Wit, Ernst

    2003-01-01

    Post-normalization checking of microarrays rarely occurs, despite the problems that using unreliable data for inference can cause. This paper considers a number of different ways to check microarrays after normalization for a variety of potential problems. Four types of problem with microarray data

  19. SIMAGE : simulation of DNA-microarray gene expression data

    NARCIS (Netherlands)

    Albers, Casper J.; Jansen, Ritsert C.; Kok, Jan; Kuipers, Oscar P.; Hijum, Sacha A.F.T. van

    2006-01-01

    Simulation of DNA-microarray data serves at least three purposes: (i) optimizing the design of an intended DNA microarray experiment, (ii) comparing existing pre-processing and processing methods for best analysis of a given DNA microarray experiment, (iii) educating students, lab-workers and other

  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. Immobilization Techniques for Microarray: Challenges and Applications

    Directory of Open Access Journals (Sweden)

    Satish Balasaheb Nimse

    2014-11-01

    Full Text Available The highly programmable positioning of molecules (biomolecules, nanoparticles, nanobeads, nanocomposites materials on surfaces has potential applications in the fields of biosensors, biomolecular electronics, and nanodevices. However, the conventional techniques including self-assembled monolayers fail to position the molecules on the nanometer scale to produce highly organized monolayers on the surface. The present article elaborates different techniques for the immobilization of the biomolecules on the surface to produce microarrays and their diagnostic applications. The advantages and the drawbacks of various methods are compared. This article also sheds light on the applications of the different technologies for the detection and discrimination of viral/bacterial genotypes and the detection of the biomarkers. A brief survey with 115 references covering the last 10 years on the biological applications of microarrays in various fields is also provided.

  2. Protein microarrays: applications and future challenges.

    Science.gov (United States)

    Stoll, Dieter; Templin, Markus F; Bachmann, Jutta; Joos, Thomas O

    2005-03-01

    Within the last decade protein microarray technology has been successfully applied for the simultaneous identification, quantification and functional analysis of proteins in basic and applied proteome research. These miniaturized and parallelized assay systems have the potential to replace state-of-the-art singleplex analysis systems. However, prior to their general application in robust, reliable, routine and high-throughput applications it is mandatory that they demonstrate robustness, sensitivity, automation and appropriate pricing. In this review, the current state of protein microarray technology will be summarized. Recent applications for the simultaneous determination of a variety of parameters using only minute amounts of sample will be described and future challenges of this cutting-edge technology will be discussed.

  3. Plasmonically amplified fluorescence bioassay with microarray format

    Science.gov (United States)

    Gogalic, S.; Hageneder, S.; Ctortecka, C.; Bauch, M.; Khan, I.; Preininger, Claudia; Sauer, U.; Dostalek, J.

    2015-05-01

    Plasmonic amplification of fluorescence signal in bioassays with microarray detection format is reported. A crossed relief diffraction grating was designed to couple an excitation laser beam to surface plasmons at the wavelength overlapping with the absorption and emission bands of fluorophore Dy647 that was used as a label. The surface of periodically corrugated sensor chip was coated with surface plasmon-supporting gold layer and a thin SU8 polymer film carrying epoxy groups. These groups were employed for the covalent immobilization of capture antibodies at arrays of spots. The plasmonic amplification of fluorescence signal on the developed microarray chip was tested by using interleukin 8 sandwich immunoassay. The readout was performed ex situ after drying the chip by using a commercial scanner with high numerical aperture collecting lens. Obtained results reveal the enhancement of fluorescence signal by a factor of 5 when compared to a regular glass chip.

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

    Science.gov (United States)

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

    2016-01-27

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

  5. Microarray for serotyping of Bartonella species

    OpenAIRE

    Raoult Didier; Nappez Claude; Bonhomme Cyrille J

    2007-01-01

    Abstract Background Bacteria of the genus Bartonella are responsible for a large variety of human and animal diseases. Serological typing of Bartonella is a method that can be used for differentiation and identification of Bartonella subspecies. Results We have developed a novel multiple antigenic microarray to serotype Bartonella strains and to select poly and monoclonal antibodies. It was validated using mouse polyclonal antibodies against 29 Bartonella strains. We then tested the microarra...

  6. 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.

  7. Hybridization thermodynamics of NimbleGen Microarrays

    Directory of Open Access Journals (Sweden)

    Posekany Alexandra

    2010-01-01

    Full Text Available Abstract Background While microarrays are the predominant method for gene expression profiling, probe signal variation is still an area of active research. Probe signal is sequence dependent and affected by probe-target binding strength and the competing formation of probe-probe dimers and secondary structures in probes and targets. Results We demonstrate the benefits of an improved model for microarray hybridization and assess the relative contributions of the probe-target binding strength and the different competing structures. Remarkably, specific and unspecific hybridization were apparently driven by different energetic contributions: For unspecific hybridization, the melting temperature Tm was the best predictor of signal variation. For specific hybridization, however, the effective interaction energy that fully considered competing structures was twice as powerful a predictor of probe signal variation. We show that this was largely due to the effects of secondary structures in the probe and target molecules. The predictive power of the strength of these intramolecular structures was already comparable to that of the melting temperature or the free energy of the probe-target duplex. Conclusions This analysis illustrates the importance of considering both the effects of probe-target binding strength and the different competing structures. For specific hybridization, the secondary structures of probe and target molecules turn out to be at least as important as the probe-target binding strength for an understanding of the observed microarray signal intensities. Besides their relevance for the design of new arrays, our results demonstrate the value of improving thermodynamic models for the read-out and interpretation of microarray signals.

  8. Weighted analysis of general microarray experiments

    Directory of Open Access Journals (Sweden)

    Kristiansson Erik

    2007-10-01

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

  9. 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/.

  10. Microarray for serotyping of Bartonella species

    Directory of Open Access Journals (Sweden)

    Raoult Didier

    2007-06-01

    Full Text Available Abstract Background Bacteria of the genus Bartonella are responsible for a large variety of human and animal diseases. Serological typing of Bartonella is a method that can be used for differentiation and identification of Bartonella subspecies. Results We have developed a novel multiple antigenic microarray to serotype Bartonella strains and to select poly and monoclonal antibodies. It was validated using mouse polyclonal antibodies against 29 Bartonella strains. We then tested the microarray for serotyping of Bartonella strains and defining the profile of monoclonal antibodies. Bartonella strains gave a strong positive signal and all were correctly identified. Screening of monoclonal antibodies towards the Gro EL protein of B. clarridgeiae identified 3 groups of antibodies, which were observed with variable affinities against Bartonella strains. Conclusion We demonstrated that microarray of spotted bacteria can be a practical tool for serotyping of unidentified strains or species (and also for affinity determination by polyclonal and monoclonal antibodies. This could be used in research and for identification of bacterial strains.

  11. 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.

  12. 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.

  13. An imputation approach for oligonucleotide microarrays.

    Directory of Open Access Journals (Sweden)

    Ming Li

    Full Text Available Oligonucleotide microarrays are commonly adopted for detecting and qualifying the abundance of molecules in biological samples. Analysis of microarray data starts with recording and interpreting hybridization signals from CEL images. However, many CEL images may be blemished by noises from various sources, observed as "bright spots", "dark clouds", and "shadowy circles", etc. It is crucial that these image defects are correctly identified and properly processed. Existing approaches mainly focus on detecting defect areas and removing affected intensities. In this article, we propose to use a mixed effect model for imputing the affected intensities. The proposed imputation procedure is a single-array-based approach which does not require any biological replicate or between-array normalization. We further examine its performance by using Affymetrix high-density SNP arrays. The results show that this imputation procedure significantly reduces genotyping error rates. We also discuss the necessary adjustments for its potential extension to other oligonucleotide microarrays, such as gene expression profiling. The R source code for the implementation of approach is freely available upon request.

  14. A New Distribution Family for Microarray Data

    Directory of Open Access Journals (Sweden)

    Diana Mabel Kelmansky

    2017-02-01

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

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

    Directory of Open Access Journals (Sweden)

    Ferhatosmanoglu Nilgun

    2009-09-01

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

  16. 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

  17. Normalization for triple-target microarray experiments

    Directory of Open Access Journals (Sweden)

    Magniette Frederic

    2008-04-01

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

  18. 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.

  19. 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.

  20. Human brain evolution: insights from microarrays.

    Science.gov (United States)

    Preuss, Todd M; Cáceres, Mario; Oldham, Michael C; Geschwind, Daniel H

    2004-11-01

    Several recent microarray studies have compared gene-expression patterns n humans, chimpanzees and other non-human primates to identify evolutionary changes that contribute to the distinctive cognitive and behavioural characteristics of humans. These studies support the surprising conclusion that the evolution of the human brain involved an upregulation of gene expression relative to non-human primates, a finding that could be relevant to understanding human cerebral physiology and function. These results show how genetic and genomic methods can shed light on the basis of human neural and cognitive specializations, and have important implications for neuroscience, anthropology and medicine.

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

    OpenAIRE

    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 successfu...

  2. 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.

  3. Identification of candidate genes in osteoporosis by integrated microarray analysis

    OpenAIRE

    Li, J J; Wang, B. Q.; Fei, Q.; Yang, Y; Li, D.

    2017-01-01

    Objectives In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. Methods We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed...

  4. Novel R Pipeline for Analyzing Biolog Phenotypic Microarray Data

    OpenAIRE

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

    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...

  5. 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...... to distinguish those strains on genus, species, and pathotype/serovar levels. Additionally, the microarray performed well when investigating which genes were found in a given strain of interest. The Enterobacteriaceae pan-genome microarray, based on 116 genomes, provides a valuable tool for determination...

  6. 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.

  7. Tissue microarrays: Potential in the Indian subcontinent

    Directory of Open Access Journals (Sweden)

    Venkataraman Girish

    2005-01-01

    Full Text Available Tissue microarrays (TMAs are a means of combining hundreds of specimens of tissue on to a single slide for analysis simultaneously. The evolution of this technology to validate the results of cDNA microarrays has impacted tremendously in accurately identifying prognostic indicators significant in determining survival demographics for patients. TMAs can be generated from archival paraffin blocks, combined with sophisticated image analysis software for reading TMA immunohistochemistry, and a staggering amount of useful information can be generated in terms of the biomarkers useful in predicting patient outcome. There is a wide range of uses for the TMA technology including profiling of specific proteins in cancerous tissues and non-cancerous tissues. Given the wide variety of tissue resources available in India, investment in a dedicated TMA facility will be of immense use in the research arena in India. This review article discusses the basics of TMA construction, design, the software available for the analysis of this technology and its relevance to Indian scientists. A potential workflow structure for setting up a TMA facility is also included.

  8. 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).

  9. The Importance of Normalization on Large and Heterogeneous Microarray Datasets

    Science.gov (United States)

    DNA microarray technology is a powerful functional genomics tool increasingly used for investigating global gene expression in environmental studies. Microarrays can also be used in identifying biological networks, as they give insight on the complex gene-to-gene interactions, ne...

  10. Experimental Approaches to Microarray Analysis of Tumor Samples

    Science.gov (United States)

    Furge, Laura Lowe; Winter, Michael B.; Meyers, Jacob I.; Furge, Kyle A.

    2008-01-01

    Comprehensive measurement of gene expression using high-density nucleic acid arrays (i.e. microarrays) has become an important tool for investigating the molecular differences in clinical and research samples. Consequently, inclusion of discussion in biochemistry, molecular biology, or other appropriate courses of microarray technologies has…

  11. 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

  12. Mathematical design of prokaryotic clone-based microarrays

    NARCIS (Netherlands)

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

    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 ran

  13. 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

  14. Automatic Spot Identification for High Throughput Microarray Analysis

    Science.gov (United States)

    Wu, Eunice; Su, Yan A.; Billings, Eric; Brooks, Bernard R.; Wu, Xiongwu

    2013-01-01

    High throughput microarray analysis has great potential in scientific research, disease diagnosis, and drug discovery. A major hurdle toward high throughput microarray analysis is the time and effort needed to accurately locate gene spots in microarray images. An automatic microarray image processor will allow accurate and efficient determination of spot locations and sizes so that gene expression information can be reliably extracted in a high throughput manner. Current microarray image processing tools require intensive manual operations in addition to the input of grid parameters to correctly and accurately identify gene spots. This work developed a method, herein called auto-spot, to automate the spot identification process. Through a series of correlation and convolution operations, as well as pixel manipulations, this method makes spot identification an automatic and accurate process. Testing with real microarray images has demonstrated that this method is capable of automatically extracting subgrids from microarray images and determining spot locations and sizes within each subgrid, regardless of variations in array patterns and background noises. With this method, we are one step closer to the goal of high throughput microarray analysis. PMID:24298393

  15. Uses of Dendrimers for DNA Microarrays

    Science.gov (United States)

    Caminade, Anne-Marie; Padié, Clément; Laurent, Régis; Maraval, Alexandrine; Majoral, Jean-Pierre

    2006-01-01

    Biosensors such as DNA microarrays and microchips are gaining an increasing importance in medicinal, forensic, and environmental analyses. Such devices are based on the detection of supramolecular interactions called hybridizations that occur between complementary oligonucleotides, one linked to a solid surface (the probe), and the other one to be analyzed (the target). This paper focuses on the improvements that hyperbranched and perfectly defined nanomolecules called dendrimers can provide to this methodology. Two main uses of dendrimers for such purpose have been described up to now; either the dendrimer is used as linker between the solid surface and the probe oligonucleotide, or the dendrimer is used as a multilabeled entity linked to the target oligonucleotide. In the first case 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 small quantities of biological entities.

  16. 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.

  17. Normalization strategy of microarray gene expression data

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Objective: To discuss strategies and methods of normalization on how to deal with and analyze data for different chips with the combination of statistics, mathematics and bioinformatics in order to find significant difference genes. Methods: With Excel and SPSS software, high or low density chips were analyzed through total intensity normalization (TIN) and locally weighted linear regression normalization (LWLRN). Results: These methods effectively reduced systemic errors and made data more comparable and reliable. Conclusion: These methods can search the genes of significant difference, although normalization methods are being developed and need to be improved further. Great breakthrough will be obtained in microarray data normalization analysis and transformation with the development of non-linear technology, software and hardware of computer.

  18. 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.

  19. Protein microarray applications: Autoantibody detection and posttranslational modification.

    Science.gov (United States)

    Atak, Apurva; Mukherjee, Shuvolina; Jain, Rekha; Gupta, Shabarni; Singh, Vedita Anand; Gahoi, Nikita; K P, Manubhai; Srivastava, Sanjeeva

    2016-10-01

    The discovery of DNA microarrays was a major milestone in genomics; however, it could not adequately predict the structure or dynamics of underlying protein entities, which are the ultimate effector molecules in a cell. Protein microarrays allow simultaneous study of thousands of proteins/peptides, and various advancements in array technologies have made this platform suitable for several diagnostic and functional studies. Antibody arrays enable researchers to quantify the abundance of target proteins in biological fluids and assess PTMs by using the antibodies. Protein microarrays have been used to assess protein-protein interactions, protein-ligand interactions, and autoantibody profiling in various disease conditions. Here, we summarize different microarray platforms with focus on its biological and clinical applications in autoantibody profiling and PTM studies. We also enumerate the potential of tissue microarrays to validate findings from protein arrays as well as other approaches, highlighting their significance in proteomics.

  20. 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.

  1. 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.

  2. Lipid Microarray Biosensor for Biotoxin Detection.

    Energy Technology Data Exchange (ETDEWEB)

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

    2006-05-01

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

  3. Polymer microarray technology for stem cell engineering.

    Science.gov (United States)

    Coyle, Robert; Jia, Jia; Mei, Ying

    2016-04-01

    Stem cells hold remarkable promise for applications in tissue engineering and disease modeling. During the past decade, significant progress has been made in developing soluble factors (e.g., small molecules and growth factors) to direct stem cells into a desired phenotype. However, the current lack of suitable synthetic materials to regulate stem cell activity has limited the realization of the enormous potential of stem cells. This can be attributed to a large number of materials properties (e.g., chemical structures and physical properties of materials) that can affect stem cell fate. This makes it challenging to design biomaterials to direct stem cell behavior. To address this, polymer microarray technology has been developed to rapidly identify materials for a variety of stem cell applications. In this article, we summarize recent developments in polymer array technology and their applications in stem cell engineering. Stem cells hold remarkable promise for applications in tissue engineering and disease modeling. In the last decade, significant progress has been made in developing chemically defined media to direct stem cells into a desired phenotype. However, the current lack of the suitable synthetic materials to regulate stem cell activities has been limiting the realization of the potential of stem cells. This can be attributed to the number of variables in material properties (e.g., chemical structures and physical properties) that can affect stem cells. Polymer microarray technology has shown to be a powerful tool to rapidly identify materials for a variety of stem cell applications. Here we summarize recent developments in polymer array technology and their applications in stem cell engineering. Copyright © 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

  4. 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.

  5. 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.

  6. Rapid and quantitative quality control of microarrays using cationic nanoparticles.

    Science.gov (United States)

    Sun, Ye; Fan, Wenhua; McCann, Michael P; Golovlev, Val

    2009-02-15

    The fabrication quality of microarrays significantly influences the accuracy and reproducibility of microarray experiments. In this report, we present a simple and fast quality control (QC) method for spotted oligonucleotide and cDNA microarrays. It employs a nonspecific electrostatic interaction of colloidal gold nanoparticles with the chemical groups of DNA molecules and other biomolecules immobilized on the microarray surface that bear positive or negative charges. An inexpensive flatbed scanner is used to visualize and quantify the binding of cationic gold particles to the anionic DNA probes on the microarray surface. An image analysis software was designed to assess the various parameters of the array spots including spot intensity, shape and array homogeneity, calculate the overall array quality score, and save the detailed array quality report in an Excel file. The gold staining technique is fast and sensitive. It can be completed in 10 min and detect less than 1% of the probe amount commonly recommended for microarrays. Compared to the current microarray QC method that utilizes the hybridization of probes with short random sequence oligonucleotides labeled with fluorophore, our gold staining method requires less time for the analysis, reduces the reagent cost, and eliminates the need for the expensive laser scanner.

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

    Science.gov (United States)

    Biyani, Manish; Ichiki, Takanori

    2015-07-14

    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.

  8. The EADGENE Microarray Data Analysis Workshop (Open Access publication

    Directory of Open Access Journals (Sweden)

    Jiménez-Marín Ángeles

    2007-11-01

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

  9. The application of protein microarray assays in psychoneuroimmunology.

    Science.gov (United States)

    Ayling, K; Bowden, T; Tighe, P; Todd, I; Dilnot, E M; Negm, O H; Fairclough, L; Vedhara, K

    2017-01-01

    Protein microarrays are miniaturized multiplex assays that exhibit many advantages over the commonly used enzyme-linked immunosorbent assay (ELISA). This article aims to introduce protein microarrays to readers of Brain, Behavior, and Immunity and demonstrate its utility and validity for use in psychoneuroimmunological research. As part of an ongoing investigation of psychological and behavioral influences on influenza vaccination responses, we optimized a novel protein microarray to quantify influenza-specific antibody levels in human sera. Reproducibility was assessed by calculating intra- and inter-assay coefficients of variance on serially diluted human IgG concentrations. A random selection of samples was analyzed by microarray and ELISA to establish validity of the assay. For IgG concentrations, intra-assay and inter-assay precision profiles demonstrated a mean coefficient of variance of 6.7% and 11.5% respectively. Significant correlations were observed between microarray and ELISA for all antigens, demonstrating the microarray is a valid alternative to ELISA. Protein microarrays are a highly robust, novel assay method that could be of significant benefit for researchers working in psychoneuroimmunology. They offer high throughput, fewer resources per analyte and can examine concurrent neuro-immune-endocrine mechanisms.

  10. 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

  11. 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

  12. Triple-target microarray experiments: a novel experimental strategy

    Directory of Open Access Journals (Sweden)

    Cooke Howard J

    2004-02-01

    Full Text Available Abstract Background High-throughput, parallel gene expression analysis by means of microarray technology has become a widely used technique in recent years. There are currently two main dye-labelling strategies for microarray studies based on custom-spotted cDNA or oligonucleotides arrays: (I Dye-labelling of a single target sample with a particular dye, followed by subsequent hybridisation to a single microarray slide, (II Dye-labelling of two different target samples with two different dyes, followed by subsequent co-hybridisation to a single microarray slide. The two dyes most frequently used for either method are Cy3 and Cy5. We propose and evaluate a novel experiment set-up utilising three differently labelled targets co-hybridised to one microarray slide. In addition to Cy3 and Cy5, this incorporates Alexa 594 as a third dye-label. We evaluate this approach in line with current data processing and analysis techniques for microarrays, and run separate analyses on Alexa 594 used in single-target, dual-target and the intended triple-target experiment set-ups (a total of 18 microarray slides. We follow this by pointing out practical applications and suitable analysis methods, and conclude that triple-target microarray experiments can add value to microarray research by reducing material costs for arrays and related processes, and by increasing the number of options for pragmatic experiment design. Results The addition of Alexa 594 as a dye-label for an additional – third – target sample works within the framework of more commonplace Cy5/Cy3 labelled target sample combinations. Standard normalisation methods are still applicable, and the resulting data can be expected to allow identification of expression differences in a biological experiment, given sufficient levels of biological replication (as is necessary for most microarray experiments. Conclusion The use of three dye-labelled target samples can be a valuable addition to the standard

  13. Optimality criteria for the design of 2-color microarray studies.

    Science.gov (United States)

    Kerr, Kathleen F

    2012-01-13

    We discuss the definition and application of design criteria for evaluating the efficiency of 2-color microarray designs. First, we point out that design optimality criteria are defined differently for the regression and block design settings. This has caused some confusion in the literature and warrants clarification. Linear models for microarray data analysis have equivalent formulations as ANOVA or regression models. However, this equivalence does not extend to design criteria. We discuss optimality criterion, and argue against applying regression-style D-optimality to the microarray design problem. We further disfavor E- and D-optimality (as defined in block design) because they are not attuned to scientific questions of interest.

  14. 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....

  15. Transcriptome analysis of zebrafish embryogenesis using microarrays.

    Directory of Open Access Journals (Sweden)

    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.

  16. 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.

  17. Tissue microarray profiling in human heart failure.

    Science.gov (United States)

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

    2016-09-01

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

  18. The use of microarray technology for cytogenetics.

    Science.gov (United States)

    Bejjani, Bassem A; Shaffer, Lisa G; Ballif, Blake C

    2010-01-01

    The use of microarray technology is revolutionizing the field of clinical cytogenetics. This new technology has transformed the cytogenetics laboratory by adapting techniques that have heretofore been the province of molecular geneticists. Intimate knowledge and comfortable familiarity with these techniques are now a must for the modern cytogeneticist, rather than a stimulating but discretionary intellectual exercise or an elective luxury. The cytogenetic laboratory of the future will likely have more scanners than microscopes, more software packages than darkrooms, and more technologists, supervisors, and directors with molecular training than ever before. This technical convergence between molecular diagnostics and clinical cytogenetics is exciting and has already resulted in many stimulating discoveries. However, the traditional skills of the cytogeneticist are needed now more than ever before. As our ability to inspect the genome increases, so does the variety of abnormalities that we uncover. Understanding the mechanisms of these aberrations to guide additional testing of the parents and genetic counseling of the patients and their families requires the expertise of individuals who are well-versed in meiotic mechanisms and chromosomal structures that may lead to these abnormalities. Cytogeneticists are uniquely positioned to understand these mechanisms and assist genetic counselors and clinicians in their daily interactions with patients and families.

  19. 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.

  20. Antibody microarrays for native toxin detection.

    Science.gov (United States)

    Rucker, Victor C; Havenstrite, Karen L; Herr, Amy E

    2005-04-15

    We have developed antibody-based microarray techniques for the multiplexed detection of cholera toxin beta-subunit, diphtheria toxin, anthrax lethal factor and protective antigen, Staphylococcus aureus enterotoxin B, and tetanus toxin C fragment in spiked samples. Two detection schemes were investigated: (i) a direct assay in which fluorescently labeled toxins were captured directly by the antibody array and (ii) a competition assay that employed unlabeled toxins as reporters for the quantification of native toxin in solution. In the direct assay, fluorescence measured at each array element is correlated with labeled toxin concentration to yield baseline binding information (Langmuir isotherms and affinity constants). Extending from the direct assay, the competition assay yields information on the presence, identity, and concentration of toxins. A significant advantage of the competition assay over reported profiling assays is the minimal sample preparation required prior to analysis because the competition assay obviates the need to fluorescently label native proteins in the sample of interest. Sigmoidal calibration curves and detection limits were established for both assay formats. Although the sensitivity of the direct assay is superior to that of the competition assay, detection limits for unmodified toxins in the competition assay are comparable to values reported previously for sandwich-format immunoassays of antibodies arrayed on planar substrates. As a demonstration of the potential of the competition assay for unlabeled toxin detection, we conclude with a straightforward multiplexed assay for the differentiation and identification of both native S. aureus enterotoxin B and tetanus toxin C fragment in spiked dilute serum samples.

  1. Cell-Based Microarrays for In Vitro Toxicology.

    Science.gov (United States)

    Wegener, Joachim

    2015-01-01

    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.

  2. 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.

  3. Glycan microarray analysis of Candida glabrata adhesin ligand specificity

    National Research Council Canada - National Science Library

    Zupancic, Margaret L; Frieman, Matthew; Smith, David; Alvarez, Richard A; Cummings, Richard D; Cormack, Brendan P

    2008-01-01

    ...) family responsible for mediating adherence to host cells. To better understand the mechanism by which the Epa proteins contribute to pathogenesis, we have used glycan microarray analysis to characterize their carbohydrate...

  4. 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.

  5. Microarray of DNA probes on carboxylate functional beads surface

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    The microarray of DNA probes with 5′-NH2 and 5′-Tex/3′-NH2 modified terminus on 10 m m carboxylate functional beads surface in the presence of 1-ethyl-3-(3-dimethylaminopropyl)- carbodiimide (EDC) is characterized in the present paper. It was found that the microarray capacity of DNA probes on the beads surface depends on the pH of the aqueous solution, the concentration 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.

  6. 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.

  7. Development of a spot reliability evaluation score for DNA microarrays.

    Science.gov (United States)

    Matsumura, Yonehiro; Shimokawa, Kazuro; Hayashizaki, Yoshihide; Ikeo, Kazuho; Tateno, Yoshio; Kawai, Jun

    2005-05-09

    We developed a reliability index named SRED (Spot Reliability Evaluation Score for DNA microarrays) that represents the probability that the calibrated gene expression level from a DNA microarray would be less than a factor of 2 different from that of quantitative real-time polymerase chain reaction assays whose dynamic quantification range is treated statistically to be similar to that of the DNA microarray. To define the SRED score, two parameters, the reproducibility of measurement value and the relative expression value were selected from nine candidate parameters. The SRED score supplies the probability that the expression level in each spot of a microarray is less than a certain-fold different compared to other expression profiling data, such as QRT-PCR. This score was applied to approximately 1,500,000 points of the expression profile in the RIKEN Expression Array Database.

  8. Rapid Diagnosis of Bacterial Meningitis Using a Microarray

    Directory of Open Access Journals (Sweden)

    Ren-Jy Ben

    2008-06-01

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

  9. Identification of mycotoxigenic fungi using an oligonucleotide microarray

    CSIR Research Space (South Africa)

    Barros, E

    2013-01-01

    Full Text Available , numerous detection tools have been developed for the detection and analysis of various mycotoxigenic fungi. These include PCR-based assays and microarrays targeting different areas of the fungal genome depending on its application. This chapter describes...

  10. Empirical evaluation of oligonucleotide probe selection for DNA microarrays.

    Directory of Open Access Journals (Sweden)

    Jennifer G Mulle

    Full Text Available DNA-based microarrays are increasingly central to biomedical research. Selecting oligonucleotide sequences that will behave consistently across experiments is essential to the design, production and performance of DNA microarrays. Here our aim was to improve on probe design parameters by empirically and systematically evaluating probe performance in a multivariate context. We used experimental data from 19 array CGH hybridizations to assess the probe performance of 385,474 probes tiled in the Duchenne muscular dystrophy (DMD region of the X chromosome. Our results demonstrate that probe melting temperature, single nucleotide polymorphisms (SNPs, and homocytosine motifs all have a strong effect on probe behavior. These findings, when incorporated into future microarray probe selection algorithms, may improve microarray performance for a wide variety of applications.

  11. Empirical evaluation of oligonucleotide probe selection for DNA microarrays.

    Science.gov (United States)

    Mulle, Jennifer G; Patel, Viren C; Warren, Stephen T; Hegde, Madhuri R; Cutler, David J; Zwick, Michael E

    2010-03-29

    DNA-based microarrays are increasingly central to biomedical research. Selecting oligonucleotide sequences that will behave consistently across experiments is essential to the design, production and performance of DNA microarrays. Here our aim was to improve on probe design parameters by empirically and systematically evaluating probe performance in a multivariate context. We used experimental data from 19 array CGH hybridizations to assess the probe performance of 385,474 probes tiled in the Duchenne muscular dystrophy (DMD) region of the X chromosome. Our results demonstrate that probe melting temperature, single nucleotide polymorphisms (SNPs), and homocytosine motifs all have a strong effect on probe behavior. These findings, when incorporated into future microarray probe selection algorithms, may improve microarray performance for a wide variety of applications.

  12. Normalization of one-channel microarrays for identification of organisms

    Directory of Open Access Journals (Sweden)

    Zierer, Astrid

    2007-03-01

    Full Text Available Microarrays are widely used in gene expression analysis, but there are further areas they can be applied to, like e.g. the identification of organisms. To interpret and compare the results of microarray experiments it is necessary to standardize the data. In this context standardization is referred to as normalization. We present data derived from a microarray experiment aiming to identify different subtypes of the hepatitis C virus. Most of the methods developed to normalize microarray data are focused on gene expression analysis. Their use for the identification of organisms is restricted and needs adaption for the special requirements. Based on our data setting, we present several possibilities how to modify the existing methods and deal with the specific conditions.

  13. Gene expression profiling of mouse embryos with microarrays

    OpenAIRE

    Sharov, Alexei A; Piao, Yulan; Minoru S.H. Ko

    2010-01-01

    Global expression profiling by DNA microarrays provides a snapshot of cell and tissue status and becomes an essential tool in biological and medical sciences. Typical questions that can be addressed by microarray analysis in developmental biology include: (1) to find a set of genes expressed in a specific cell type; (2) to identify genes expressed commonly in multiple cell types; (3) to follow the time-course changes of gene expression patterns; (4) to demonstrate cell’s identity by showing s...

  14. Plant-pathogen interactions: what microarray tells about it?

    Science.gov (United States)

    Lodha, T D; Basak, J

    2012-01-01

    Plant defense responses are mediated by elementary regulatory proteins that affect expression of thousands of genes. Over the last decade, microarray technology has played a key role in deciphering the underlying networks of gene regulation in plants that lead to a wide variety of defence responses. Microarray is an important tool to quantify and profile the expression of thousands of genes simultaneously, with two main aims: (1) gene discovery and (2) global expression profiling. Several microarray technologies are currently in use; most include a glass slide platform with spotted cDNA or oligonucleotides. Till date, microarray technology has been used in the identification of regulatory genes, end-point defence genes, to understand the signal transduction processes underlying disease resistance and its intimate links to other physiological pathways. Microarray technology can be used for in-depth, simultaneous profiling of host/pathogen genes as the disease progresses from infection to resistance/susceptibility at different developmental stages of the host, which can be done in different environments, for clearer understanding of the processes involved. A thorough knowledge of plant disease resistance using successful combination of microarray and other high throughput techniques, as well as biochemical, genetic, and cell biological experiments is needed for practical application to secure and stabilize yield of many crop plants. This review starts with a brief introduction to microarray technology, followed by the basics of plant-pathogen interaction, the use of DNA microarrays over the last decade to unravel the mysteries of plant-pathogen interaction, and ends with the future prospects of this technology.

  15. 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...

  16. 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.

  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

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    Andrea Flannery

    2015-12-01

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

  19. DNA Microarray Characterization of Pathogens Associated with Sexually Transmitted Diseases.

    Science.gov (United States)

    Cao, Boyang; Wang, Suwei; Tian, Zhenyang; Hu, Pinliang; Feng, Lu; Wang, Lei

    2015-01-01

    This study established a multiplex PCR-based microarray to detect simultaneously a diverse panel of 17 sexually transmitted diseases (STDs)-associated pathogens including Neisseria gonorrhoeae, Chlamydia trachomatis, Mycoplasma genitalium, Mycoplasma hominis, Ureaplasma, Herpes simplex virus (HSV) types 1 and 2, and Human papillomavirus (HPV) types 6, 11, 16, 18, 31, 33, 35, 39, 54 and 58. The target genes are 16S rRNA gene for N. gonorrhoeae, M. genitalium, M. hominism, and Ureaplasma, the major outer membrane protein gene (ompA) for C. trachomatis, the glycoprotein B gene (gB) for HSV; and the L1 gene for HPV. A total of 34 probes were selected for the microarray including 31 specific probes, one as positive control, one as negative control, and one as positional control probe for printing reference. The microarray is specific as the commensal and pathogenic microbes (and closely related organisms) in the genitourinary tract did not cross-react with the microarray probes. The microarray is 10 times more sensitive than that of the multiplex PCR. Among the 158 suspected HPV specimens examined, the microarray showed that 49 samples contained HPV, 21 samples contained Ureaplasma, 15 contained M. hominis, four contained C. trachomatis, and one contained N. gonorrhoeae. This work reports the development of the first high through-put detection system that identifies common pathogens associated with STDs from clinical samples, and paves the way for establishing a time-saving, accurate and high-throughput diagnostic tool for STDs.

  20. SIMAGE: simulation of DNA-microarray gene expression data

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    Kuipers Oscar P

    2006-04-01

    Full Text Available Abstract Background Simulation of DNA-microarray data serves at least three purposes: (i optimizing the design of an intended DNA microarray experiment, (ii comparing existing pre-processing and processing methods for best analysis of a given DNA microarray experiment, (iii educating students, lab-workers and other researchers by making them aware of the many factors influencing DNA microarray experiments. Results Our model has multiple layers of factors influencing the experiment. The relative influence of such factors can differ significantly between labs, experiments within labs, etc. Therefore, we have added a module to roughly estimate their parameters from a given data set. This guarantees that our simulated data mimics real data as closely as possible. Conclusion We introduce a model for the simulation of dual-dye cDNA-microarray data closely resembling real data and coin the model and its software implementation "SIMAGE" which stands for simulation of microarray gene expression data. The software is freely accessible at: http://bioinformatics.biol.rug.nl/websoftware/simage.

  1. Challenges for MicroRNA Microarray Data Analysisf

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    Bin Wang

    2013-03-01

    Full Text Available Microarray is a high throughput discovery tool that has been broadly used for genomic research. Probe-target hybridization is the central concept of this technology to determine the relative abundance of nucleic acid sequences through fluorescence-based detection. In microarray experiments, variations of expression measurements can be attributed to many different sources that influence the stability and reproducibility of microarray platforms. Normalization is an essential step to reduce non-biological errors and to convert raw image data from multiple arrays (channels to quality data for further analysis. In general, for the traditional microarray analysis, most established normalization methods are based on two assumptions: (1 the total number of target genes is large enough (>10,000; and (2 the expression level of the majority of genes is kept constant. However, microRNA (miRNA arrays are usually spotted in low density, due to the fact that the total number of miRNAs is less than 2,000 and the majority of miRNAs are weakly or not expressed. As a result, normalization methods based on the above two assumptions are not applicable to miRNA profiling studies. In this review, we discuss a few representative microarray platforms on the market for miRNA profiling and compare the traditional methods with a few novel strategies specific for miRNA microarrays.

  2. Optimized light-directed synthesis of aptamer microarrays.

    Science.gov (United States)

    Franssen-van Hal, Nicole L W; van der Putte, Pepijn; Hellmuth, Klaus; Matysiak, Stefan; Kretschy, Nicole; Somoza, Mark M

    2013-06-18

    Aptamer microarrays are a promising high-throughput method for ultrasensitive detection of multiple analytes, but although much is known about the optimal synthesis of oligonucleotide microarrays used in hybridization-based genomics applications, the bioaffinity interactions between aptamers and their targets is qualitatively different and requires significant changes to synthesis parameters. Focusing on streptavidin-binding DNA aptamers, we employed light-directed in situ synthesis of microarrays to analyze the effects of sequence fidelity, linker length, surface probe density, and substrate functionalization on detection sensitivity. Direct comparison with oligonucleotide hybridization experiments indicates that aptamer microarrays are significantly more sensitive to sequence fidelity and substrate functionalization and have different optimal linker length and surface probe density requirements. Whereas microarray hybridization probes generate maximum signal with multiple deletions, aptamer sequences with the same deletion rate result in a 3-fold binding signal reduction compared with the same sequences synthesized for maximized sequence fidelity. The highest hybridization signal was obtained with dT 5mer linkers, and the highest aptamer signal was obtained with dT 11mers, with shorter aptamer linkers significantly reducing the binding signal. The probe hybridization signal was found to be more sensitive to molecular crowding, whereas the aptamer probe signal does not appear to be constrained within the density of functional surface groups commonly used to synthesize microarrays.

  3. A brief introduction to tiling microarrays: principles, concepts, and applications.

    Science.gov (United States)

    Lemetre, Christophe; Zhang, Zhengdong D

    2013-01-01

    Technological achievements have always contributed to the advancement of biomedical research. It has never been more so than in recent times, when the development and application of innovative cutting-edge technologies have transformed biology into a data-rich quantitative science. This stunning revolution in biology primarily ensued from the emergence of microarrays over two decades ago. The completion of whole-genome sequencing projects and the advance in microarray manufacturing technologies enabled the development of tiling microarrays, which gave unprecedented genomic coverage. Since their first description, several types of application of tiling arrays have emerged, each aiming to tackle a different biological problem. Although numerous algorithms have already been developed to analyze microarray data, new method development is still needed not only for better performance but also for integration of available microarray data sets, which without doubt constitute one of the largest collections of biological data ever generated. In this chapter we first introduce the principles behind the emergence and the development of tiling microarrays, and then discuss with some examples how they are used to investigate different biological problems.

  4. 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.

  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. 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.

  7. Microintaglio Printing of In situ Synthesized Proteins Enables Rapid Printing of High-Density Protein Microarrays Directly from DNA Microarrays

    Science.gov (United States)

    Biyani, Manish; Moriyasu, Junpei; Tanaka, Yoko; Sato, Shusuke; Ueno, Shingo; Ichiki, Takanori

    2013-08-01

    A simple and versatile approach to the simultaneous on-chip synthesis and printing of proteins has been studied for high-density protein microarray applications. The method used is based on the principle of intaglio printing using microengraved plates. Unlike conventional approaches that require multistep reactions for synthesizing proteins off the chip followed by printing using a robotic spotter, our approach demonstrates the following: (i) parallel and spotter-free printing of high-density protein microarrays directly from a type of DNA microarray and (ii) microcompartmentalization of cell-free coupled transcription/translation reaction and direct transferring of picoliter protein solution per spot to pattern microarrays of 25-100 µm features.

  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. A fisheye viewer for microarray-based gene expression data

    Directory of Open Access Journals (Sweden)

    Munson Ethan V

    2006-10-01

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

  10. Statistical implications of pooling RNA samples for microarray experiments

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    Landfield Philip W

    2003-06-01

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

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

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    V.G. Biju

    2015-11-01

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

  12. Significance analysis of lexical bias in microarray data

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    Falkow Stanley

    2003-04-01

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

  13. Microarray-based Identification of Novel Biomarkers in Asthma

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    Kenji Izuhara

    2006-01-01

    Full Text Available Bronchial asthma is a complicated and diverse disorder affected by genetic and environmental factors. It is widely accepted that it is a Th2-type inflammation originating in lung and caused by inhalation of ubiquitous allergens. The complicated and diverse pathogenesis of this disease yet to be clarified. Functional genomics is the analysis of whole gene expression profiling under given condition, and microarray technology is now the most powerful tool for functional genomics. Several attempts to clarify the pathogenesis of bronchial asthma have been carried out using microarray technology, providing us some novel biomarkers for diagnosis, therapeutic targets or understanding pathogenic mechanisms of bronchial asthma. In this article, we review the outcomes of these analyses by the microarray approach as applied to this disease by focusing on the identification of novel biomarkers.

  14. 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...... computer skills and can be executed from any Internet-connected computer. The probe selection procedure for a standard microarray design targeting all yeast transcripts can be completed in 1 h....

  15. An effective method for network module extraction from microarray data

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    Mahanta Priyakshi

    2012-08-01

    Full Text Available Abstract Background The development of high-throughput Microarray technologies has provided various opportunities to systematically characterize diverse types of computational biological networks. Co-expression network have become popular in the analysis of microarray data, such as for detecting functional gene modules. Results This paper presents a method to build a co-expression network (CEN and to detect network modules from the built network. We use an effective gene expression similarity measure called NMRS (Normalized mean residue similarity to construct the CEN. We have tested our method on five publicly available benchmark microarray datasets. The network modules extracted by our algorithm have been biologically validated in terms of Q value and p value. Conclusions Our results show that the technique is capable of detecting biologically significant network modules from the co-expression network. Biologist can use this technique to find groups of genes with similar functionality based on their expression information.

  16. Performance comparison of SLFN training algorithms for DNA microarray classification.

    Science.gov (United States)

    Huynh, Hieu Trung; Kim, Jung-Ja; Won, Yonggwan

    2011-01-01

    The classification of biological samples measured by DNA microarrays has been a major topic of interest in the last decade, and several approaches to this topic have been investigated. However, till now, classifying the high-dimensional data of microarrays still presents a challenge to researchers. In this chapter, we focus on evaluating the performance of the training algorithms of the single hidden layer feedforward neural networks (SLFNs) to classify DNA microarrays. The training algorithms consist of backpropagation (BP), extreme learning machine (ELM) and regularized least squares ELM (RLS-ELM), and an effective algorithm called neural-SVD has recently been proposed. We also compare the performance of the neural network approaches with popular classifiers such as support vector machine (SVM), principle component analysis (PCA) and fisher discriminant analysis (FDA).

  17. Statistical approaches for the analysis of DNA methylation microarray data.

    Science.gov (United States)

    Siegmund, Kimberly D

    2011-06-01

    Following the rapid development and adoption in DNA methylation microarray assays, we are now experiencing a growth in the number of statistical tools to analyze the resulting large-scale data sets. As is the case for other microarray applications, biases caused by technical issues are of concern. Some of these issues are old (e.g., two-color dye bias and probe- and array-specific effects), while others are new (e.g., fragment length bias and bisulfite conversion efficiency). Here, I highlight characteristics of DNA methylation that suggest standard statistical tools developed for other data types may not be directly suitable. I then describe the microarray technologies most commonly in use, along with the methods used for preprocessing and obtaining a summary measure. I finish with a section describing downstream analyses of the data, focusing on methods that model percentage DNA methylation as the outcome, and methods for integrating DNA methylation with gene expression or genotype data.

  18. 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.

  19. Biological networks to the analysis of microarray data

    Institute of Scientific and Technical Information of China (English)

    FANG Zhuo; LUO Qingming; ZHANG Guoqing; LI Yixue

    2006-01-01

    Microarray technology, which permits rapid and large-scale screening for patterns of gene expressions, usually generates a large amount of data. How to mine the biological meanings under these data is one of the main challenges in bioinformatics. Compared to the pure mathematical techniques, those methods incorporated with some prior biological knowledge generally bring better interpretations.Recently, a new analysis, in which the knowledge of biological networks such as metabolic network and protein interaction network is introduced, is widely applied to microarray data analysis. The microarray data analysis based on biological networks contains two main research aspects: identification of active components in biological networks and assessment of gene sets significance. In this paper, we briefly review the progress of these two categories of analyses, especially some representative methods.

  20. Surface manipulation of biomolecules for cell microarray applications.

    Science.gov (United States)

    Hook, Andrew L; Thissen, Helmut; Voelcker, Nicolas H

    2006-10-01

    Many biological events, such as cellular communication, antigen recognition, tissue repair and DNA linear transfer, are intimately associated with biomolecule interactions at the solid-liquid interface. To facilitate the study and use of these biological events for biodevice and biomaterial applications, a sound understanding of how biomolecules behave at interfaces and a concomitant ability to manipulate biomolecules spatially and temporally at surfaces is required. This is particularly true for cell microarray applications, where a range of biological processes must be duly controlled to maximize the efficiency and throughput of these devices. Of particular interest are transfected-cell microarrays (TCMs), which significantly widen the scope of microarray genomic analysis by enabling the high-throughput analysis of gene function within living cells. This article reviews this current research focus, discussing fundamental and applied research into the spatial and temporal surface manipulation of DNA, proteins and other biomolecules and the implications of this work for TCMs.

  1. 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.

  2. Karyotype versus microarray testing for genetic abnormalities after stillbirth.

    Science.gov (United States)

    Reddy, Uma M; Page, Grier P; Saade, George R; Silver, Robert M; Thorsten, Vanessa R; Parker, Corette B; Pinar, Halit; Willinger, Marian; Stoll, Barbara J; Heim-Hall, Josefine; Varner, Michael W; Goldenberg, Robert L; Bukowski, Radek; Wapner, Ronald J; Drews-Botsch, Carolyn D; O'Brien, Barbara M; Dudley, Donald J; Levy, Brynn

    2012-12-06

    Genetic abnormalities have been associated with 6 to 13% of stillbirths, but the true prevalence may be higher. Unlike karyotype analysis, microarray analysis does not require live cells, and it detects small deletions and duplications called copy-number variants. The Stillbirth Collaborative Research Network conducted a population-based study of stillbirth in five geographic catchment areas. Standardized postmortem examinations and karyotype analyses were performed. A single-nucleotide polymorphism array was used to detect copy-number variants of at least 500 kb in placental or fetal tissue. Variants that were not identified in any of three databases of apparently unaffected persons were then classified into three groups: probably benign, clinical significance unknown, or pathogenic. We compared the results of karyotype and microarray analyses of samples obtained after delivery. In our analysis of samples from 532 stillbirths, microarray analysis yielded results more often than did karyotype analysis (87.4% vs. 70.5%, P<0.001) and provided better detection of genetic abnormalities (aneuploidy or pathogenic copy-number variants, 8.3% vs. 5.8%; P=0.007). Microarray analysis also identified more genetic abnormalities among 443 antepartum stillbirths (8.8% vs. 6.5%, P=0.02) and 67 stillbirths with congenital anomalies (29.9% vs. 19.4%, P=0.008). As compared with karyotype analysis, microarray analysis provided a relative increase in the diagnosis of genetic abnormalities of 41.9% in all stillbirths, 34.5% in antepartum stillbirths, and 53.8% in stillbirths with anomalies. Microarray analysis is more likely than karyotype analysis to provide a genetic diagnosis, primarily because of its success with nonviable tissue, and is especially valuable in analyses of stillbirths with congenital anomalies or in cases in which karyotype results cannot be obtained. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development.).

  3. The bioinformatics of microarrays to study cancer: Advantages and disadvantages

    Science.gov (United States)

    Rodríguez-Segura, M. A.; Godina-Nava, J. J.; Villa-Treviño, S.

    2012-10-01

    Microarrays are devices designed to analyze simultaneous expression of thousands of genes. However, the process will adds noise into the information at each stage of the study. To analyze these thousands of data is necessary to use bioinformatics tools. The traditional analysis begins by normalizing data, but the obtained results are highly dependent on how it is conducted the study. It is shown the need to develop new strategies to analyze microarray. Liver tissue taken from an animal model in which is chemically induced cancer is used as an example.

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

    OpenAIRE

    2006-01-01

    Abstract Background Microarray has been widely used to measure the relative amounts of every mRNA transcript from the genome in a single scan. Biologists have been accustomed to reading their experimental data directly from tables. However, microarray data are quite large and are stored in a series of files in a machine-readable format, so direct reading of the full data set is not feasible. The challenge is to design a user interface that allows biologists to usefully view large tables of ra...

  5. 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.

  6. Hand-held portable microarray reader for biodetection

    Science.gov (United States)

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

    2013-04-23

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

  7. 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.

  8. 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.

  9. Dimension reduction methods for microarray data: a review

    Directory of Open Access Journals (Sweden)

    Rabia Aziz

    2017-03-01

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

  10. 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 oocyt...

  11. Microtiter plate-based antibody microarrays for bacteria and toxins

    Science.gov (United States)

    Research has focused on the development of rapid biosensor-based, high-throughput, and multiplexed detection of pathogenic bacteria in foods. Specifically, antibody microarrays in 96-well microtiter plates have been generated for the purpose of selective detection of Shiga toxin-producing E. coli (...

  12. Exploiting fluorescence for multiplex immunoassays on protein microarrays

    Science.gov (United States)

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

    2014-09-01

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

  13. Versatile High Throughput Microarray Analysis for Marine Glycobiology

    DEFF Research Database (Denmark)

    Asunción Salmeán, Armando

    to concept proof that is possible to use the Comprehensive Microarray Polymer Profiling (CoMPP) as a tool for other extracellular matrixes such as marine animals and not only for algal or plant cell walls. Thus, we discovered fucoidan and cellulose epitopes in several tissues of various marine animals from...

  14. Application of Microarray technology in research and diagnostics

    DEFF Research Database (Denmark)

    Helweg-Larsen, Rehannah Borup

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

  15. Quantitative analysis of tumor mitochondrial RNA using microarray

    Institute of Scientific and Technical Information of China (English)

    Cheng-Bo Han; Xiao-Yun Mao; Yan Xin; Shao-Cheng Wang; Jia-Ming Ma; Yu-Jie Zhao

    2005-01-01

    AIM: To design a novel method to rapidly detect the quantitative alteration of mtRNA in patients with tumors.METHODS: Oligo 6.22 and Primer Premier 5.0 bio-soft were used to design 15 pairs of primers of mtRNA cDNA probes in light of the functional and structural property of mtDNA, and then RT-PCR amplification was used to produce 15 probes of mtRNA from one normal gastric mucosal tissue. Total RNA extracted from 9 gastric cancers and corresponding normal gastric mucosal tissues was reverse transcribed into cDNA labeled with fluorescein. The spotted mtDNA microarrays were made and hybridized. Finally,the microarrays were scanned with a GeneTACTM laser scanner to get the hybridized results. Northern blot was used to confirm the microarray results.RESULTS: The hybridized spots were distinct with clear and consistent backgrounds. After data was standardized according to the housekeeping genes, the results showed that the expression levels of some mitochondrial genes in gastric carcinoma were different from those in the corresponding non-cancerous regions.CONCLUSION: The mtDNA expression microarray can rapidly, massively and exactly detect the quantity of mtRNA in tissues and cells. In addition, the whole expressive information of mtRNA from a tumor patient on just one slide can be obtained using this method, providing an effective method to investigate the relationship between mtDNA expression and tumorigenesis.

  16. Viral discovery and sequence recovery using DNA microarrays.

    Directory of Open Access Journals (Sweden)

    David Wang

    2003-11-01

    Full Text Available Because of the constant threat posed by emerging infectious diseases and the limitations of existing approaches used to identify new pathogens, there is a great demand for new technological methods for viral discovery. We describe herein a DNA microarray-based platform for novel virus identification and characterization. Central to this approach was a DNA microarray designed to detect a wide range of known viruses as well as novel members of existing viral families; this microarray contained the most highly conserved 70mer sequences from every fully sequenced reference viral genome in GenBank. During an outbreak of severe acute respiratory syndrome (SARS in March 2003, hybridization to this microarray revealed the presence of a previously uncharacterized coronavirus in a viral isolate cultivated from a SARS patient. To further characterize this new virus, approximately 1 kb of the unknown virus genome was cloned by physically recovering viral sequences hybridized to individual array elements. Sequencing of these fragments confirmed that the virus was indeed a new member of the coronavirus family. This combination of array hybridization followed by direct viral sequence recovery should prove to be a general strategy for the rapid identification and characterization of novel viruses and emerging infectious disease.

  17. 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.

  18. Native antigen fractionation protein microarrays for biomarker discovery.

    Science.gov (United States)

    Caiazzo, Robert J; O'Rourke, Dennis J; Barder, Timothy J; Nelson, Bryce P; Liu, Brian C-S

    2011-01-01

    In this protocol, we used the T24 human bladder cancer cell line as a source of native antigens to construct fractionated lysate microarrays. Subsequently, these microarrays were used to compare the autoantibody responses of individuals with interstitial cystitis/painful bladder syndrome (IC/PBS) to those of normal female controls. To accomplish this, T24 cells were lysed under nondenaturing conditions to obtain native antigens. These native antigens were then fractionated in 2D using a PF-2D liquid chromatography; the first dimension separated the proteins by their isoelectric points, and the second separated them according to hydrophobicity. The resulting protein fractions were printed onto nitrocellulose-coated glass slides (PATH slides) to create a set of fractionated lysate microarrays. To compare the autoantibody responses of IC/PBS patients with normal controls, the fractionated lysate arrays were competitively hybridized with fluorescently labeled IgG samples purified from both IC/PBS and control sera. This protocol presents a detailed description of the creation and use of native antigen fractionated lysate microarrays for autoantibody profiling.

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

    NARCIS (Netherlands)

    Staal, Y.; van Herwijnen, M.H.M.; van Schooten, F.J.; van Delft, J.H.M.

    2005-01-01

    BACKGROUND: DNA microarrays are widely used in gene expression analyses. To increase throughput and minimize costs without reducing gene expression data obtained, we investigated whether four mRNA samples can be analyzed simultaneously by applying four different fluorescent dyes. RESULTS: Following

  20. 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...

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

    Science.gov (United States)

    Dehghan Khalilabad, Nastaran; Hassanpour, Hamid

    2017-02-01

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

  2. Robust Likelihood-Based Survival Modeling with Microarray Data

    Directory of Open Access Journals (Sweden)

    HyungJun Cho

    2008-09-01

    Full Text Available Gene expression data can be associated with various clinical outcomes. In particular, these data can be of importance in discovering survival-associated genes for medical applications. As alternatives to traditional statistical methods, sophisticated methods and software programs have been developed to overcome the high-dimensional difficulty of microarray data. Nevertheless, new algorithms and software programs are needed to include practical functions such as the discovery of multiple sets of survival-associated genes and the incorporation of risk factors, and to use in the R environment which many statisticians are familiar with. For survival modeling with microarray data, we have developed a software program (called rbsurv which can be used conveniently and interactively in the R environment. This program selects survival-associated genes based on the partial likelihood of the Cox model and separates training and validation sets of samples for robustness. It can discover multiple sets of genes by iterative forward selection rather than one large set of genes. It can also allow adjustment for risk factors in microarray survival modeling. This software package, the rbsurv package, can be used to discover survival-associated genes with microarray data conveniently.

  3. 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...

  4. 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).

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

    Directory of Open Access Journals (Sweden)

    Lan Shu

    2008-07-01

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

  6. 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.

  7. VIPR: A probabilistic algorithm for analysis of microbial detection microarrays

    Directory of Open Access Journals (Sweden)

    Holbrook Michael R

    2010-07-01

    Full Text Available Abstract Background All infectious disease oriented clinical diagnostic assays in use today focus on detecting the presence of a single, well defined target agent or a set of agents. In recent years, microarray-based diagnostics have been developed that greatly facilitate the highly parallel detection of multiple microbes that may be present in a given clinical specimen. While several algorithms have been described for interpretation of diagnostic microarrays, none of the existing approaches is capable of incorporating training data generated from positive control samples to improve performance. Results To specifically address this issue we have developed a novel interpretive algorithm, VIPR (Viral Identification using a PRobabilistic algorithm, which uses Bayesian inference to capitalize on empirical training data to optimize detection sensitivity. To illustrate this approach, we have focused on the detection of viruses that cause hemorrhagic fever (HF using a custom HF-virus microarray. VIPR was used to analyze 110 empirical microarray hybridizations generated from 33 distinct virus species. An accuracy of 94% was achieved as measured by leave-one-out cross validation. Conclusions VIPR outperformed previously described algorithms for this dataset. The VIPR algorithm has potential to be broadly applicable to clinical diagnostic settings, wherein positive controls are typically readily available for generation of training data.

  8. 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.

  9. Gene expression profiling of mouse embryos with microarrays

    Science.gov (United States)

    Sharov, Alexei A.; Piao, Yulan; Ko, Minoru S. H.

    2011-01-01

    Global expression profiling by DNA microarrays provides a snapshot of cell and tissue status and becomes an essential tool in biological and medical sciences. Typical questions that can be addressed by microarray analysis in developmental biology include: (1) to find a set of genes expressed in a specific cell type; (2) to identify genes expressed commonly in multiple cell types; (3) to follow the time-course changes of gene expression patterns; (4) to demonstrate cell’s identity by showing similarities or differences among two or multiple cell types; (5) to find regulatory pathways and/or networks affected by gene manipulations, such as overexpression or repression of gene expression; (6) to find downstream target genes of transcription factors; (7) to find downstream target genes of cell signaling; (8) to examine the effects of environmental manipulation of cells on gene expression patterns; and (9) to find the effects of genetic manipulation in embryos and adults. Here we describe strategies for executing these experiments and monitoring changes of cell state with gene expression microarrays in application to mouse embryology. Both statistical assessment and interpretation of data are discussed. We also present a protocol for performing microarray analysis on a small amount of embryonic materials. PMID:20699157

  10. 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...

  11. Microarray-based RNA profiling of breast cancer

    DEFF Research Database (Denmark)

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

    2014-01-01

    Microarray is a powerful technique used extensively for gene expression analysis. Different technologies are available, but lack of standardization makes it challenging to compare and integrate data. Furthermore, batch-related biases within datasets are common but often not tackled. We have analy...

  12. 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.

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

    Science.gov (United States)

    von Götz, Franz

    2010-03-01

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

  14. 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.

  15. 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

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

    Directory of Open Access Journals (Sweden)

    Vanderburg Charles R

    2009-01-01

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

  17. 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

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

    Science.gov (United States)

    Wang, Junbai

    2008-01-01

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

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. Sex determination of bovine preimplantation embryos by oligonucleotide microarray.

    Science.gov (United States)

    Yang, Hua; Zhong, Fagang; Yang, Yonglin; Wang, Xinhua; Liu, Shouren; Zhu, Bin

    2013-06-01

    The aim has been to set up a rapid and accurate microarray assay using sandwich mode for sex determination of bovine preimplantation embryos. Twelve sequence-specific oligonucleotide capture probes used to discriminate 12 samples were spotted onto the aldehyde-modified glass slides by Arrayer. The 2 recognition probes used to identify coding regions of the sex-determining region of the Y chromosome gene (SRY) and β-casein (CSN2) reference gene were coupled with biotin. The assay was optimized by using genomic DNA extracted from blood samples of known sex individuals. Polymerase chain reaction (PCR) was used to amplify the fragments in the HMG box region of SRY gene and CSN2 gene with sequence-specific primers. The sex of samples was identified by detecting both the SRY and CSN2 genes simultaneously in 2 reaction cells of microarrays, with the male having SRY and CSN2 signals and the female only CSN2. The sex of 20 bovine preimplantation embryos was determined by oligonucleotide microarray. The protocol was run with a blind test that showed a 100% (82/82) specificity and accuracy in sexing of leukocytes. The bovine embryos were transferred into 20 bovine recipients, with a pregnant rate of 40% (8/20). Three calves were born at term, and 5 fetuses were miscarried. Their sexes were fully in accordance with the embryonic sex predetermination predicted by oligonucleotide microarray. This suggests that the oligonucleotide microarray method of SRY gene analysis can be used in early sex prediction of bovine embryos in breeding programs.

  4. Microarray data integration for genome-wide analysis of human tissue-selective gene expression

    OpenAIRE

    Wang, Liangjiang; Srivastava, Anand K; Schwartz, Charles E

    2010-01-01

    Background Microarray gene expression data are accumulating in public databases. The expression profiles contain valuable information for understanding human gene expression patterns. However, the effective use of public microarray data requires integrating the expression profiles from heterogeneous sources. Results In this study, we have compiled a compendium of microarray expression profiles of various human tissue samples. The microarray raw data generated in different research laboratorie...

  5. In Situ-Synthesized Novel Microarray Optimized for Mouse Stem Cell and Early Developmental Expression Profiling

    OpenAIRE

    Carter, Mark G.; Hamatani, Toshio; Sharov, Alexei A; Carmack, Condie E; Qian, Yong; Aiba, Kazuhiro; Ko, Naomi T.; Dudekula, Dawood B.; Brzoska, Pius M.; Hwang, S. Stuart; Minoru S.H. Ko

    2003-01-01

    Applications of microarray technologies to mouse embryology/genetics have been limited, due to the nonavailability of microarrays containing large numbers of embryonic genes and the gap between microgram quantities of RNA required by typical microarray methods and the miniscule amounts of tissue available to researchers. To overcome these problems, we have developed a microarray platform containing in situ-synthesized 60-mer oligonucleotide probes representing approximately 22,000 unique mous...

  6. 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.

  7. 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.

  8. 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.

  9. Key aspects of analyzing microarray gene-expression data.

    Science.gov (United States)

    Chen, James J

    2007-05-01

    One major challenge with the use of microarray technology is the analysis of massive amounts of gene-expression data for various applications. This review addresses the key aspects of the microarray gene-expression data analysis for the two most common objectives: class comparison and class prediction. Class comparison mainly aims to select which genes are differentially expressed across experimental conditions. Gene selection is separated into two steps: gene ranking and assigning a significance level. Class prediction uses expression profiling analysis to develop a prediction model for patient selection, diagnostic prediction or prognostic classification. Development of a prediction model involves two components: model building and performance assessment. It also describes two additional data analysis methods: gene-class testing and multiple ordering criteria.

  10. 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.

  11. Quantification of global transcription patterns in prokaryotes using spotted microarrays

    OpenAIRE

    Sidders, B.; Withers, M; Kendall, SL; J. Bacon; Waddell, SJ; Hinds, J; Golby, P.; Movahedzadeh, F; Cox, RA; Frita, R.; Ten Bokum, AM; Wernisch, L; Stoker, NG

    2007-01-01

    \\ud \\ud We describe an analysis, applicable to any spotted microarray dataset produced using genomic DNA as a reference, that quantifies prokaryotic levels of mRNA on a genome-wide scale. Applying this to Mycobacterium tuberculosis, we validate the technique, show a correlation between level of expression and biological importance, define the complement of invariant genes and analyze absolute levels of expression by functional class to develop ways of understanding an organism's biology witho...

  12. Universal ligation-detection-reaction microarray applied for compost microbes

    Directory of Open Access Journals (Sweden)

    Romantschuk Martin

    2008-12-01

    Full Text Available Abstract Background Composting is one of the methods utilised in recycling organic communal waste. The composting process is dependent on aerobic microbial activity and proceeds through a succession of different phases each dominated by certain microorganisms. In this study, a ligation-detection-reaction (LDR based microarray method was adapted for species-level detection of compost microbes characteristic of each stage of the composting process. LDR utilises the specificity of the ligase enzyme to covalently join two adjacently hybridised probes. A zip-oligo is attached to the 3'-end of one probe and fluorescent label to the 5'-end of the other probe. Upon ligation, the probes are combined in the same molecule and can be detected in a specific location on a universal microarray with complementary zip-oligos enabling equivalent hybridisation conditions for all probes. The method was applied to samples from Nordic composting facilities after testing and optimisation with fungal pure cultures and environmental clones. Results Probes targeted for fungi were able to detect 0.1 fmol of target ribosomal PCR product in an artificial reaction mixture containing 100 ng competing fungal ribosomal internal transcribed spacer (ITS area or herring sperm DNA. The detection level was therefore approximately 0.04% of total DNA. Clone libraries were constructed from eight compost samples. The LDR microarray results were in concordance with the clone library sequencing results. In addition a control probe was used to monitor the per-spot hybridisation efficiency on the array. Conclusion This study demonstrates that the LDR microarray method is capable of sensitive and accurate species-level detection from a complex microbial community. The method can detect key species from compost samples, making it a basis for a tool for compost process monitoring in industrial facilities.

  13. Fast Gene Ontology based clustering for microarray experiments

    OpenAIRE

    Ovaska Kristian; Laakso Marko; Hautaniemi Sampsa

    2008-01-01

    Abstract Background Analysis of a microarray experiment often results in a list of hundreds of disease-associated genes. In order to suggest common biological processes and functions for these genes, Gene Ontology annotations with statistical testing are widely used. However, these analyses can produce a very large number of significantly altered biological processes. Thus, it is often challenging to interpret GO results and identify novel testable biological hypotheses. Results We present fa...

  14. Gel-forming reagents and uses thereof for preparing microarrays

    Science.gov (United States)

    Golova, Julia; Chernov, Boris; Perov, Alexander

    2010-11-09

    New gel-forming reagents including monomers and cross-linkers, which can be applied to gel-drop microarray manufacturing by using co-polymerization approaches are disclosed. Compositions for the preparation of co-polymerization mixtures with new gel-forming monomers and cross-linker reagents are described herein. New co-polymerization compositions and cross-linkers with variable length linker groups between unsaturated C.dbd.C bonds that participate in the formation of gel networks are disclosed.

  15. 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.

  16. Basic Concepts of Microarrays and Potential Applications in Clinical Microbiology

    OpenAIRE

    Miller, Melissa B.; Tang, Yi-Wei

    2009-01-01

    Summary: The introduction of in vitro nucleic acid amplification techniques, led by real-time PCR, into the clinical microbiology laboratory has transformed the laboratory detection of viruses and select bacterial pathogens. However, the progression of the molecular diagnostic revolution currently relies on the ability to efficiently and accurately offer multiplex detection and characterization for a variety of infectious disease pathogens. Microarray analysis has the capability to offer robu...

  17. 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...

  18. A portable interferometric micro-array reader on image sensor

    OpenAIRE

    Villar Zafra, Aitor

    2014-01-01

    [ANGLÈS] Microarrays constitute a valuable analytical tool for multiplex and high-throughput analysis and are widely used in genomics and proteomics with many potential applications. During the last decades, protein chips have found increasing acceptance for diagnostic applications due to several advantages over conventional bioanalysis such as miniaturization, parallelization, real-time and sensitivity. Even though the majority of DNA-sensor systems relies on labeling of DNA, the recent prog...

  19. 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

  20. Gene set analyses for interpreting microarray experiments on prokaryotic organisms

    OpenAIRE

    Heffron Fred; Van Bruggen Dirk; DeJongh Matthew; Best Aaron A; Tintle Nathan L; Porwollik Steffen; Taylor Ronald C

    2008-01-01

    Abstract Background Despite the widespread usage of DNA microarrays, questions remain about how best to interpret the wealth of gene-by-gene transcriptional levels that they measure. Recently, methods have been proposed which use biologically defined sets of genes in interpretation, instead of examining results gene-by-gene. Despite a serious limitation, a method based on Fisher's exact test remains one of the few plausible options for gene set analysis when an experiment has few replicates, ...

  1. Microarray expression analysis of epithelial ovarian cancer with distinct differentiation

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    To identify gene expression profiling in epithelial ovarian cancer and to explore its correlation with histopathology characterization and prognosis. Gene expression profiles were generated from 10 human ovarian frozen tissue specimens using Agilent Human 1A microarrays. Strikingly, clear differences of gene expression patterns were observed in ovarian cancer as compared to normal tissues. Unique gene profiles were observed in moderately and poorly differentiated epithelial ovarian cancer. It is concluded that different histopathology characterization likely exists extensive molecular heterogeneity.

  2. 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.

  3. New 3-D microarray platform based on macroporous polymer monoliths.

    Science.gov (United States)

    Rober, M; Walter, J; Vlakh, E; Stahl, F; Kasper, C; Tennikova, T

    2009-06-30

    Polymer macroporous monoliths are widely used as efficient sorbents in different, mostly dynamic, interphase processes. In this paper, monolithic materials strongly bound to the inert glass surface are suggested as operative matrices at the development of three-dimensional (3-D) microarrays. For this purpose, several rigid macroporous copolymers differed by reactivity and hydrophobic-hydrophilic properties were synthesized and tested: (1) glycidyl methacrylate-co-ethylene dimethacrylate (poly(GMA-co-EDMA)), (2) glycidyl methacrylate-co-glycerol dimethacrylate (poly(GMA-co-GDMA)), (3) N-hydroxyphthalimide ester of acrylic acid-co-glycidyl methacrylate-co-ethylene dimethacrylate (poly(HPIEAA-co-GMA-co-EDMA)), (4) 2-cyanoethyl methacrylate-co-ethylene dimethacrylate (poly(CEMA-co-EDMA)), and (5) 2-cyanoethyl methacrylate-co-2-hydroxyethyl methacrylate-co-ethylene dimethacrylate (poly(CEMA-co-HEMA-co-EDMA)). The constructed devices were used as platforms for protein microarrays construction and model mouse IgG-goat anti-mouse IgG affinity pair was used to demonstrate the potential of developed test-systems, as well as to optimize microanalytical conditions. The offered microarray platforms were applied to detect the bone tissue marker osteopontin directly in cell culture medium.

  4. 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.

  5. ArrayPipe: a flexible processing pipeline for microarray data

    Science.gov (United States)

    Hokamp, Karsten; Roche, Fiona M.; Acab, Michael; Rousseau, Marc-Etienne; Kuo, Byron; Goode, David; Aeschliman, Dana; Bryan, Jenny; Babiuk, Lorne A.; Hancock, Robert E. W.; Brinkman, Fiona S. L.

    2004-01-01

    A number of microarray analysis software packages exist already; however, none combines the user-friendly features of a web-based interface with potential ability to analyse multiple arrays at once using flexible analysis steps. The ArrayPipe web server (freely available at www.pathogenomics.ca/arraypipe) allows the automated application of complex analyses to microarray data which can range from single slides to large data sets including replicates and dye-swaps. It handles output from most commonly used quantification software packages for dual-labelled arrays. Application features range from quality assessment of slides through various data visualizations to multi-step analyses including normalization, detection of differentially expressed genes, andcomparison and highlighting of gene lists. A highly customizable action set-up facilitates unrestricted arrangement of functions, which can be stored as action profiles. A unique combination of web-based and command-line functionality enables comfortable configuration of processes that can be repeatedly applied to large data sets in high throughput. The output consists of reports formatted as standard web pages and tab-delimited lists of calculated values that can be inserted into other analysis programs. Additional features, such as web-based spreadsheet functionality, auto-parallelization and password protection make this a powerful tool in microarray research for individuals and large groups alike. PMID:15215429

  6. 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.

  7. 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.

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

    Science.gov (United States)

    Agbavwe, Christy; Somoza, Mark M

    2011-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Christy Agbavwe

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

  10. A New Distribution Family for Microarray Data †

    Science.gov (United States)

    Kelmansky, Diana Mabel; Ricci, Lila

    2017-01-01

    The traditional approach with microarray data has been to apply transformations that approximately normalize them, with the drawback of losing the original scale. The alternative standpoint taken here is to search for models that fit the data, characterized by the presence of negative values, preserving their scale; one advantage of this strategy is that it facilitates a direct interpretation of the results. A new family of distributions named gpower-normal indexed by p∈R is introduced and it is proven that these variables become normal or truncated normal when a suitable gpower transformation is applied. Expressions are given for moments and quantiles, in terms of the truncated normal density. This new family can be used to model asymmetric data that include non-positive values, as required for microarray analysis. Moreover, it has been proven that the gpower-normal family is a special case of pseudo-dispersion models, inheriting all the good properties of these models, such as asymptotic normality for small variances. A combined maximum likelihood method is proposed to estimate the model parameters, and it is applied to microarray and contamination data. R codes are available from the authors upon request. PMID:28208652

  11. 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.

  12. MAGMA: analysis of two-channel microarrays made easy.

    Science.gov (United States)

    Rehrauer, Hubert; Zoller, Stefan; Schlapbach, Ralph

    2007-07-01

    The web application MAGMA provides a simple and intuitive interface to identify differentially expressed genes from two-channel microarray data. While the underlying algorithms are not superior to those of similar web applications, MAGMA is particularly user friendly and can be used without prior training. The user interface guides the novice user through the most typical microarray analysis workflow consisting of data upload, annotation, normalization and statistical analysis. It automatically generates R-scripts that document MAGMA's entire data processing steps, thereby allowing the user to regenerate all results in his local R installation. The implementation of MAGMA follows the model-view-controller design pattern that strictly separates the R-based statistical data processing, the web-representation and the application logic. This modular design makes the application flexible and easily extendible by experts in one of the fields: statistical microarray analysis, web design or software development. State-of-the-art Java Server Faces technology was used to generate the web interface and to perform user input processing. MAGMA's object-oriented modular framework makes it easily extendible and applicable to other fields and demonstrates that modern Java technology is also suitable for rather small and concise academic projects. MAGMA is freely available at www.magma-fgcz.uzh.ch.

  13. 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.

  14. Chemical microarray: a new tool for drug screening and discovery.

    Science.gov (United States)

    Ma, Haiching; Horiuchi, Kurumi Y

    2006-07-01

    HTS with microtiter plates has been the major tool used in the pharmaceutical industry to explore chemical diversity space and to identify active compounds and pharmacophores for specific biological targets. However, HTS faces a daunting challenge regarding the fast-growing numbers of drug targets arising from genomic and proteomic research, and large chemical libraries generated from high-throughput synthesis. There is an urgent need to find new ways to profile the activity of large numbers of chemicals against hundreds of biological targets in a fast, low-cost fashion. Chemical microarray can rise to this challenge because it has the capability of identifying and evaluating small molecules as potential therapeutic reagents. During the past few years, chemical microarray technology, with different surface chemistries and activation strategies, has generated many successes in the evaluation of chemical-protein interactions, enzyme activity inhibition, target identification, signal pathway elucidation and cell-based functional analysis. The success of chemical microarray technology will provide unprecedented possibilities and capabilities for parallel functional analysis of tremendous amounts of chemical compounds.

  15. 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.

  16. 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.

  17. Coupled two-way clustering analysis of gene microarray data

    Science.gov (United States)

    Getz, Gad; Levine, Erel; Domany, Eytan

    2000-10-01

    We present a 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, that 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.

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

    Directory of Open Access Journals (Sweden)

    Dubitzky Werner

    2006-02-01

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

  19. Identification of candidate genes in osteoporosis by integrated microarray analysis

    Science.gov (United States)

    Li, J. J.; Wang, B. Q.; Yang, Y.; Li, D.

    2016-01-01

    Objectives In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. Methods We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed genes (DEGs) between patients with osteoporosis and normal controls. Gene function analysis was performed to uncover the functions of identified DEGs. Results A total of three microarray studies were selected for integrated analysis. In all, 1125 genes were found to be significantly differentially expressed between osteoporosis patients and normal controls, with 373 upregulated and 752 downregulated genes. Positive regulation of the cellular amino metabolic process (gene ontology (GO): 0033240, false discovery rate (FDR) = 1.00E + 00) was significantly enriched under the GO category for biological processes, while for molecular functions, flavin adenine dinucleotide binding (GO: 0050660, FDR = 3.66E-01) and androgen receptor binding (GO: 0050681, FDR = 6.35E-01) were significantly enriched. DEGs were enriched in many osteoporosis-related signalling pathways, including those of mitogen-activated protein kinase (MAPK) and calcium. Protein-protein interaction (PPI) network analysis showed that the significant hub proteins contained ubiquitin specific peptidase 9, X-linked (Degree = 99), ubiquitin specific peptidase 19 (Degree = 57) and ubiquitin conjugating enzyme E2 B (Degree = 57). Conclusion Analysis of gene function of identified differentially expressed genes may expand our understanding of fundamental mechanisms leading to osteoporosis. Moreover, significantly enriched pathways, such as MAPK and calcium, may involve in osteoporosis through osteoblastic differentiation and

  20. High throughput genetic analysis of congenital myasthenic syndromes using resequencing microarrays.

    Directory of Open Access Journals (Sweden)

    Lisa Denning

    Full Text Available BACKGROUND: The use of resequencing microarrays for screening multiple, candidate disease loci is a promising alternative to conventional capillary sequencing. We describe the performance of a custom resequencing microarray for mutational analysis of Congenital Myasthenic Syndromes (CMSs, a group of disorders in which the normal process of neuromuscular transmission is impaired. METHODOLOGY/PRINCIPAL FINDINGS: Our microarray was designed to assay the exons and flanking intronic regions of 8 genes linked to CMSs. A total of 31 microarrays were hybridized with genomic DNA from either individuals with known CMS mutations or from healthy controls. We estimated an overall microarray call rate of 93.61%, and we found the percentage agreement between the microarray and capillary sequencing techniques to be 99.95%. In addition, our microarray exhibited 100% specificity and 99.99% reproducibility. Finally, the microarray detected 22 out of the 23 known missense mutations, but it failed to detect all 7 known insertion and deletion (indels mutations, indicating an overall sensitivity of 73.33% and a sensitivity with respect to missense mutations of 95.65%. CONCLUSIONS/SIGNIFICANCE: Overall, our microarray prototype exhibited strong performance and proved highly efficient for screening genes associated with CMSs. Until indels can be efficiently assayed with this technology, however, we recommend using resequencing microarrays for screening CMS mutations after common indels have been first assayed by capillary sequencing.

  1. Signal stability of Cy3 and Cy5 on antibody microarrays

    Directory of Open Access Journals (Sweden)

    Kim Caroline

    2006-10-01

    Full Text Available Abstract Background The antibody microarray technique is a newly emerging proteomics tool for differential protein expression analyses that uses fluorescent dyes Cy 3 and Cy 5. Environmental factors, such as light exposure, can affect the signal intensity of fluorescent dyes on microarray slides thus, it is logical to scan microarray slides immediately after the final wash and drying processes. However, no research data are available concerning time-dependent changes of fluorescent signals on antibody microarray slides to this date. In the present study, microarray slides were preserved at -20°C after regular microarray experiments and were rescanned at day 10, 20 and 30 to evaluate change in signal intensity. Results Fluorescent intensities of microarray spots were detected using a confocal laser scanner after the experiment at day 0, and re-examined at day 10, 20 and 30, respectively. Fluorescent intensities of rescanned microarray spots did not show significant changes when compared with those scanned immediately after standard microarray experiments. Conclusion Microarray slides can be preserved and rescanned multiple times using a confocal laser scanner over a period of days or weeks.

  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. Microarray expression profiling in adhesion and normal peritoneal tissues.

    Science.gov (United States)

    Ambler, Dana R; Golden, Alicia M; Gell, Jennifer S; Saed, Ghassan M; Carey, David J; Diamond, Michael P

    2012-05-01

    To identify molecular markers associated with adhesion and normal peritoneal tissue using microarray expression profiling. Comparative study. University hospital. Five premenopausal women. Adhesion and normal peritoneal tissue samples were obtained from premenopausal women. Ribonucleic acid was extracted using standard protocols and processed for hybridization to Affymetrix Whole Transcript Human Gene Expression Chips. Microarray data were obtained from five different patients, each with adhesion tissue and normal peritoneal samples. Real-time polymerase chain reaction was performed for confirmation using standard protocols. Gene expression in postoperative adhesion and normal peritoneal tissues. A total of 1,263 genes were differentially expressed between adhesion and normal tissues. One hundred seventy-three genes were found to be up-regulated and 56 genes were down-regulated in the adhesion tissues compared with normal peritoneal tissues. The genes were sorted into functional categories according to Gene Ontology annotations. Twenty-six up-regulated genes and 11 down-regulated genes were identified with functions potentially relevant to the pathophysiology of postoperative adhesions. We evaluated and confirmed expression of 12 of these specific genes via polymerase chain reaction. The pathogenesis, natural history, and optimal treatment of postoperative adhesive disease remains unanswered. Microarray analysis of adhesions identified specific genes with increased and decreased expression when compared with normal peritoneum. Knowledge of these genes and ontologic pathways with altered expression provide targets for new therapies to treat patients who have or are at risk for postoperative adhesions. Copyright © 2012 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

  4. Microarrays: molecular allergology and nanotechnology for personalised medicine (I).

    Science.gov (United States)

    Lucas, J M

    2010-01-01

    The diagnosis of antibody-mediated allergic disorders is based on the clinical findings and the detection of allergen-specific IgE based on in vitro and in vivo techniques, together with allergen provocation tests. In vitro diagnostic techniques have progressed enormously following the introduction of the advances made in proteomics and nanotechnology--offering tools for the diagnosis and investigation of allergy at molecular level. The most advanced developments are the microarray techniques, which in genomics allowed rapid description of the human genetic code, and which now have been applied to proteomics, broadening the field for research and clinical use. Together with these technological advances, the characterisation of most of the different proteins generating specific IgE and which conform each natural allergen, as well as their purification or genetic engineering-based synthesis, have been crucial elements--offering the possibility of identifying disease-causing allergens at molecular level, establishing a component-resolved diagnosis (CRD), using them to study the natural course of the disease, and applying them to improvements in specific immunotherapy. Microarrays of allergic components offer results relating to hundreds of these allergenic components in a single test, and use a small amount of serum that can be obtained from capillary blood. The availability of new molecules will allow the development of panels including new allergenic components and sources, which will require evaluation for clinical use. The present study reviews these new developments, component-resolved diagnosis, and the development of microarray techniques as a critical element for furthering our knowledge of allergic disease.

  5. 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

  6. Visualization methods for statistical analysis of microarray clusters

    Directory of Open Access Journals (Sweden)

    Li Kai

    2005-05-01

    Full Text Available Abstract Background The most common method of identifying groups of functionally related genes in microarray data is to apply a clustering algorithm. However, it is impossible to determine which clustering algorithm is most appropriate to apply, and it is difficult to verify the results of any algorithm due to the lack of a gold-standard. Appropriate data visualization tools can aid this analysis process, but existing visualization methods do not specifically address this issue. Results We present several visualization techniques that incorporate meaningful statistics that are noise-robust for the purpose of analyzing the results of clustering algorithms on microarray data. This includes a rank-based visualization method that is more robust to noise, a difference display method to aid assessments of cluster quality and detection of outliers, and a projection of high dimensional data into a three dimensional space in order to examine relationships between clusters. Our methods are interactive and are dynamically linked together for comprehensive analysis. Further, our approach applies to both protein and gene expression microarrays, and our architecture is scalable for use on both desktop/laptop screens and large-scale display devices. This methodology is implemented in GeneVAnD (Genomic Visual ANalysis of Datasets and is available at http://function.princeton.edu/GeneVAnD. Conclusion Incorporating relevant statistical information into data visualizations is key for analysis of large biological datasets, particularly because of high levels of noise and the lack of a gold-standard for comparisons. We developed several new visualization techniques and demonstrated their effectiveness for evaluating cluster quality and relationships between clusters.

  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. Development of a genotyping microarray for Usher syndrome

    Science.gov (United States)

    Cremers, Frans P M; Kimberling, William J; Külm, Maigi; de Brouwer, Arjan P; van Wijk, Erwin; te Brinke, Heleen; Cremers, Cor W R J; Hoefsloot, Lies H; Banfi, Sandro; Simonelli, Francesca; Fleischhauer, Johannes C; Berger, Wolfgang; Kelley, Phil M; Haralambous, Elene; Bitner‐Glindzicz, Maria; Webster, Andrew R; Saihan, Zubin; De Baere, Elfride; Leroy, Bart P; Silvestri, Giuliana; McKay, Gareth J; Koenekoop, Robert K; Millan, Jose M; Rosenberg, Thomas; Joensuu, Tarja; Sankila, Eeva‐Marja; Weil, Dominique; Weston, Mike D; Wissinger, Bernd; Kremer, Hannie

    2007-01-01

    Background Usher syndrome, a combination of retinitis pigmentosa (RP) and sensorineural hearing loss with or without vestibular dysfunction, displays a high degree of clinical and genetic heterogeneity. Three clinical subtypes can be distinguished, based on the age of onset and severity of the hearing impairment, and the presence or absence of vestibular abnormalities. Thus far, eight genes have been implicated in the syndrome, together comprising 347 protein‐coding exons. Methods: To improve DNA diagnostics for patients with Usher syndrome, we developed a genotyping microarray based on the arrayed primer extension (APEX) method. Allele‐specific oligonucleotides corresponding to all 298 Usher syndrome‐associated sequence variants known to date, 76 of which are novel, were arrayed. Results Approximately half of these variants were validated using original patient DNAs, which yielded an accuracy of >98%. The efficiency of the Usher genotyping microarray was tested using DNAs from 370 unrelated European and American patients with Usher syndrome. Sequence variants were identified in 64/140 (46%) patients with Usher syndrome type I, 45/189 (24%) patients with Usher syndrome type II, 6/21 (29%) patients with Usher syndrome type III and 6/20 (30%) patients with atypical Usher syndrome. The chip also identified two novel sequence variants, c.400C>T (p.R134X) in PCDH15 and c.1606T>C (p.C536S) in USH2A. Conclusion The Usher genotyping microarray is a versatile and affordable screening tool for Usher syndrome. Its efficiency will improve with the addition of novel sequence variants with minimal extra costs, making it a very useful first‐pass screening tool. PMID:16963483

  9. Mathematical design of prokaryotic clone-based microarrays

    Directory of Open Access Journals (Sweden)

    Quirijns Elisabeth J

    2005-09-01

    Full Text Available Abstract 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 random process, it is beforehand uncertain which genes are represented. Nevertheless, the genome coverage of such an array, which depends on different variables like the insert size and the number of clones in the library, can be predicted by mathematical approaches. When applying the classical formulas that determine the probability that a certain sequence is represented in a DNA library at the nucleotide level, massive amounts of clones would be necessary to obtain a proper coverage of the genome. Results This paper describes the development of two complementary equations for determining the genome coverage at the gene level. The first equation predicts the fraction of genes that is represented on the array in a detectable way and cover at least a set part (the minimal insert coverage of the genomic fragment by which these genes are represented. The higher this minimal insert coverage, the larger the chance that changes in expression of a specific gene can be detected and attributed to that gene. The second equation predicts the fraction of genes that is represented in spots on the array that only represent genes from a single transcription unit, which information can be interpreted in a quantitative way. Conclusion Validation of these equations shows that they form reliable tools supporting optimal design of prokaryotic clone-based microarrays.

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

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    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.

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

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    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.

  12. Optimization of Cyanine Dye Stability and Analysis of FRET Interaction on DNA Microarrays.

    Science.gov (United States)

    von der Haar, Marcel; Heuer, Christopher; Pähler, Martin; von der Haar, Kathrin; Lindner, Patrick; Scheper, Thomas; Stahl, Frank

    2016-11-30

    The application of DNA microarrays for high throughput analysis of genetic regulation is often limited by the fluorophores used as markers. The implementation of multi-scan techniques is limited by the fluorophores' susceptibility to photobleaching when exposed to the scanner laser light. This paper presents combined mechanical and chemical strategies which enhance the photostability of cyanine 3 and cyanine 5 as part of solid state DNA microarrays. These strategies are based on scanning the microarrays while the hybridized DNA is still in an aqueous solution with the presence of a reductive/oxidative system (ROXS). Furthermore, the experimental setup allows for the analysis and eventual normalization of Förster-resonance-energy-transfer (FRET) interaction of cyanine-3/cyanine-5 dye combinations on the microarray. These findings constitute a step towards standardization of microarray experiments and analysis and may help to increase the comparability of microarray experiment results between labs.

  13. Optimization of Cyanine Dye Stability and Analysis of FRET Interaction on DNA Microarrays

    Directory of Open Access Journals (Sweden)

    Marcel von der Haar

    2016-11-01

    Full Text Available The application of DNA microarrays for high throughput analysis of genetic regulation is often limited by the fluorophores used as markers. The implementation of multi-scan techniques is limited by the fluorophores’ susceptibility to photobleaching when exposed to the scanner laser light. This paper presents combined mechanical and chemical strategies which enhance the photostability of cyanine 3 and cyanine 5 as part of solid state DNA microarrays. These strategies are based on scanning the microarrays while the hybridized DNA is still in an aqueous solution with the presence of a reductive/oxidative system (ROXS. Furthermore, the experimental setup allows for the analysis and eventual normalization of Förster-resonance-energy-transfer (FRET interaction of cyanine-3/cyanine-5 dye combinations on the microarray. These findings constitute a step towards standardization of microarray experiments and analysis and may help to increase the comparability of microarray experiment results between labs.

  14. 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.

  15. 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.  

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

    Directory of Open Access Journals (Sweden)

    Bernhard Schweighofer

    2015-06-01

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

  17. 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.

  18. NAPPA as a Real New Method for Protein Microarray Generation.

    Science.gov (United States)

    Díez, Paula; González-González, María; Lourido, Lucía; Dégano, Rosa M; Ibarrola, Nieves; Casado-Vela, Juan; LaBaer, Joshua; Fuentes, Manuel

    2015-04-24

    Nucleic Acid Programmable Protein Arrays (NAPPA) have emerged as a powerful and innovative technology for the screening of biomarkers and the study of protein-protein interactions, among others possible applications. The principal advantages are the high specificity and sensitivity that this platform offers. Moreover, compared to conventional protein microarrays, NAPPA technology avoids the necessity of protein purification, which is expensive and time-consuming, by substituting expression in situ with an in vitro transcription/translation kit. In summary, NAPPA arrays have been broadly employed in different studies improving knowledge about diseases and responses to treatments. Here, we review the principal advances and applications performed using this platform during the last years.

  19. 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....

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

    Directory of Open Access Journals (Sweden)

    Jung Klaus

    2011-04-01

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

  1. Identifying distinct classes of bladder carcinoma using microarrays

    DEFF Research Database (Denmark)

    Andersen, Lars Dyrskjøt; Andersen, Thomas Thykjær; Kruhøffer, Mogens;

    2003-01-01

    Bladder cancer is a common malignant disease characterized by frequent recurrences. The stage of disease at diagnosis and the presence of surrounding carcinoma in situ are important in determining the disease course of an affected individual. Despite considerable effort, no accepted...... immunohistological or molecular markers have been identified to define clinically relevant subsets of bladder cancer. Here we report the identification of clinically relevant subclasses of bladder carcinoma using expression microarray analysis of 40 well characterized bladder tumors. Hierarchical cluster analysis...... of 68 tumors. The classifier provided new predictive information on disease progression in Ta tumors compared with conventional staging (P expression patterns in 31 tumors by applying a supervised learning...

  2. High throughput production of mouse monoclonal antibodies using antigen microarrays

    DEFF Research Database (Denmark)

    De Masi, Federico; Chiarella, P.; Wilhelm, H.;

    2005-01-01

    Recent advances in proteomics research underscore the increasing need for high-affinity monoclonal antibodies, which are still generated with lengthy, low-throughput antibody production techniques. Here we present a semi-automated, high-throughput method of hybridoma generation and identification....... Monoclonal antibodies were raised to different targets in single batch runs of 6-10 wk using multiplexed immunisations, automated fusion and cell-culture, and a novel antigen-coated microarray-screening assay. In a large-scale experiment, where eight mice were immunized with ten antigens each, we generated...

  3. Gene Expression Network Reconstruction by LEP Method Using Microarray Data

    Directory of Open Access Journals (Sweden)

    Na You

    2012-01-01

    Full Text Available Gene expression network reconstruction using microarray data is widely studied aiming to investigate the behavior of a gene cluster simultaneously. Under the Gaussian assumption, the conditional dependence between genes in the network is fully described by the partial correlation coefficient matrix. Due to the high dimensionality and sparsity, we utilize the LEP method to estimate it in this paper. Compared to the existing methods, the LEP reaches the highest PPV with the sensitivity controlled at the satisfactory level. A set of gene expression data from the HapMap project is analyzed for illustration.

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

    DEFF Research Database (Denmark)

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

    2007-01-01

    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....

  5. Segmentation of cDNA Microarray Images using Parallel Spectral Clustering

    Directory of Open Access Journals (Sweden)

    Sandrine MOUYSSET

    2013-05-01

    Full Text Available Microarray technology generates large amounts of expression level of genes to be analyzed simultaneously. This analysis implies microarray image segmentation to extract the quantitative information from spots. Spectral clustering is one of the most relevant unsupervised methods able to gather data without a priori information on shapes or locality. We propose and test on microarray images a parallel strategy for the Spectral Clustering method based on domain decomposition with a criterion to determine the number of clusters.

  6. 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 ...

  7. Using microarrays to study the microenvironment in tumor biology: The crucial role of statistics

    OpenAIRE

    2008-01-01

    Microarrays represent a potentially powerful tool for better understanding the role of the microenvironment on tumor biology. To make the best use of microarray data and avoid incorrect or unsubstantiated conclusions, care must be taken in the statistical analysis. To illustrate the statistical issues involved we discuss three microarray studies related to the microenvironment and tumor biology involving: (i) prostatic stroma cells in cancer and non-cancer tissues; (ii) breast stroma and epit...

  8. Immune-Signatures for Lung Cancer Diagnostics: Evaluation of Protein Microarray Data Normalization Strategies

    OpenAIRE

    2015-01-01

    New minimal invasive diagnostic methods for early detection of lung cancer are urgently needed. It is known that the immune system responds to tumors with production of tumor-autoantibodies. Protein microarrays are a suitable highly multiplexed platform for identification of autoantibody signatures against tumor-associated antigens (TAA). These microarrays can be probed using 0.1 mg immunoglobulin G (IgG), purified from 10 µL of plasma. We used a microarray comprising recombinant proteins der...

  9. Segmentation of cDNA Microarray Images using Parallel Spectral Clustering

    Directory of Open Access Journals (Sweden)

    Daniel RUIZ

    2013-05-01

    Full Text Available Microarray technology generates large amounts of expression level of genes to be analyzed simultaneously. This analysis implies microarray image segmentation to extract the quantitative information from spots. Spectral clustering is one of the most relevant unsupervised methods able to gather data without a priori information on shapes or locality. We propose and test on microarray images a parallel strategy for the Spectral Clustering method based on domain decomposition with a criterion to determine the number of clusters.

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. Characterization and simulation of cDNA microarray spots using a novel mathematical model

    OpenAIRE

    2007-01-01

    Abstract Background The quality of cDNA microarray data is crucial for expanding its application to other research areas, such as the study of gene regulatory networks. Despite the fact that a number of algorithms have been suggested to increase the accuracy of microarray gene expression data, it is necessary to obtain reliable microarray images by improving wet-lab experiments. As the first step of a cDNA microarray experiment, spotting cDNA probes is critical to determining the quality of s...

  15. Calculation of Spot Reliability Evaluation Scores (SRED) for DNA Microarray Data.

    Science.gov (United States)

    Shimokawa, Kazuro; Kodzius, Rimantas; Matsumura, Yonehiro; Hayashizaki, Yoshihide

    2008-02-01

    INTRODUCTIONIn terms of cost per measurement, the use of DNA microarrays for comprehensive and quantitative expression measurements is vastly superior to other methods such as Northern blotting or quantitative reverse transcriptase polymerase chain reaction (QRT-PCR). However, the output values of DNA microarrays are not always highly reliable or accurate compared with other techniques, and the output data sometimes consist of measurements of relative expression (treated sample vs. untreated) rather than absolute expression values as desired. In effect, some measurements from some laboratories do not represent absolute expression values (such as the number of transcripts) and as such are experimentally deficient. This protocol addresses one problem in some microarray data: the absence of accurate measurements. Spot reliability evaluation score for DNA microarrays (SRED) offers a reliability value for each spot in the microarray. SRED does not require an entire microarray to assess the reliability, but rather analyzes the reliability of individual spots of the microarray. The calculation of a reliability index can be used for different microarray systems, which facilitates the analysis of multiple microarray data sets from different experimental platforms.

  16. Dispositivo de lectura de microarrays de tipo eléctrico y reutilizable

    OpenAIRE

    Fernández Sánchez, César; Bonilla Aguilar, Diana Lissette; Baldi Coll, Antonio; Rica Quesada, Roberto de la

    2010-01-01

    Dispositivo de lectura de microarrays de tipo eléctrico y reutilizable. El objeto principal de la presente invención es un dispositivo de lectura eléctrica de microarrays que se puede limpiar y volver a utilizar más de una vez. El dispositivo (1, 1’, 1”) de lectura de microarrays (6) tiene las siguientes partes: una base (2, 2’, 2”), que tiene unos medios de apoyo (3, 3’, 3”) para situar la superficie de test (7) del microarray (6) en paralelo a una superficie de lectu...

  17. 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.

  18. Development and validation of a bovine macrophage specific cDNA microarray

    Directory of Open Access Journals (Sweden)

    Waddington David

    2006-09-01

    Full Text Available Abstract Background The response of macrophages to danger signals is an important early stage in the immune response. Our understanding of this complex event has been furthered by microarray analysis, which allows the simultaneous investigation of the expression of large numbers of genes. However, the microarray resources available to study these events in livestock animals are limited. Results Here we report the development of a bovine macrophage specific (BoMP cDNA microarray. The BoMP microarray contains 5026 sequence elements (printed in duplicate and numerous controls. The majority of the clones incorporated on the microarray were derived from the BoMP cDNA library generated from bovine myeloid cells subjected to various stimuli, including over 900 sequences unique to the library. Additional clones representing immunologically important genes have been included on the BoMP microarray. The microarray was validated by investigating the response of bovine monocytes to stimulation with interferon-γ and lipopolysaccharide using amplified RNA. At 2 and 16 hours post stimulation 695 genes exhibited statistically significant differential expression, including; 26 sequences unique to the BoMP library, interleukin 6, prion protein and toll-like receptor 4. Conclusion A 5 K cDNA microarray has been successfully developed to investigate gene expression in bovine myeloid cells. The BoMP microarray is available from the ARK-Genomics Centre for Functional Genomics in Farm Animals, UK.

  19. Biocompatible Hydrogels for Microarray Cell Printing and Encapsulation

    Directory of Open Access Journals (Sweden)

    Akshata Datar

    2015-10-01

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

  20. 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.

  1. 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.

  2. 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.

  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. 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.

  5. Kinship Testing Based on SNPs Using Microarray System

    Science.gov (United States)

    Cho, Sohee; Seo, Hee Jin; Lee, Jihyun; Yu, Hyung Jin; Lee, Soong Deok

    2016-01-01

    Background Kinship testing using biallelic SNP markers has been demonstrated to be a promising approach as a supplement to standard STR typing, and several systems, such as pyrosequencing and microarray, have been introduced and utilized in real forensic cases. The Affymetrix microarray containing 169 autosomal SNPs developed for forensic application was applied to our practical case for kinship analysis that had remained inconclusive due to partial STR profiles of degraded DNA and possibility of inbreeding within the population. Case Report 169 autosomal SNPs were typed on array with severely degraded DNA of two bone samples, and the kinship compared to genotypes in a reference database of their putative family members. Results Two bone samples remained unidentified through traditional STR typing with partial profiles of 10 or 14 of 16 alleles. Because these samples originated from a geographically isolated population, a cautious approach was required when analyzing and declaring true paternity only based on PI values. In a supplementary SNP typing, 106 and 78 SNPs were obtained, and the match candidates were found in each case with improved PI values than using only STRs and with no discrepant SNPs in comparison. Conclusion Our case showed that the utility of multiple SNPs on array is expected in practical forensic caseworks with an establishment of reference database. PMID:27994531

  6. Genetic Programming Based Ensemble System for Microarray Data Classification

    Directory of Open Access Journals (Sweden)

    Kun-Hong Liu

    2015-01-01

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

  7. 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.

  8. ArrayD: A general purpose software for Microarray design

    Directory of Open Access Journals (Sweden)

    Sharma Vineet K

    2004-10-01

    Full Text Available Abstract Background Microarray is a high-throughput technology to study expression of thousands of genes in parallel. A critical aspect of microarray production is the design aimed at space optimization while maximizing the number of gene probes and their replicates to be spotted. Results We have developed a software called 'ArrayD' that offers various alternative design solutions for an array given a set of user requirements. The user feeds the following inputs: type of source plates to be used, number of gene probes to be printed, number of replicates and number of pins to be used for printing. The solutions are stored in a text file. The choice of a design solution to be used will be governed by the spotting chemistry to be used and the accuracy of the robot. Conclusions ArrayD is a software for standard cartesian robots. The software aids users in preparing a judicious and elegant design. ArrayD is universally applicable and is available at http://www.igib.res.in/scientists/arrayd/arrayd.html.

  9. Protein microarrays using liquid phase fractionation of cell lysates.

    Science.gov (United States)

    Yan, Fang; Sreekumar, Arun; Laxman, Bharathi; Chinnaiyan, Arul M; Lubman, David M; Barder, Timothy J

    2003-07-01

    We describe an approach in which protein microarrays are produced using a two-dimensional (2-D) liquid phase fractionation of cell lysates. The method involves a pI-based fractionation using chromatofocusing in the first dimension followed by nonporous reversed-phase high-performance liquid chromatography (HPLC) of each pI fraction in the second dimension. This allows fractionation of cellular proteins in the liquid phase that could then be arrayed on nitrocellulose slides and used to study humoral response in cancer. Protein microarrays have been used to identify potential serum biomarkers for prostate cancer. It is shown that specific fractions are immunoreactive against prostate cancer serum but not against serum from healthy individuals. These proteins could serve as sero-diagnostic markers for prostate cancer. Importantly, this method allows for use of post-translationally modified proteins as baits for detection of humoral response. Proteins eliciting an immune response are identified using the molecular mass and peptide sequence data obtained using mass spectrometric analysis of the liquid fractions. The fractionation of proteins in the liquid phase make this method amenable to automation.

  10. 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.

  11. Is there a niche for DNA microarrays in molecular diagnostics?

    Science.gov (United States)

    Jordan, Bertrand R

    2010-10-01

    DNA microarrays, 15 years after their appearance, have achieved presence in a number of medical settings. Several tests have been introduced and have obtained regulatory approval, mostly in the fields of bacterial identification, mutation detection and the global assessment of genome alterations, a particularly successful case being the whole-genome assay of copy-number variations. Gene-expression applications have been less successful because of technical issues (e.g., reproducibility, platform-to-platform consistency and statistical issues in data analysis) and difficulties in demonstrating the clinical utility of expression signatures. In their different applications, DNA arrays have faced competition from PCR-based assays for low and intermediate multiplicity. Now they have a new competitor, new-generation sequencing, that can provide a wealth of direct sequence information, or digital gene-expression data, at a constantly decreasing cost. In this article we evaluate the strengths and weaknesses of the DNA microarray approach to diagnostics, and highlight the fields in which it is most likely to achieve a durable presence.

  12. 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.

  13. 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.

  14. Visualisation and pre-processing of peptide microarray data.

    Science.gov (United States)

    Reilly, Marie; Valentini, Davide

    2009-01-01

    The data files produced by digitising peptide microarray images contain detailed information on the location, feature, response parameters and quality of each spot on each array. In this chapter, we will describe how such peptide microarray data can be read into the R statistical package and pre-processed in preparation for subsequent comparative or predictive analysis. We illustrate how the information in the data can be visualised using images and graphical displays that highlight the main features, enabling the quality of the data to be assessed and invalid data points to be identified and excluded. The log-ratio of the foreground to background signal is used as a response index. Negative control responses serve as a reference against which "detectable" responses can be defined, and slides incubated with only buffer and secondary antibody help identify false-positive responses from peptides. For peptides that have a detectable response on at least one subarray, and no false-positive response, we use linear mixed models to remove artefacts due to the arrays and their architecture. The resulting normalized responses provide the input data for further analysis.

  15. Kinship Testing Based on SNPs Using Microarray System.

    Science.gov (United States)

    Cho, Sohee; Seo, Hee Jin; Lee, Jihyun; Yu, Hyung Jin; Lee, Soong Deok

    2016-11-01

    Kinship testing using biallelic SNP markers has been demonstrated to be a promising approach as a supplement to standard STR typing, and several systems, such as pyrosequencing and microarray, have been introduced and utilized in real forensic cases. The Affymetrix microarray containing 169 autosomal SNPs developed for forensic application was applied to our practical case for kinship analysis that had remained inconclusive due to partial STR profiles of degraded DNA and possibility of inbreeding within the population. 169 autosomal SNPs were typed on array with severely degraded DNA of two bone samples, and the kinship compared to genotypes in a reference database of their putative family members. Two bone samples remained unidentified through traditional STR typing with partial profiles of 10 or 14 of 16 alleles. Because these samples originated from a geographically isolated population, a cautious approach was required when analyzing and declaring true paternity only based on PI values. In a supplementary SNP typing, 106 and 78 SNPs were obtained, and the match candidates were found in each case with improved PI values than using only STRs and with no discrepant SNPs in comparison. Our case showed that the utility of multiple SNPs on array is expected in practical forensic caseworks with an establishment of reference database.

  16. 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.

  17. Gene set analyses for interpreting microarray experiments on prokaryotic organisms.

    Energy Technology Data Exchange (ETDEWEB)

    Tintle, Nathan; Best, Aaron; Dejongh, Matthew; VanBruggen, Dirk; Heffron, Fred; Porwollik, Steffen; Taylor, Ronald C.

    2008-11-05

    Background: Recent advances in microarray technology have brought with them the need for enhanced methods of biologically interpreting gene expression data. Recently, methods like Gene Set Enrichment Analysis (GSEA) and variants of Fisher’s exact test have been proposed which utilize a priori biological information. Typically, these methods are demonstrated with a priori biological information from the Gene Ontology. Results: Alternative gene set definitions are presented based on gene sets inferred from the SEED: open-source software environment for comparative genome annotation and analysis of microbial organisms. Many of these gene sets are then shown to provide consistent expression across a series of experiments involving Salmonella Typhimurium. Implementation of the gene sets in an analysis of microarray data is then presented for the Salmonella Typhimurium data. Conclusions: SEED inferred gene sets can be naturally defined based on subsystems in the SEED. The consistent expression values of these SEED inferred gene sets suggest their utility for statistical analyses of gene expression data based on a priori biological information

  18. Novel multiple 5'-amino-modified primer for DNA microarrays.

    Science.gov (United States)

    Han, Jing; Lee, Hin; Nguyen, Nga Yen; Beaucage, Serge L; Puri, Raj K

    2005-08-01

    For DNA microarray analysis, total RNA is reverse-transcribed, labeled by incorporating fluorescent dye into the cDNA, and used to hybridize microarray. This protocol requires a minimum of 20 microg of total RNA. To overcome the sample limitation, an RNA amplification technique has been developed. Although it needs less RNA, this amplification technique is relatively expensive, time consuming, and, unfortunately, has been found to introduce bias. In this study, we designed a novel 5'-amino-modified primer and used it for priming cDNA synthesis. The novel primer has a special structure that contains four Uni-Link molecules with two nucleotide (thymine) residues inserted between them as spacers. This novel primer is used in the reverse-transcription reaction for cDNA synthesis. Using the novel 5'-modified primer combined with indirect labeling method, cDNA probes can be prepared with much less total RNA (5 microg or less) without amplification producing optimal results after hybridization of arrays. This primer can also be used to label nucleotides for other purposes.

  19. 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.

  20. Cluster stability scores for microarray data in cancer studies

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    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.

  1. 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).

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

    Directory of Open Access Journals (Sweden)

    Eils Roland

    2005-11-01

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

  3. Assessment and integration of publicly available SAGE, cDNA microarray, and oligonucleotide microarray expression data for global coexpression analyses.

    Science.gov (United States)

    Griffith, Obi L; Pleasance, Erin D; Fulton, Debra L; Oveisi, Mehrdad; Ester, Martin; Siddiqui, Asim S; Jones, Steven J M

    2005-10-01

    Large amounts of gene expression data from several different technologies are becoming available to the scientific community. A common practice is to use these data to calculate global gene coexpression for validation or integration of other "omic" data. To assess the utility of publicly available datasets for this purpose we have analyzed Homo sapiens data from 1202 cDNA microarray experiments, 242 SAGE libraries, and 667 Affymetrix oligonucleotide microarray experiments. The three datasets compared demonstrate significant but low levels of global concordance (rc<0.11). Assessment against Gene Ontology (GO) revealed that all three platforms identify more coexpressed gene pairs with common biological processes than expected by chance. As the Pearson correlation for a gene pair increased it was more likely to be confirmed by GO. The Affymetrix dataset performed best individually with gene pairs of correlation 0.9-1.0 confirmed by GO in 74% of cases. However, in all cases, gene pairs confirmed by multiple platforms were more likely to be confirmed by GO. We show that combining results from different expression platforms increases reliability of coexpression. A comparison with other recently published coexpression studies found similar results in terms of performance against GO but with each method producing distinctly different gene pair lists.

  4. 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

  5. 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

  6. 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

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

    DEFF Research Database (Denmark)

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

    2007-01-01

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

  8. A 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

    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

  9. Reproducibility of oligonucleotide microarray transcriptome analyses - An interlaboratory comparison using chemostat cultures of Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Piper, M.D.W.; Daran-Lapujade, P.; Bro, Christoffer;

    2002-01-01

    Assessment of reproducibility of DNA-microarray analysis from published data sets is complicated by the use of different microbial strains, cultivation techniques, and analytical procedures. Because intra- and interlaboratory reproducibility is highly relevant for application of DNA-microarray an...

  10. An oligonucleotide-tagged microarray for routine diagnostics of colon cancer by genotyping KRAS mutations

    DEFF Research Database (Denmark)

    Liu, Yuliang; Guðnason, Haukur; Li, Yiping

    2014-01-01

    or spiked fecal samples. The immobilized tag-probes were stable under multiple thermal cycling treatments, allowing re-use of the tag-microarray and further optimization to solid PCR. Our results demonstrated that a novel oligonucleotide-tagged microarray system has been developed which would be suitable...

  11. A novel scheme to assess factors involved in the reproducibility of DNA-microarray data

    NARCIS (Netherlands)

    Hijum, Sacha A.F.T. van; Jong, Anne de; Baerends, Richard J.S.; Karsens, Harma A.; Kramer, Naomi E.; Larsen, Rasmus; Hengst, Chris D. den; Albers, Casper J.; Kok, Jan; Kuipers, Oscar P.

    2005-01-01

    Background: In research laboratories using DNA-microarrays, usually a number of researchers perform experiments, each generating possible sources of error. There is a need for a quick and robust method to assess data quality and sources of errors in DNA-microarray experiments. To this end, a novel a

  12. Reproducibility of oligonucleotide microarray transcriptome analyses - An interlaboratory comparison using chemostat cultures of Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Piper, M.D.W.; Daran-Lapujade, P.; Bro, Christoffer

    2002-01-01

    Assessment of reproducibility of DNA-microarray analysis from published data sets is complicated by the use of different microbial strains, cultivation techniques, and analytical procedures. Because intra- and interlaboratory reproducibility is highly relevant for application of DNA-microarray an...

  13. 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

  14. The application of phenotypic microarray analysis to anti-fungal drug development.

    Science.gov (United States)

    Greetham, Darren; Lappin, David F; Rajendran, Ranjith; O'Donnell, Lindsay; Sherry, Leighann; Ramage, Gordon; Nile, Christopher

    2017-03-01

    Candida albicans metabolic activity in the presence and absence of acetylcholine was measured using phenotypic microarray analysis. Acetylcholine inhibited C. albicans biofilm formation by slowing metabolism independent of biofilm forming capabilities. Phenotypic microarray analysis can therefore be used for screening compound libraries for novel anti-fungal drugs and measuring antifungal resistance.

  15. 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

  16. 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

  17. An experimental evaluation of a loop versus a reference design for two-channel microarrays

    NARCIS (Netherlands)

    Vinciotti, V.; Khanin, R.; Alimonte, D. D’; Liu, X.; Cattini, N.; Hotchkiss, G.; Bucca, G.; Jesus, O. de; Rasaiyaah, J.; Kellam, P.; Wit, Ernst

    2005-01-01

    Motivation: Despite theoretical arguments that so-called ‘loop designs’ for two-channel DNA microarray experiments are more efficient, biologists continue to use ‘reference designs’. We describe two sets of microarray experiments with RNA from two different biological systems (TPA-stimulated mammali

  18. High throughput screening of starch structures using carbohydrate microarrays

    DEFF Research Database (Denmark)

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

    2016-01-01

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

  19. SNPMClust: Bivariate Gaussian Genotype Clustering and Calling for Illumina Microarrays

    Directory of Open Access Journals (Sweden)

    Stephen W. Erickson

    2016-07-01

    Full Text Available SNPMClust is an R package for genotype clustering and calling with Illumina microarrays. It was originally developed for studies using the GoldenGate custom genotyping platform but can be used with other Illumina platforms, including Infinium BeadChip. The algorithm first rescales the fluorescent signal intensity data, adds empirically derived pseudo-data to minor allele genotype clusters, then uses the package mclust for bivariate Gaussian model fitting. We compared the accuracy and sensitivity of SNPMClust to that of GenCall, Illumina's proprietary algorithm, on a data set of 94 whole-genome amplified buccal (cheek swab DNA samples. These samples were genotyped on a custom panel which included 1064 SNPs for which the true genotype was known with high confidence. SNPMClust produced uniformly lower false call rates over a wide range of overall call rates.

  20. 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.

  1. NAPPA as a Real New Method for Protein Microarray Generation

    Directory of Open Access Journals (Sweden)

    Paula Díez

    2015-04-01

    Full Text Available Nucleic Acid Programmable Protein Arrays (NAPPA have emerged as a powerful and innovative technology for the screening of biomarkers and the study of protein-protein interactions, among others possible applications. The principal advantages are the high specificity and sensitivity that this platform offers. Moreover, compared to conventional protein microarrays, NAPPA technology avoids the necessity of protein purification, which is expensive and time-consuming, by substituting expression in situ with an in vitro transcription/translation kit. In summary, NAPPA arrays have been broadly employed in different studies improving knowledge about diseases and responses to treatments. Here, we review the principal advances and applications performed using this platform during the last years.

  2. 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...

  3. Exhaustive Search for Fuzzy Gene Networks from Microarray Data

    Energy Technology Data Exchange (ETDEWEB)

    Sokhansanj, B A; Fitch, J P; Quong, J N; Quong, A A

    2003-07-07

    Recent technological advances in high-throughput data collection allow for the study of increasingly complex systems on the scale of the whole cellular genome and proteome. Gene network models are required to interpret large and complex data sets. Rationally designed system perturbations (e.g. gene knock-outs, metabolite removal, etc) can be used to iteratively refine hypothetical models, leading to a modeling-experiment cycle for high-throughput biological system analysis. We use fuzzy logic gene network models because they have greater resolution than Boolean logic models and do not require the precise parameter measurement needed for chemical kinetics-based modeling. The fuzzy gene network approach is tested by exhaustive search for network models describing cyclin gene interactions in yeast cell cycle microarray data, with preliminary success in recovering interactions predicted by previous biological knowledge and other analysis techniques. Our goal is to further develop this method in combination with experiments we are performing on bacterial regulatory networks.

  4. 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.

  5. 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.

  6. Random forest for gene selection and microarray data classification.

    Science.gov (United States)

    Moorthy, Kohbalan; Mohamad, Mohd Saberi

    2011-01-01

    A random forest method has been selected to perform both gene selection and classification of the microarray data. In this embedded method, the selection of smallest possible sets of genes with lowest error rates is the key factor in achieving highest classification accuracy. Hence, improved gene selection method using random forest has been proposed to obtain the smallest subset of genes as well as biggest subset of genes prior to classification. The option for biggest subset selection is done to assist researchers who intend to use the informative genes for further research. Enhanced random forest gene selection has performed better in terms of selecting the smallest subset as well as biggest subset of informative genes with lowest out of bag error rates through gene selection. Furthermore, the classification performed on the selected subset of genes using random forest has lead to lower prediction error rates compared to existing method and other similar available methods.

  7. 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...

  8. 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.

  9. 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.

  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. Recyclable hydrophilic-hydrophobic micropatterns on glass for microarray applications.

    Science.gov (United States)

    Zhang, Hua; Lee, Yong Yeow; Leck, Kwong Joo; Kim, Namyong Y; Ying, Jackie Y

    2007-04-24

    A novel method for fabricating recyclable hydrophilic-hydrophobic micropatterns on glass chips is presented. TiOx patterns (100-2000 microm) were sputtered on glass chips via a through-hole mask. The patterned chips were then vapor-coated with fluoroalkylsilane, for example, (heptadecafluoro-1,1,2,2-tetrahydrodecyl)triethoxysilane (FTES) to form a hydrophobic coating layer. The fluoroalkyl chain of FTES film on TiOx patterns was photocleaved under UV irradiation, exposing the fresh hydrophilic TiOx patterns. The resulting chip could be used multiple times by repeating the coating and photocleaving processes with negligible deterioration of the hydrophobic FTES film coated on glass. If desired, bare glass patterns could also be generated by removing the TiOx patterns with KOH. The patterned glass chips have been successfully used for microarray fabrication.

  12. 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.

  13. 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.

  14. 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.

  15. Caryoscope: An Open Source Java application for viewing microarray data in a genomic context

    Directory of Open Access Journals (Sweden)

    Ball Catherine A

    2004-10-01

    Full Text Available Abstract Background Microarray-based comparative genome hybridization experiments generate data that can be mapped onto the genome. These data are interpreted more easily when represented graphically in a genomic context. Results We have developed Caryoscope, which is an open source Java application for visualizing microarray data from array comparative genome hybridization experiments in a genomic context. Caryoscope can read General Feature Format files (GFF files, as well as comma- and tab-delimited files, that define the genomic positions of the microarray reporters for which data are obtained. The microarray data can be browsed using an interactive, zoomable interface, which helps users identify regions of chromosomal deletion or amplification. The graphical representation of the data can be exported in a number of graphic formats, including publication-quality formats such as PostScript. Conclusion Caryoscope is a useful tool that can aid in the visualization, exploration and interpretation of microarray data in a genomic context.

  16. ArrayNinja: An Open Source Platform for Unified Planning and Analysis of Microarray Experiments.

    Science.gov (United States)

    Dickson, B M; Cornett, E M; Ramjan, Z; Rothbart, S B

    2016-01-01

    Microarray-based proteomic platforms have emerged as valuable tools for studying various aspects of protein function, particularly in the field of chromatin biochemistry. Microarray technology itself is largely unrestricted in regard to printable material and platform design, and efficient multidimensional optimization of assay parameters requires fluidity in the design and analysis of custom print layouts. This motivates the need for streamlined software infrastructure that facilitates the combined planning and analysis of custom microarray experiments. To this end, we have developed ArrayNinja as a portable, open source, and interactive application that unifies the planning and visualization of microarray experiments and provides maximum flexibility to end users. Array experiments can be planned, stored to a private database, and merged with the imaged results for a level of data interaction and centralization that is not currently attainable with available microarray informatics tools.

  17. 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

    , and one reason for this is a lack of suitable glycans with which to populate arrays. Polysaccharide microarrays are relatively easy to produce because of the ease of immobilizing large polymers noncovalently onto a variety of microarray surfaces, but they lack analytical resolution because polysaccharides...... often contain multiple distinct carbohydrate substructures. Microarrays of defined oligosaccharides potentially overcome this problem but are harder to produce because oligosaccharides usually require coupling prior to immobilization. We have assembled a library of well characterized plant...... oligosaccharides produced either by partial hydrolysis from polysaccharides or by de novo chemical synthesis. Once coupled to protein, these neoglycoconjugates are versatile reagents that can be printed as microarrays onto a variety of slide types and membranes. We show that these microarrays are suitable...

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

    Science.gov (United States)

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

    2017-05-01

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

  19. 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.

  20. 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.

  1. Novel and future applications of microarrays in toxicological research.

    Science.gov (United States)

    Gant, Timothy W

    2007-08-01

    Microarray technologies have both fascinated and frustrated the toxicological community since their introduction around a decade ago. Fascination arose from the possibility offered by the technology to gain a profound insight into the cellular response to chemically mediated stress, and the potential that this genomic signature would be indicative of the biological mechanism by which that stress was induced. Frustrations have arisen primarily from technical factors such as data variance, the requirement for the application of advanced statistical and mathematical analysis, and difficulties associated with actually recognising signature gene expression patterns, and discerning mechanisms. Toxicogenomics was predicted to make toxicological assessment and extrapolation easier, faster and cheaper. The reality has been somewhat different; toxicogenomics is difficult. However, its potential when properly applied has been indicated by some well designed toxicogenomics studies, particularly in the differentiation of genotoxins from non-genotoxins. Technology waits though for no man. While the toxicological community has been working to apply transcriptomics (mRNA levels) in toxicology, the technology has moved beyond this application into new arenas. Some have application to toxicology and are reviewed here, except transcriptomics which has been extensively written about before. This review discusses the application of microarray technologies applied to the genome per se (amplifications, deletions, epigenetic change), mRNA translation and its control mechanisms through miRNA. Which of the new genomics technoï¿(1/2)logies will find most application in toxicology? In the opinion of the author there are three potentially major applications: i) arrayCGH in assessment and recognition of genotoxicity; ii) epigenetic assessment in developmental and transgenerational toxicology; and iii) miRNA assessment in all toxicology types, but particularly developmental toxicology.

  2. Whole genome microarray analysis, from neonatal blood cards

    Directory of Open Access Journals (Sweden)

    Hogan Michael E

    2009-07-01

    Full Text Available Abstract Background Neonatal blood, obtained from a heel stick and stored dry on paper cards, has been the standard for birth defects screening for 50 years. Such dried blood samples are used, primarily, for analysis of small-molecule analytes. More recently, the DNA complement of such dried blood cards has been used for targeted genetic testing, such as for single nucleotide polymorphism in cystic fibrosis. Expansion of such testing to include polygenic traits, and perhaps whole genome scanning, has been discussed as a formal possibility. However, until now the amount of DNA that might be obtained from such dried blood cards has been limiting, due to inefficient DNA recovery technology. Results A new technology is employed for efficient DNA release from a standard neonatal blood card. Using standard Guthrie cards, stored an average of ten years post-collection, about 1/40th of the air-dried neonatal blood specimen (two 3 mm punches was processed to obtain DNA that was sufficient in mass and quality for direct use in microarray-based whole genome scanning. Using that same DNA release technology, it is also shown that approximately 1/250th of the original purified DNA (about 1 ng could be subjected to whole genome amplification, thus yielding an additional microgram of amplified DNA product. That amplified DNA product was then used in microarray analysis and yielded statistical concordance of 99% or greater to the primary, unamplified DNA sample. Conclusion Together, these data suggest that DNA obtained from less than 10% of a standard neonatal blood specimen, stored dry for several years on a Guthrie card, can support a program of genome-wide neonatal genetic testing.

  3. 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

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

    Science.gov (United States)

    Hipp, Jennifer A; Hipp, Jason D; Lim, Megan; Sharma, Gaurav; Smith, Lauren B; Hewitt, Stephen M; Balis, Ulysses G J

    2012-01-01

    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. 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. 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 bodies, was subsequently carried out on the

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

    Science.gov (United States)

    Martinez-Godoy, M Angeles; Mauri, Nuria; Juarez, Jose; Marques, M Carmen; Santiago, Julia; Forment, Javier; Gadea, Jose

    2008-07-03

    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. 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. 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 studies in citrus by using it to catalogue genes expressed in

  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. 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

  8. Melanoma MAPK pathway proteins and associated tumour suppressors: p16 is an independent prognostic biomarker by tissue microarrays

    DEFF Research Database (Denmark)

    Lade-Keller, Johanne; Guldberg, Per; Hamilton-Dutoit, Stephen Jacques

    2013-01-01

    Melanoma MAPK pathway proteins and associated tumour suppressors: p16 is an independent prognostic biomarker by tissue microarrays......Melanoma MAPK pathway proteins and associated tumour suppressors: p16 is an independent prognostic biomarker by tissue microarrays...

  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. Confirmation of the molecular classification of diffuse large B-cell lymphoma by immunohistochemistry using a tissue microarray

    National Research Council Canada - National Science Library

    Hans, Christine P; Weisenburger, Dennis D; Greiner, Timothy C; Gascoyne, Randy D; Delabie, Jan; Ott, German; Müller-Hermelink, H Konrad; Campo, Elias; Braziel, Rita M; Jaffe, Elaine S; Pan, Zenggang; Farinha, Pedro; Smith, Lynette M; Falini, Brunangelo; Banham, Alison H; Rosenwald, Andreas; Staudt, Louis M; Connors, Joseph M; Armitage, James O; Chan, Wing C

    2004-01-01

    ...), activated B-cell-like (ABC), and type 3 gene expression profiles using a cDNA microarray. Tissue microarray (TMA) blocks were created from 152 cases of DLBCL, 142 of which had been successfully evaluated by cDNA microarray...

  11. A Web-based multi-database system supporting distributed collaborative management and sharing of microarray experiment information.

    Science.gov (United States)

    Burgarella, Sarah; Cattaneo, Dario; Masseroli, Marco

    2006-01-01

    We developed MicroGen, a multi-database Web based system for managing all the information characterizing spotted microarray experiments. It supports information gathering and storing according to the Minimum Information About Microarray Experiments (MIAME) standard. It also allows easy sharing of information and data among all multidisciplinary actors involved in spotted microarray experiments.

  12. Interpreting microarray data to build models of microbial genetic regulation networks

    Science.gov (United States)

    Sokhansanj, Bahrad A.; Garnham, Janine B.; Fitch, J. Patrick

    2002-06-01

    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 cell's global genetic regulatory networks. Besides poor signal characteristics, the massive number of data produced by microarray experiments pose 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.

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

    Science.gov (United States)

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

    2013-03-05

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

  14. Large scale comparison of gene expression levels by microarrays and RNAseq using TCGA data.

    Science.gov (United States)

    Guo, Yan; Sheng, Quanhu; Li, Jiang; Ye, Fei; Samuels, David C; Shyr, Yu

    2013-01-01

    RNAseq and microarray methods are frequently used to measure gene expression level. While similar in purpose, there are fundamental differences between the two technologies. Here, we present the largest comparative study between microarray and RNAseq methods to date using The Cancer Genome Atlas (TCGA) data. We found high correlations between expression data obtained from the Affymetrix one-channel microarray and RNAseq (Spearman correlations coefficients of ∼0.8). We also observed that the low abundance genes had poorer correlations between microarray and RNAseq data than high abundance genes. As expected, due to measurement and normalization differences, Agilent two-channel microarray and RNAseq data were poorly correlated (Spearman correlations coefficients of only ∼0.2). By examining the differentially expressed genes between tumor and normal samples we observed reasonable concordance in directionality between Agilent two-channel microarray and RNAseq data, although a small group of genes were found to have expression changes reported in opposite directions using these two technologies. Overall, RNAseq produces comparable results to microarray technologies in term of expression profiling. The RNAseq normalization methods RPKM and RSEM produce similar results on the gene level and reasonably concordant results on the exon level. Longer exons tended to have better concordance between the two normalization methods than shorter exons.

  15. A Platform for Combined DNA and Protein Microarrays Based on Total Internal Reflection Fluorescence

    Directory of Open Access Journals (Sweden)

    Alexander Asanov

    2012-02-01

    Full Text Available We have developed a novel microarray technology based on total internal reflection fluorescence (TIRF in combination with DNA and protein bioassays immobilized at the TIRF surface. Unlike conventional microarrays that exhibit reduced signal-to-background ratio, require several stages of incubation, rinsing and stringency control, and measure only end-point results, our TIRF microarray technology provides several orders of magnitude better signal-to-background ratio, performs analysis rapidly in one step, and measures the entire course of association and dissociation kinetics between target DNA and protein molecules and the bioassays. In many practical cases detection of only DNA or protein markers alone does not provide the necessary accuracy for diagnosing a disease or detecting a pathogen. Here we describe TIRF microarrays that detect DNA and protein markers simultaneously, which reduces the probabilities of false responses. Supersensitive and multiplexed TIRF DNA and protein microarray technology may provide a platform for accurate diagnosis or enhanced research studies. Our TIRF microarray system can be mounted on upright or inverted microscopes or interfaced directly with CCD cameras equipped with a single objective, facilitating the development of portable devices. As proof-of-concept we applied TIRF microarrays for detecting molecular markers from Bacillus anthracis, the pathogen responsible for anthrax.

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. Reusable conductimetric array of interdigitated microelectrodes for the readout of low-density microarrays.

    Science.gov (United States)

    Mallén, Maria; Díaz-González, María; Bonilla, Diana; Salvador, Juan P; Marco, María P; Baldi, Antoni; Fernández-Sánchez, César

    2014-06-17

    Low-density protein microarrays are emerging tools in diagnostics whose deployment could be primarily limited by the cost of fluorescence detection schemes. This paper describes an electrical readout system of microarrays comprising an array of gold interdigitated microelectrodes and an array of polydimethylsiloxane microwells, which enabled multiplexed detection of up to thirty six biological events on the same substrate. Similarly to fluorescent readout counterparts, the microarray can be developed on disposable glass slide substrates. However, unlike them, the presented approach is compact and requires a simple and inexpensive instrumentation. The system makes use of urease labeled affinity reagents for developing the microarrays and is based on detection of conductivity changes taking place when ionic species are generated in solution due to the catalytic hydrolysis of urea. The use of a polydimethylsiloxane microwell array facilitates the positioning of the measurement solution on every spot of the microarray. Also, it ensures the liquid tightness and isolation from the surrounding ones during the microarray readout process, thereby avoiding evaporation and chemical cross-talk effects that were shown to affect the sensitivity and reliability of the system. The performance of the system is demonstrated by carrying out the readout of a microarray for boldenone anabolic androgenic steroid hormone. Analytical results are comparable to those obtained by fluorescent scanner detection approaches. The estimated detection limit is 4.0 ng mL(-1), this being below the threshold value set by the World Anti-Doping Agency and the European Community.

  1. 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

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

    Directory of Open Access Journals (Sweden)

    Ludwig Nicole

    2010-11-01

    Full Text Available Abstract Background 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. Methods 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. Result 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. Conclusion 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

  3. On the statistical assessment of classifiers using DNA microarray data

    Directory of Open Access Journals (Sweden)

    Carella M

    2006-08-01

    Full Text Available Abstract Background In this paper we present a method for the statistical assessment of cancer predictors which make use of gene expression profiles. The methodology is applied to a new data set of microarray gene expression data collected in Casa Sollievo della Sofferenza Hospital, Foggia – Italy. The data set is made up of normal (22 and tumor (25 specimens extracted from 25 patients affected by colon cancer. We propose to give answers to some questions which are relevant for the automatic diagnosis of cancer such as: Is the size of the available data set sufficient to build accurate classifiers? What is the statistical significance of the associated error rates? In what ways can accuracy be considered dependant on the adopted classification scheme? How many genes are correlated with the pathology and how many are sufficient for an accurate colon cancer classification? The method we propose answers these questions whilst avoiding the potential pitfalls hidden in the analysis and interpretation of microarray data. Results We estimate the generalization error, evaluated through the Leave-K-Out Cross Validation error, for three different classification schemes by varying the number of training examples and the number of the genes used. The statistical significance of the error rate is measured by using a permutation test. We provide a statistical analysis in terms of the frequencies of the genes involved in the classification. Using the whole set of genes, we found that the Weighted Voting Algorithm (WVA classifier learns the distinction between normal and tumor specimens with 25 training examples, providing e = 21% (p = 0.045 as an error rate. This remains constant even when the number of examples increases. Moreover, Regularized Least Squares (RLS and Support Vector Machines (SVM classifiers can learn with only 15 training examples, with an error rate of e = 19% (p = 0.035 and e = 18% (p = 0.037 respectively. Moreover, the error rate

  4. 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

  5. On the Statics for Micro-Array Data Analysis

    Science.gov (United States)

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

    2010-01-01

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

  6. Multiplex Serum Cytokine Immunoassay Using Nanoplasmonic Biosensor Microarrays

    Science.gov (United States)

    Chen, Pengyu; Chung, Meng Ting; McHugh, Walker; Nidetz, Robert; Li, Yuwei; Fu, Jianping; Cornell, Timothy T.; Shanley, Thomas P.; Kurabayashi, Katsuo

    2015-01-01

    Precise monitoring of the rapidly changing immune status during the course of a disease requires multiplex analysis of cytokines from frequently sampled human blood. However, the current lack of rapid, multiplex, and low volume assays makes immune monitoring for clinical decision-making (e.g., critically ill patients) impractical. Without such assays, immune monitoring is even virtually impossible for infants and neonates with infectious diseases and/or immune mediated disorders as access to their blood in large quantities is prohibited. Localized surface plasmon resonance (LSPR)-based microfluidic optical biosensing is a promising approach to fill this technical gap as it could potentially permit real-time refractometric detection of biomolecular binding on a metallic nanoparticle surface and sensor miniaturization, both leading to rapid and sample-sparing analyte analysis. Despite this promise, practical implementation of such a microfluidic assay for cytokine biomarker detection in serum samples has not been established primarily due to the limited sensitivity of LSPR biosensing. Here, we developed a high-throughput, label-free, multiarrayed LSPR optical biosensor device with 480 nanoplasmonic sensing spots in microfluidic channel arrays and demonstrated parallel multiplex immunoassays of six cytokines in a complex serum matrix on a single device chip while overcoming technical limitations. The device was fabricated using easy-to-implement, one-step microfluidic patterning and antibody conjugation of gold nanorods (AuNRs). When scanning the scattering light intensity across the microarrays of AuNR ensembles with dark-field imaging optics, our LSPR biosensing technique allowed for high-sensitivity quantitative cytokine measurements at concentrations down to 5–20 pg/mL from a 1 µL serum sample. Using the nanoplasmonic biosensor microarray device, we demonstrated the ability to monitor the inflammatory responses of infants following cardiopulmonary bypass (CPB

  7. From single gene to integrative molecular concept MAPS: pitfalls and potentials of microarray technology.

    Science.gov (United States)

    Chiorino, G; Mello Grand, M; Scatolini, M; Ostano, P

    2008-01-01

    Microarray experiments have a large variety of applications and several important achievements have been obtained by means of this technology, especially within the field of whole genome expression profiling, which undoubtedly is the most diffused world-wide. Nevertheless, care must be taken in unconditionally applying such high-throughput techniques and in extracting/interpreting their results. Both the validity and the reproducibility of microarray-based clinical research have recently been challenged. Pitfalls and potentials of the microarray technology for gene expression profiling are critically reviewed in this paper.

  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....

  9. Microarray Technology for the Diagnosis of Fetal Chromosomal Aberrations: Which Platform Should We Use?

    Directory of Open Access Journals (Sweden)

    Evangelia Karampetsou

    2014-06-01

    Full Text Available The advantage of microarray (array over conventional karyotype for the diagnosis of fetal pathogenic chromosomal anomalies has prompted the use of microarrays in prenatal diagnostics. In this review we compare the performance of different array platforms (BAC, oligonucleotide CGH, SNP and designs (targeted, whole genome, whole genome, and targeted, custom and discuss their advantages and disadvantages in relation to prenatal testing. We also discuss the factors to consider when implementing a microarray testing service for the diagnosis of fetal chromosomal aberrations.

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

    DEFF Research Database (Denmark)

    Dufva, Martin; Petersen, Jesper; Poulsen, Lena

    2009-01-01

    DNA microarrays have for a decade been the only platform for genome-wide analysis and have provided a wealth of information about living organisms. DNA microarrays are processed today under one condition only, which puts large demands on assay development because all probes on the array need...... to function optimally under one condition only. Microarrays are often burdened with a significant degree of cross-hybridization, because of a poor combination of assay conditions and probe choice. As reviewed here, a number of promising microfluidics-based technologies can provide automatic processing...

  11. 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.

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

    Science.gov (United States)

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

    2013-01-01

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

  13. Particle-Based Microarrays of Oligonucleotides and Oligopeptides.

    Science.gov (United States)

    Nesterov-Mueller, Alexander; Maerkle, Frieder; Hahn, Lothar; Foertsch, Tobias; Schillo, Sebastian; Bykovskaya, Valentina; Sedlmayr, Martyna; Weber, Laura K; Ridder, Barbara; Soehindrijo, Miriam; Muenster, Bastian; Striffler, Jakob; Bischoff, F Ralf; Breitling, Frank; Loeffler, Felix F

    2014-10-28

    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.

  14. 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.

  15. 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.

  16. 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.

  17. Evolving applications of microarray technology in postnatal diagnosis (review).

    Science.gov (United States)

    Kang, Ji Un; Koo, Sun Hoe

    2012-08-01

    Microarray-based cytogenetics is revealing the tremendous fluidity and complexity of the human genome, and is starting to illustrate the implications of genomic variability with respect to human health and disease. In the last few years, the robustness of array-based technologies has provided accurate diagnosis and appropriate clinical management in a timely and efficient manner for identifying genomic defects of congenital and developmental abnormalities including developmental delay (DD), intellectual disability (ID), autism spectrum disorders (ASD) and/or multiple congenital anomalies (MCA). The implementation of this technology in these categories of disorders has been thoroughly evaluated and is now recommended as a first-line diagnostic approach for clinically suspected genetic disorders. However, clinical application of array-CGH in postnatal evaluation raises the debate of whether array-CGH will replace traditional cytogenetics in the near future and whether there is still a role for karyotyping and FISH. In this article, we therefore review the current status of array-based technology use for postnatal diagnosis and predict that it will replace standard cytogenetics as a first-line test for clinical evaluation in these population groups.

  18. Automated prostate cancer diagnosis and Gleason grading of tissue microarrays

    Science.gov (United States)

    Tabesh, Ali; Kumar, Vinay P.; Pang, Ho-Yuen; Verbel, David; Kotsianti, Angeliki; Teverovskiy, Mikhail; Saidi, Olivier

    2005-04-01

    We present the results on the development of an automated system for prostate cancer diagnosis and Gleason grading. Images of representative areas of the original Hematoxylin-and-Eosin (H&E)-stained tissue retrieved from each patient, either from a tissue microarray (TMA) core or whole section, were captured and analyzed. The image sets consisted of 367 and 268 color images for the diagnosis and Gleason grading problems, respectively. In diagnosis, the goal is to classify a tissue image into tumor versus non-tumor classes. In Gleason grading, which characterizes tumor aggressiveness, the objective is to classify a tissue image as being from either a low- or high-grade tumor. Several feature sets were computed from the image. The feature sets considered were: (i) color channel histograms, (ii) fractal dimension features, (iii) fractal code features, (iv) wavelet features, and (v) color, shape and texture features computed using Aureon Biosciences' MAGIC system. The linear and quadratic Gaussian classifiers together with a greedy search feature selection algorithm were used. For cancer diagnosis, a classification accuracy of 94.5% was obtained on an independent test set. For Gleason grading, the achieved accuracy of classification into low- and high-grade classes of an independent test set was 77.6%.

  19. Glycan microarray analysis of Candida glabrata adhesin ligand specificity.

    Science.gov (United States)

    Zupancic, Margaret L; Frieman, Matthew; Smith, David; Alvarez, Richard A; Cummings, Richard D; Cormack, Brendan P

    2008-05-01

    The Candida glabrata genome encodes at least 23 members of the EPA (epithelial adhesin) family responsible for mediating adherence to host cells. To better understand the mechanism by which the Epa proteins contribute to pathogenesis, we have used glycan microarray analysis to characterize their carbohydrate-binding specificities. Using Saccharomyces cerevisiae strains surface-expressing the N-terminal ligand-binding domain of the Epa proteins, we found that the three Epa family members functionally identified as adhesins in Candida glabrata (Epa1, Epa6 and Epa7) bind to ligands containing a terminal galactose residue. However, the specificity of the three proteins for glycans within this class varies, with Epa6 having a broader specificity range than Epa1 or Epa7. This result is intriguing given the close homology between Epa6 and Epa7, which are 92% identical at the amino acid level. We have mapped a five-amino-acid region within the N-terminal ligand-binding domain that accounts for the difference in specificity of Epa6 and Epa7 and show that these residues contribute to adherence to both epithelial and endothelial cell lines in vitro.

  20. 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.

  1. Fine-scaled human genetic structure revealed by SNP microarrays.

    Science.gov (United States)

    Xing, Jinchuan; Watkins, W Scott; Witherspoon, David J; Zhang, Yuhua; Guthery, Stephen L; Thara, Rangaswamy; Mowry, Bryan J; Bulayeva, Kazima; Weiss, Robert B; Jorde, Lynn B

    2009-05-01

    We report an analysis of more than 240,000 loci genotyped using the Affymetrix SNP microarray in 554 individuals from 27 worldwide populations in Africa, Asia, and Europe. To provide a more extensive and complete sampling of human genetic variation, we have included caste and tribal samples from two states in South India, Daghestanis from eastern Europe, and the Iban from Malaysia. Consistent with observations made by Charles Darwin, our results highlight shared variation among human populations and demonstrate that much genetic variation is geographically continuous. At the same time, principal components analyses reveal discernible genetic differentiation among almost all identified populations in our sample, and in most cases, individuals can be clearly assigned to defined populations on the basis of SNP genotypes. All individuals are accurately classified into continental groups using a model-based clustering algorithm, but between closely related populations, genetic and self-classifications conflict for some individuals. The 250K data permitted high-level resolution of genetic variation among Indian caste and tribal populations and between highland and lowland Daghestani populations. In particular, upper-caste individuals from Tamil Nadu and Andhra Pradesh form one defined group, lower-caste individuals from these two states form another, and the tribal Irula samples form a third. Our results emphasize the correlation of genetic and geographic distances and highlight other elements, including social factors that have contributed to population structure.

  2. Unscaled Bayes factors for multiple hypothesis testing in microarray experiments.

    Science.gov (United States)

    Bertolino, Francesco; Cabras, Stefano; Castellanos, Maria Eugenia; Racugno, Walter

    2015-12-01

    Multiple hypothesis testing collects a series of techniques usually based on p-values as a summary of the available evidence from many statistical tests. In hypothesis testing, under a Bayesian perspective, the evidence for a specified hypothesis against an alternative, conditionally on data, is given by the Bayes factor. In this study, we approach multiple hypothesis testing based on both Bayes factors and p-values, regarding multiple hypothesis testing as a multiple model selection problem. To obtain the Bayes factors we assume default priors that are typically improper. In this case, the Bayes factor is usually undetermined due to the ratio of prior pseudo-constants. We show that ignoring prior pseudo-constants leads to unscaled Bayes factor which do not invalidate the inferential procedure in multiple hypothesis testing, because they are used within a comparative scheme. In fact, using partial information from the p-values, we are able to approximate the sampling null distribution of the unscaled Bayes factor and use it within Efron's multiple testing procedure. The simulation study suggests that under normal sampling model and even with small sample sizes, our approach provides false positive and false negative proportions that are less than other common multiple hypothesis testing approaches based only on p-values. The proposed procedure is illustrated in two simulation studies, and the advantages of its use are showed in the analysis of two microarray experiments.

  3. Protein Microarray Characterization of the S-Nitrosoproteome*

    Science.gov (United States)

    Lee, Yun-Il; Giovinazzo, Daniel; Kang, Ho Chul; Lee, Yunjong; Jeong, Jun Seop; Doulias, Paschalis-Thomas; Xie, Zhi; Hu, Jianfei; Ghasemi, Mehdi; Ischiropoulos, Harry; Qian, Jiang; Zhu, Heng; Blackshaw, Seth; Dawson, Valina L.; Dawson, Ted M.

    2014-01-01

    Nitric oxide (NO) mediates a substantial part of its physiologic functions via S-nitrosylation, however the cellular substrates for NO-mediated S-nitrosylation are largely unknown. Here we describe the S-nitrosoproteome using a high-density protein microarray chip containing 16,368 unique human proteins. We identified 834 potentially S-nitrosylated human proteins. Using a unique and highly specific labeling and affinity capture of S-nitrosylated proteins, 138 cysteine residues on 131 peptides in 95 proteins were determined, defining critical sites of NO's actions. Of these cysteine residues 113 are novel sites of S-nitrosylation. A consensus sequence motif from these 834 proteins for S-nitrosylation was identified, suggesting that the residues flanking the S-nitrosylated cysteine are likely to be the critical determinant of whether the cysteine is S-nitrosylated. We identify eight ubiquitin E3 ligases, RNF10, RNF11, RNF41, RNF141, RNF181, RNF208, WWP2, and UBE3A, whose activities are modulated by S-nitrosylation, providing a unique regulatory mechanism of the ubiquitin proteasome system. These results define a new and extensive set of proteins that are susceptible to NO regulation via S-nitrosylation. Similar approaches could be used to identify other post-translational modification proteomes. PMID:24105792

  4. 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.

  5. New insights about host response to smallpox using microarray data

    Directory of Open Access Journals (Sweden)

    Dias Rodrigo A

    2007-08-01

    Full Text Available Abstract Background Smallpox is a lethal disease that was endemic in many parts of the world until eradicated by massive immunization. Due to its lethality, there are serious concerns about its use as a bioweapon. Here we analyze publicly available microarray data to further understand survival of smallpox infected macaques, using systems biology approaches. Our goal is to improve the knowledge about the progression of this disease. Results We used KEGG pathways annotations to define groups of genes (or modules, and subsequently compared them to macaque survival times. This technique provided additional insights about the host response to this disease, such as increased expression of the cytokines and ECM receptors in the individuals with higher survival times. These results could indicate that these gene groups could influence an effective response from the host to smallpox. Conclusion Macaques with higher survival times clearly express some specific pathways previously unidentified using regular gene-by-gene approaches. Our work also shows how third party analysis of public datasets can be important to support new hypotheses to relevant biological problems.

  6. Microarray Analysis of the Microflora of Root Caries in Elderly

    Science.gov (United States)

    Preza, Dorita; Olsen, Ingar; Willumsen, Tiril; Boches, Susan K.; Cotton, Sean L.; Grinde, Bjørn; Paster, Bruce J.

    2009-01-01

    Purpose The present study used a new 16S rRNA-based microarray with probes for over 300 bacterial species better define the bacterial profiles of healthy root surfaces and root caries (RC) in the elderly. Materials Supragingival plaque was collected from 20 healthy subjects (Controls) and from healthy and carious roots and carious dentin from 21 RC subjects (Patients). Results Collectively, 179 bacterial species and species groups were detected. A higher bacterial diversity was observed in the Controls as compared to Patients. Lactobacillus casei/paracasei/rhamnosus and Pseudoramibacter alactolyticus were notably associated with most root caries samples. Streptococcus mutans was detected more frequently in the infected dentin than in the other samples, but the difference was not significant. Actinomyces were found more frequently in Controls. Conclusion Actinomyces and S. mutans may play a limited role as pathogens of RC. The results from this study were in agreement with those of our previous study based on 16S rRNA gene sequencing with 72% of the species being detected with both methods. PMID:19039610

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

    Science.gov (United States)

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

    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 greater than or equal to 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 RTPCR test, which validated 11 genes, namely, CIDEC, PID1, LYRM1, ADD1, PPAR?2, 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.

  8. 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.

  9. Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis

    Directory of Open Access Journals (Sweden)

    Xi Wang

    2015-05-01

    Full Text Available Kashin-Beck Disease (KBD is an endemic osteochondropathy with an unknown pathogenesis. Diagnosis of KBD is effective only in advanced cases, which eliminates the possibility of early treatment and leads to an inevitable exacerbation of symptoms. Therefore, we aim to identify an accurate blood-based gene signature for the detection of KBD. Previously published gene expression profile data on cartilage and peripheral blood mononuclear cells (PBMCs from adults with KBD were compared to select potential target genes. Microarray analysis was conducted to evaluate the expression of the target genes in a cohort of 100 KBD patients and 100 healthy controls. A gene expression signature was identified using a training set, which was subsequently validated using an independent test set with a minimum redundancy maximum relevance (mRMR algorithm and support vector machine (SVM algorithm. Fifty unique genes were differentially expressed between KBD patients and healthy controls. A 20-gene signature was identified that distinguished between KBD patients and controls with 90% accuracy, 85% sensitivity, and 95% specificity. This study identified a 20-gene signature that accurately distinguishes between patients with KBD and controls using peripheral blood samples. These results promote the further development of blood-based genetic biomarkers for detection of KBD.

  10. 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.

  11. Stochastic Oscillations in Genetic Regulatory Networks: Application to Microarray Experiments

    Directory of Open Access Journals (Sweden)

    Rosenfeld Simon

    2006-01-01

    Full Text Available We analyze the stochastic dynamics of genetic regulatory networks using a system of nonlinear differential equations. The system of -functions is applied to capture the role of RNA polymerase in the transcription-translation mechanism. Using probabilistic properties of chemical rate equations, we derive a system of stochastic differential equations which are analytically tractable despite the high dimension of the regulatory network. Using stationary solutions of these equations, we explain the apparently paradoxical results of some recent time-course microarray experiments where mRNA transcription levels are found to only weakly correlate with the corresponding transcription rates. Combining analytical and simulation approaches, we determine the set of relationships between the size of the regulatory network, its structural complexity, chemical variability, and spectrum of oscillations. In particular, we show that temporal variability of chemical constituents may decrease while complexity of the network is increasing. This finding provides an insight into the nature of "functional determinism" of such an inherently stochastic system as genetic regulatory network.

  12. 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

  13. Inflammatory Pathways in Parkinson's Disease; A BNE Microarray Study.

    Science.gov (United States)

    Durrenberger, Pascal F; Grünblatt, Edna; Fernando, Francesca S; Monoranu, Camelia Maria; Evans, Jordan; Riederer, Peter; Reynolds, Richard; Dexter, David T

    2012-01-01

    The aetiology of Parkinson's disease (PD) is yet to be fully understood but it is becoming more and more evident that neuronal cell death may be multifactorial in essence. The main focus of PD research is to better understand substantia nigra homeostasis disruption, particularly in relation to the wide-spread deposition of the aberrant protein α-synuclein. Microarray technology contributed towards PD research with several studies to date and one gene, ALDH1A1 (Aldehyde dehydrogenase 1 family, member A1), consistently reappeared across studies including the present study, highlighting dopamine (DA) metabolism dysfunction resulting in oxidative stress and most probably leading to neuronal cell death. Neuronal cell death leads to increased inflammation through the activation of astrocytes and microglia. Using our dataset, we aimed to isolate some of these pathways so to offer potential novel neuroprotective therapeutic avenues. To that effect our study has focused on the upregulation of P2X7 (purinergic receptor P2X, ligand-gated ion channel, 7) receptor pathway (microglial activation) and on the NOS3 (nitric oxide synthase 3) pathway (angiogenesis). In summary, although the exact initiator of striatal DA neuronal cell death remains to be determined, based on our analysis, this event does not remain without consequence. Extracellular ATP and reactive astrocytes appear to be responsible for the activation of microglia which in turn release proinflammatory cytokines contributing further to the parkinsonian condition. In addition to tackling oxidative stress pathways we also suggest to reduce microglial and endothelial activation to support neuronal outgrowth.

  14. 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.

  15. 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.

  16. Reproducibility of gene expression across generations of Affymetrix microarrays

    Directory of Open Access Journals (Sweden)

    Haslett Judith N

    2003-06-01

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

  17. Microarray analysis of human epithelial cell responses to bacterial interaction.

    Science.gov (United States)

    Mans, Jeffrey J; Lamont, Richard J; Handfield, Martin

    2006-09-01

    Host-pathogen interactions are inherently complex and dynamic. The recent use of human microarrays has been invaluable to monitor the effects of various bacterial and viral pathogens upon host cell gene expression programs. This methodology has allowed the host response transcriptome of several cell lines to be studied on a global scale. To this point, the great majority of reports have focused on the response of immune cells, including macrophages and dendritic cells. These studies revealed that the immune response to microbial pathogens is tailored to different microbial challenges. Conversely, the paradigm for epithelial cells has--until recently--held that the epithelium mostly served as a relatively passive physical barrier to infection. It is now generally accepted that the epithelial barrier contributes more actively to signaling events in the immune response. In light of this shift, this review will compare transcriptional profiling data from studies that involved host-pathogen interactions occurring with epithelial cells. Experiments that defined both a common core response, as well as pathogen-specific host responses will be discussed. This review will also summarize the contributions that transcriptional profiling analysis has made to our understanding of bacterial physio-pathogensis of infection. This will include a discussion of how host transcriptional responses can be used to infer the function of virulence determinants from bacterial pathogens interacting with epithelial mucosa. In particular, we will expand upon the lessons that have been learned from gastro-intestinal and oral pathogens, as well as from members of the commensal flora.

  18. 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

  19. 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...

  20. 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...

  1. Semi-automatic video semantic annotation based on active learning

    Science.gov (United States)

    Song, Yan; Hua, Xian-Sheng; Dai, Li-Rong; Wang, Ren-Hua

    2005-07-01

    In this paper, we propose a novel semi-automatic annotation scheme for home videos based on active learning. It is well-known that there is a large gap between semantics and low-level features. To narrow down this gap, relevance feedback has been introduced in a number of literatures. Furthermore, to accelerate the convergence to the optimal result, several active learning schemes, in which the most informative samples are chosen to be annotated, have been proposed in literature instead of randomly selecting samples. In this paper, a representative active learning method is proposed, which local consistency of video content is effectively taken into consideration. The main idea is to exploit the global and local statistical characteristics of videos, and the temporal relationship between shots. The global model is trained on a smaller pre-labeled video dataset, and the local information is obtained online in the process of active learning, and will be used to adjust the initial global model adaptively. The experiment results show that the proposed active learning scheme has significantly improved the annotation performance compared with random selecting and common active learning method.

  2. Annotation-Based Whole Genomic Prediction and Selection

    DEFF Research Database (Denmark)

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

    Cπ 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...... groups. Genomic prediction has accuracy comparable to an own phenotype and use of genomic prediction can be cost effective by replacing feed intake measurement. Use of genomic annotation of SNPs and QTL information had no largely significant impact on predictive accuracy for the current traits but may...... 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...

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

    Directory of Open Access Journals (Sweden)

    Atefeh Pourjahed

    2013-12-01

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

  4. Putative psychosis genes in the prefrontal cortex: combined analysis of gene expression microarrays

    Directory of Open Access Journals (Sweden)

    Yolken Robert H

    2008-11-01

    Full Text Available Abstract Background Recent studies have shown similarities between schizophrenia and bipolar disorder in phenotypes and in genotypes, and those studies have contributed to an ongoing re-evaluation of the traditional dichotomy between schizophrenia and bipolar disorder. Bipolar disorder with psychotic features may be closely related to schizophrenia and therefore, psychosis may be an alternative phenotype compared to the traditional diagnosis categories. Methods We performed a cross-study analysis of 7 gene expression microarrays that include both psychosis and non-psychosis subjects. These studies include over 400 microarray samples (163 individual subjects on 3 different Affymetrix microarray platforms. Results We found that 110 transcripts are differentially regulated (p Conclusion This study demonstrates the advantages of cross-study analysis in detecting consensus changes in gene expression across multiple microarray studies. Differential gene expression between individuals with and without psychosis suggests that psychosis may be a useful phenotypic variable to complement the traditional diagnosis categories.

  5. Assessing the reliability of amplified RNA used in microarrays: a DUMB table approach.

    Science.gov (United States)

    Bearden, Edward D; Simpson, Pippa M; Peterson, Charlotte A; Beggs, Marjorie L

    2006-01-01

    A certain minimal amount of RNA from biological samples is necessary to perform a microarray experiment with suitable replication. In some cases, the amount of RNA available is insufficient, necessitating RNA amplification prior to target synthesis. However, there is some uncertainty about the reliability of targets that have been generated from amplified RNA, because of nonlinearity and preferential amplification. This current work develops a straightforward strategy to assess the reliability of microarray data obtained from amplified RNA. The tabular method we developed, which utilises a Down-Up-Missing-Below (DUMB) classification scheme, shows that microarrays generated with amplified RNA targets are reliable within constraints. There was an increase in false negatives because of the need for increased filtering. Furthermore, this analysis method is generic and can be broadly applied to evaluate all microarray data. A copy of the Microsoft Excel spreadsheet is available upon request from Edward Bearden.

  6. 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

  7. FPGA based system for automatic cDNA microarray image processing.

    Science.gov (United States)

    Belean, Bogdan; Borda, Monica; Le Gal, Bertrand; Terebes, Romulus

    2012-07-01

    Automation is an open subject in DNA microarray image processing, aiming reliable gene expression estimation. The paper presents a novel shock filter based approach for automatic microarray grid alignment. The proposed method brings up significantly reduced computational complexity compared to state of the art approaches, while similar results in terms of accuracy are achieved. Based on this approach, we also propose an FPGA based system for microarray image analysis that eliminates the shortcomings of existing software platforms: user intervention, increased computational time and cost. Our system includes application-specific architectures which involve algorithm parallelization, aiming fast and automated cDNA microarray image processing. The proposed automated image processing chain is implemented both on a general purpose processor and using the developed hardware architectures as co-processors in a FPGA based system. The comparative results included in the last section show that an important gain in terms of computational time is obtained using hardware based implementations.

  8. Large-scale plasmonic microarrays for label-free high-throughput screening.

    Science.gov (United States)

    Chang, Tsung-Yao; Huang, Min; Yanik, Ahmet Ali; Tsai, Hsin-Yu; Shi, Peng; Aksu, Serap; Yanik, Mehmet Fatih; Altug, Hatice

    2011-11-07

    Microarrays allowing simultaneous analysis of thousands of parameters can significantly accelerate screening of large libraries of pharmaceutical compounds and biomolecular interactions. For large-scale studies on diverse biomedical samples, reliable, label-free, and high-content microarrays are needed. In this work, using large-area plasmonic nanohole arrays, we demonstrate for the first time a large-scale label-free microarray technology with over one million sensors on a single microscope slide. A dual-color filter imaging method is introduced to dramatically increase the accuracy, reliability, and signal-to-noise ratio of the sensors in a highly multiplexed manner. We used our technology to quantitatively measure protein-protein interactions. Our platform, which is highly compatible with the current microarray scanning systems can enable a powerful screening technology and facilitate diagnosis and treatment of diseases.

  9. Microarray-Based Phospho-Proteomic Profiling of Complex Biological Systems

    Directory of Open Access Journals (Sweden)

    C. Rory Goodwin

    2016-04-01

    Full Text Available Protein microarray technology has been successfully used for identifying substrates of purified activated kinases. We used protein microarrays to globally interrogate the effects of PTEN and Akt activity on the phospho-kinome of in vitro and in vivo glioma models and validated results in clinical pathological specimens. Whole cell lysates extracted from tumor samples can be applied to human kinome chip microarrays to profile the global kinase phosphorylation patterns in a high-throughput manner and identify novel substrates inherent to the tumor cell and the interactions with tumor microenvironment. Our findings identify a novel microarray-based method for assessing intracellular signaling events applicable to human oncogenesis and other pathophysiologic states.

  10. Reconfiguration-based implementation of SVM classifier on FPGA for Classifying Microarray data.

    Science.gov (United States)

    Hussain, Hanaa M; Benkrid, Khaled; Seker, Huseyin

    2013-01-01

    Classifying Microarray data, which are of high dimensional nature, requires high computational power. Support Vector Machines-based classifier (SVM) is among the most common and successful classifiers used in the analysis of Microarray data but also requires high computational power due to its complex mathematical architecture. Implementing SVM on hardware exploits the parallelism available within the algorithm kernels to accelerate the classification of Microarray data. In this work, a flexible, dynamically and partially reconfigurable implementation of the SVM classifier on Field Programmable Gate Array (FPGA) is presented. The SVM architecture achieved up to 85× speed-up over equivalent general purpose processor (GPP) showing the capability of FPGAs in enhancing the performance of SVM-based analysis of Microarray data as well as future bioinformatics applications.

  11. 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.

  12. 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.

  13. 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

  14. Microarray analysis of p-anisaldehyde-induced transcriptome of Saccharomyces cerevisiae.

    Science.gov (United States)

    Yu, Lu; Guo, Na; Yang, Yi; Wu, Xiuping; Meng, Rizeng; Fan, Junwen; Ge, Fa; Wang, Xuelin; Liu, Jingbo; Deng, Xuming

    2010-03-01

    p-Anisaldehyde (4-methoxybenzaldehyde), an extract from Pimpinella anisum L. seeds, is a potential novel preservative. To reveal the possible action mechanism of p-anisaldehyde against microorganisms, yeast-based commercial oligonucleotide microarrays were used to analyze the genome-wide transcriptional changes in response to p-anisaldehyde. Quantitative real-time RT-PCR was performed for selected genes to verify the microarray results. We interpreted our microarray data with the clustering tool, T-profiler. Analysis of microarray data revealed that p-anisaldehyde induced the expression of genes related to sulphur assimilation, aromatic aldehydes metabolism, and secondary metabolism, which demonstrated that the addition of p-anisaldehyde may influence the normal metabolism of aromatic aldehydes. This genome-wide transcriptomics approach revealed first insights into the response of Saccharomyces cerevisiae (S. cerevisiae) to p-anisaldehyde challenge.

  15. 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

  16. SPERM RNA AMPLIFICATION FOR GENE EXPRESSION PROFILING BY DNA MICROARRAY TECHNOLOGY

    Science.gov (United States)

    Sperm RNA Amplification for Gene Expression Profiling by DNA Microarray TechnologyHongzu Ren, Kary E. Thompson, Judith E. Schmid and David J. Dix, Reproductive Toxicology Division, NHEERL, Office of Research and Development, US Environmental Protection Agency, Research Triang...

  17. 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

  18. 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.

  19. Microarray analysis of genes affected by salt stress in tomato | Zhou ...

    African Journals Online (AJOL)

    Microarray analysis of genes affected by salt stress in tomato. ... African Journal of Environmental Science and Technology ... key enzyme genes in the metabolic pathways of carbohydrates, amino acids, and fatty acids, were also affected by ...

  20. Constructing the gene regulation-level representation of microarray data for cancer classification.

    Science.gov (United States)

    Wong, Hau-San; Wang, Hong-Qiang

    2008-02-01

    In this paper, we propose a regulation-level representation for microarray data and optimize it using genetic algorithms (GAs) for cancer classification. Compared with the traditional expression-level features, this representation can greatly reduce the dimensionality of microarray data and accommodate noise and variability such that many statistical machine-learning methods now become applicable and efficient for cancer classification. Experimental results on real-world microarray datasets show that the regulation-level representation can consistently converge at a solution with three regulation levels. This verifies the existence of the three regulation levels (up-regulation, down-regulation and non-significant regulation) associated with a particular biological phenotype. The ternary regulation-level representation not only improves the cancer classification capability but also facilitates the visualization of microarray data.

  1. 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.

  2. Statistical tests for differential expression in cDNA microarray experiments

    OpenAIRE

    Cui, Xiangqin; Churchill, Gary A.

    2003-01-01

    Extracting biological information from microarray data requires appropriate statistical methods. The simplest statistical method for detecting differential expression is the t test, which can be used to compare two conditions when there is replication of samples. With more than two conditions, analysis of variance (ANOVA) can be used, and the mixed ANOVA model is a general and powerful approach for microarray experiments with multiple factors and/or several sources of variation.

  3. Ontology-based, Tissue MicroArray oriented, image centered tissue bank

    OpenAIRE

    Viti Federica; Merelli Ivan; Caprera Andrea; Lazzari Barbara; Stella Alessandra; Milanesi Luciano

    2008-01-01

    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 util...

  4. Design of oligonucleotides for microarrays and perspectives for design of multi-transcriptome arrays

    DEFF Research Database (Denmark)

    Nielsen, Henrik Bjørn; Wernersson, Rasmus; Knudsen, Steen

    2003-01-01

    Optimal design of oligonucleotides for microarrays involves tedious and laborious work evaluating potential oligonucleotides relative to a series of parameters. The currently available tools for this purpose are limited in their flexibility and do not present the oligonucleotide designer with an ......Optimal design of oligonucleotides for microarrays involves tedious and laborious work evaluating potential oligonucleotides relative to a series of parameters. The currently available tools for this purpose are limited in their flexibility and do not present the oligonucleotide designer...

  5. The use of chromosomal microarray for prenatal diagnosis.

    Science.gov (United States)

    Dugoff, Lorraine; Norton, Mary E; Kuller, Jeffrey A

    2016-10-01

    Chromosomal microarray analysis is a high-resolution, whole-genome technique used to identify chromosomal abnormalities, including those detected by conventional cytogenetic techniques, as well as small submicroscopic deletions and duplications referred to as copy number variants. Because chromosomal microarray analysis has a greater resolution than conventional karyotyping, it can detect deletions and duplications down to a 50- to 100-kb level. The purpose of this document is to discuss the technique, advantages, and disadvantages of chromosomal microarray analysis and its indications and limitations. We recommend the following: (1) that chromosomal microarray analysis be offered when genetic analysis is performed in cases with fetal structural anomalies and/or stillbirth and replaces the need for fetal karyotype in these cases (GRADE 1A); (2) that providers discuss the benefits and limitations of chromosomal microarray analysis and conventional karyotype with patients who are considering amniocentesis and chorionic villus sampling (CVS), and that both options should be available to women who choose to undergo diagnostic testing (GRADE 1B); (3) that pre- and posttest counseling should be performed by trained genetic counselors, geneticists, or other providers with expertise in the complexities of interpreting chromosomal microarray analysis results (Best Practice); (4) that patients be informed that chromosomal microarray analysis does not detect every genetic disease or syndrome and specifically does not detect autosomal-recessive disorders associated with single gene point mutations, as well as that chromosomal microarray analysis can detect consanguinity and nonpaternity in some cases (Best Practice); (5) that patients in whom a fetal variant of uncertain significance is detected by prenatal diagnosis receive counseling from experts who have access to databases that provide updated information concerning genotype-phenotype correlations (Best Practice

  6. 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.

  7. A DNA Microarray-Based Assay to Detect Dual Infection with Two Dengue Virus Serotypes

    OpenAIRE

    Alvaro Díaz-Badillo; María de Lourdes Muñoz; Gerardo Perez-Ramirez; Victor Altuzar; Juan Burgueño; Mendoza-Alvarez, Julio G.; Martínez-Muñoz, Jorge P.; Alejandro Cisneros; Joel Navarrete-Espinosa; Feliciano Sanchez-Sinencio

    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 hybrid...

  8. Discovery and analysis of inflammatory disease-related genes using cDNA microarrays

    OpenAIRE

    1997-01-01

    cDNA microarray technology is used to profile complex diseases and discover novel disease-related genes. In inflammatory disease such as rheumatoid arthritis, expression patterns of diverse cell types contribute to the pathology. We have monitored gene expression in this disease state with a microarray of selected human genes of probable significance in inflammation as well as with genes expressed in peripheral human blood cells. Messenger RNA from cultured macrophages, chondrocyte cell lines...

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

    DEFF Research Database (Denmark)

    Eklund, Aron Charles; Szallasi, Zoltan Imre

    2008-01-01

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

  10. Differentially expressed genes identified by cross-species microarray in the blind cavefish Astyanax

    OpenAIRE

    2009-01-01

    Changes in gene expression were examined by microarray analysis during development of the eyed surface dwelling (surface fish) and blind cave-dwelling (cavefish) forms of the teleost Astyanax mexicanus De Filippi, 1853. The cross-species microarray used surface and cavefish RNA hybridized to a DNA chip prepared from a closely related species, the zebrafish Danio rerio Hamilton, 1822. We identified a total of 67 differentially expressed probe sets at three days post-fertilization: six upregula...

  11. Learning from microarray interlaboratory studies: measures of precision for gene expression

    Directory of Open Access Journals (Sweden)

    Reid Laura H

    2009-04-01

    Full Text Available Abstract Background The ability to demonstrate the reproducibility of gene expression microarray results is a critical consideration for the use of microarray technology in clinical applications. While studies have asserted that microarray data can be "highly reproducible" under given conditions, there is little ability to quantitatively compare amongst the various metrics and terminology used to characterize and express measurement performance. Use of standardized conceptual tools can greatly facilitate communication among the user, developer, and regulator stakeholders of the microarray community. While shaped by less highly multiplexed systems, measurement science (metrology is devoted to establishing a coherent and internationally recognized vocabulary and quantitative practice for the characterization of measurement processes. Results The two independent aspects of the metrological concept of "accuracy" are "trueness" (closeness of a measurement to an accepted reference value and "precision" (the closeness of measurement results to each other. A carefully designed collaborative study enables estimation of a variety of gene expression measurement precision metrics: repeatability, several flavors of intermediate precision, and reproducibility. The three 2004 Expression Analysis Pilot Proficiency Test collaborative studies, each with 13 to 16 participants, provide triplicate microarray measurements on each of two reference RNA pools. Using and modestly extending the consensus ISO 5725 documentary standard, we evaluate the metrological precision figures of merit for individual microarray signal measurement, building from calculations appropriate to single measurement processes, such as technical replicate expression values for individual probes on a microarray, to the estimation and display of precision functions representing all of the probes in a given platform. Conclusion With only modest extensions, the established metrological framework

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

    Directory of Open Access Journals (Sweden)

    Lifeng Liang

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

  13. An experimental evaluation of a loop versus a reference design for two-channel microarrays

    OpenAIRE

    2005-01-01

    http://bioinformatics.oxfordjournals.org/cgi/content/abstract/21/4/492 Motivation: Despite theoretical arguments that socalled \\loop designs" of two-channel DNA microarray experiments are more e cient, biologists keep on using \\reference designs". We describe two sets of microarray experiments with RNA from two di erent biological systems (TPA-stimulated mammalian cells and Streptomyces coelicor). In each case, both a loop and a reference design were performed using the same RNA preparatio...

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

    Directory of Open Access Journals (Sweden)

    Bernie J Daigle

    2010-03-01

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

  15. MAD: a suite of tools for microarray data management and processing.

    Science.gov (United States)

    Liao, B; Hale, W; Epstein, C B; Butow, R A; Garner, H R

    2000-10-01

    Microarray data management and processing (MAD) is a set of Windows integrated software for microarray analysis. It consists of a relational database for data storage with many user-interfaces for data manipulation, several text file parsers and Microsoft Excel macros for automation of data processing, and a generator to produce text files that are ready for cluster analysis. Executable is available free of charge on http://pompous.swmed.edu. The source code is also available upon request.

  16. Hierarchical information representation and efficient classification of gene expression microarray data

    OpenAIRE

    Bosio, Mattia

    2014-01-01

    In the field of computational biology, microarryas are used to measure the activity of thousands of genes at once and create a global picture of cellular function. Microarrays allow scientists to analyze expression of many genes in a single experiment quickly and eficiently. Even if microarrays are a consolidated research technology nowadays and the trends in high-throughput data analysis are shifting towards new technologies like Next Generation Sequencing (NGS), an optimum method for sample...

  17. Microarray screening of Guillain-Barré syndrome sera for antibodies to glycolipid complexes

    OpenAIRE

    Halstead, Susan K.; Kalna, Gabriela; Islam, Mohammad B.; Jahan, Israt; Mohammad, Quazi D.; Bart C Jacobs; Endtz, Hubert P.; Islam, Zhahirul; Willison, Hugh J.

    2016-01-01

    Objective: To characterize the patterns of autoantibodies to glycolipid complexes in a large cohort of Guillain-Barré syndrome (GBS) and control samples collected in Bangladesh using a newly developed microarray technique.\\ud \\ud Methods: Twelve commonly studied glycolipids and lipids, plus their 66 possible heteromeric complexes, totaling 78 antigens, were applied to polyvinylidene fluoride–coated slides using a microarray printer. Arrays were probed with 266 GBS and 579 control sera (2 μL p...

  18. Microarray screening of Guillain-Barré syndrome sera for antibodies to glycolipid complexes

    OpenAIRE

    Halstead, Susan K.; Kalna, Gabriela; Islam, Mohammad B.; Jahan, Israt; Mohammad, Quazi D.; Bart C Jacobs; Endtz, Hubert P.; Islam, Zhahirul; Willison, Hugh J.

    2016-01-01

    Objective: To characterize the patterns of autoantibodies to glycolipid complexes in a large cohort of Guillain-Barré syndrome (GBS) and control samples collected in Bangladesh using a newly developed microarray technique. Methods: Twelve commonly studied glycolipids and lipids, plus their 66 possible heteromeric complexes, totaling 78 antigens, were applied to polyvinylidene fluoride–coated slides using a microarray printer. Arrays were probed with 266 GBS and 579 control sera (2 μL per seru...

  19. Development and application of antibody microarray for white spot syndrome virus detection in shrimp

    Institute of Scientific and Technical Information of China (English)

    XU Xiaoli; SHENG Xiuzhen; ZHAN Wenbin

    2011-01-01

    Detecting white spot syndrome virus (WSSV) in shrimp in high efficiency and veracity is important for disease prevention in aquaculture.Antibody-based microarray is a novel proteomic technology that can meet the requirements.In this study,we developed an antibody microarray for WSSV-detection in a specific and parallel way at multiple samples.First,seven slides each with different modifications were characterized by atomic force microscope,and were compared in the efficiency of immobilizing proteins.Of the seven,3-dimensional structured agarose gel-modified slides were chosen appropriate for the microarray for having higher signal value and superior spot size.A purified rabbit anti-WSSV antibody was arrayed as the capture antibody of the microarray on the agarose gel-modified slides,and then the microarray slides were incubated in the tissue homogenate of sampled shrimp and the antibody-antigen complex was detected by Cy3-conjugated anti-WSSV monoclonal antibody.The results were measured by a laser chipscanner and analyzed with software.To obtain satisfied fluorescence signal intensity,optimal conditions were searched.The detection limit of the antibody microarray for WSSV is 0.62 μg/mL,with a proven long shelf life for 6 months at 4℃ or 8 months at -20℃.Furthermore,concordance between antibody microarray and traditional indirect ELISA reached 100% for WSSV detection.These results suggest that the antibody microarray could be served as an effective tool for diagnostic and epidemiological studies of WSSV.

  20. 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.

  1. Discovery of a TNF-α Antagonist Using Chondroitin Sulfate Microarrays

    OpenAIRE

    Tully, Sarah E.; Rawat, Manish; Hsieh-Wilson, Linda C.

    2006-01-01

    We report the first example of synthetic chondroitin sulfate (CS) microarrays to rapidly identify glycosaminoglycan−protein interactions and probe the specificity of proteins for distinct sulfation sequences. Using the microarrays, we identify a novel interaction between CS and TNF-α, a proinflammatory cytokine involved in rheumatoid arthritis, Crohn's disease, and psoriasis. Moreover, we demonstrate that CS-E tetrasaccharides and polysaccharides enriched in the CS-E sulfation motif can inhib...

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

    Science.gov (United States)

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

    2012-01-01

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

  3. 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.

  4. 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.

  5. A versatile protein microarray platform enabling antibody profiling against denatured proteins.

    Science.gov (United States)

    Wang, Jie; Barker, Kristi; Steel, Jason; Park, Jin; Saul, Justin; Festa, Fernanda; Wallstrom, Garrick; Yu, Xiaobo; Bian, Xiaofang; Anderson, Karen S; Figueroa, Jonine D; LaBaer, Joshua; Qiu, Ji

    2013-06-01

    We aim to develop a protein microarray platform capable of presenting both natural and denatured forms of proteins for antibody biomarker discovery. We will further optimize plasma screening protocols to improve detection. We developed a new covalent capture protein microarray chemistry using HaloTag fusion proteins and ligand. To enhance protein yield, we used HeLa cell lysate as an in vitro transcription translation (IVTT) system. Escherichia coli lysates were added to the plasma blocking buffer to reduce nonspecific background. These protein microarrays were probed with plasma samples and autoantibody responses were quantified and compared with or without denaturing buffer treatment. We demonstrated that protein microarrays using the covalent attachment chemistry endured denaturing conditions. Blocking with E. coli lysates greatly reduced the background signals and expression with IVTT based on HeLa cell lysates significantly improved the antibody signals on protein microarrays probed with plasma samples. Plasma samples probed on denatured protein arrays produced autoantibody profiles distinct from those probed on natively displayed proteins. This versatile protein microarray platform allows the display of both natural and denatured proteins, offers a new dimension to search for disease-specific antibodies, broadens the repertoire of potential biomarkers, and will potentially yield clinical diagnostics with greater performance. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. 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.

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

    Science.gov (United States)

    Yang, Jianji; Cohen, Aaron; Hersh, William

    2009-02-05

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

  8. 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.

  9. ArrayIDer: automated structural re-annotation pipeline for DNA microarrays

    Directory of Open Access Journals (Sweden)

    McCarthy Fiona M

    2009-01-01

    Full Text Available Abstract Background Systems biology modeling from microarray data requires the most contemporary structural and functional array annotation. However, microarray annotations, especially for non-commercial, non-traditional biomedical model organisms, are often dated. In addition, most microarray analysis tools do not readily accept EST clone names, which are abundantly represented on arrays. Manual re-annotation of microarrays is impracticable and so we developed a computational re-annotation tool (ArrayIDer to retrieve the most recent accession mapping files from public databases based on EST clone names or accessions and rapidly generate database accessions for entire microarrays. Results We utilized the Fred Hutchinson Cancer Research Centre 13K chicken cDNA array – a widely-used non-commercial chicken microarray – to demonstrate the principle that ArrayIDer could markedly improve annotation. We structurally re-annotated 55% of the entire array. Moreover, we decreased non-chicken functional annotations by 2 fold. One beneficial consequence of our re-annotation was to identify 290 pseudogenes, of which 66 were previously incorrectly annotated. Conclusion ArrayIDer allows rapid automated structural re-annotation of entire arrays and provides multiple accession types for use in subsequent functional analysis. This information is especially valuable for systems biology modeling in the non-traditional biomedical model organisms.

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

    Science.gov (United States)

    2012-01-01

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

  11. CARMA: A platform for analyzing microarray datasets that incorporate replicate measures

    Directory of Open Access Journals (Sweden)

    Brooks Heddwen L

    2006-03-01

    Full Text Available Abstract Background The incorporation of statistical models that account for experimental variability provides a necessary framework for the interpretation of microarray data. A robust experimental design coupled with an analysis of variance (ANOVA incorporating a model that accounts for known sources of experimental variability can significantly improve the determination of differences in gene expression and estimations of their significance. Results To realize the full benefits of performing analysis of variance on microarray data we have developed CARMA, a microarray analysis platform that reads data files generated by most microarray image processing software packages, performs ANOVA using a user-defined linear model, and produces easily interpretable graphical and numeric results. No pre-processing of the data is required and user-specified parameters control most aspects of the analysis including statistical significance criterion. The software also performs location and intensity dependent lowess normalization, automatic outlier detection and removal, and accommodates missing data. Conclusion CARMA provides a clear quantitative and statistical characterization of each measured gene that can be used to assess marginally acceptable measures and improve confidence in the interpretation of microarray results. Overall, applying CARMA to microarray datasets incorporating repeated measures effectively reduces the number of gene incorrectly identified as differentially expressed and results in a more robust and reliable analysis.

  12. 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.

  13. 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.

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

    Science.gov (United States)

    Morris, Brandon E. L.

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

  15. Gene ordering in partitive clustering using microarray expressions.

    Science.gov (United States)

    Ray, Shubhra Sankar; Bandyopadhyay, Sanghamitra; Pal, Sankar K

    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.

  16. 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.

  17. Differential analysis for high density tiling microarray data

    Directory of Open Access Journals (Sweden)

    Kapranov Philipp

    2007-09-01

    Full Text Available Abstract Background High density oligonucleotide tiling arrays are an effective and powerful platform for conducting unbiased genome-wide studies. The ab initio probe selection method employed in tiling arrays is unbiased, and thus ensures consistent sampling across coding and non-coding regions of the genome. These arrays are being increasingly used to study the associated processes of transcription, transcription factor binding, chromatin structure and their association. Studies of differential expression and/or regulation provide critical insight into the mechanics of transcription and regulation that occurs during the developmental program of a cell. The time-course experiment, which comprises an in-vivo system and the proposed analyses, is used to determine if annotated and un-annotated portions of genome manifest coordinated differential response to the induced developmental program. Results We have proposed a novel approach, based on a piece-wise function – to analyze genome-wide differential response. This enables segmentation of the response based on protein-coding and non-coding regions; for genes the methodology also partitions differential response with a 5' versus 3' versus intra-genic bias. Conclusion The algorithm built upon the framework of Significance Analysis of Microarrays, uses a generalized logic to define regions/patterns of coordinated differential change. By not adhering to the gene-centric paradigm, discordant differential expression patterns between exons and introns have been identified at a FDR of less than 12 percent. A co-localization of differential binding between RNA Polymerase II and tetra-acetylated histone has been quantified at a p-value -13. The prototype R code has been made available as supplementary material [see Additional file 1]. Additional file 1 gsam_prototypercode.zip. File archive comprising of prototype R code for gSAM implementation including readme and examples. Click here for file

  18. Differential analysis for high density tiling microarray data.

    Science.gov (United States)

    Ghosh, Srinka; Hirsch, Heather A; Sekinger, Edward A; Kapranov, Philipp; Struhl, Kevin; Gingeras, Thomas R

    2007-09-24

    High density oligonucleotide tiling arrays are an effective and powerful platform for conducting unbiased genome-wide studies. The ab initio probe selection method employed in tiling arrays is unbiased, and thus ensures consistent sampling across coding and non-coding regions of the genome. These arrays are being increasingly used to study the associated processes of transcription, transcription factor binding, chromatin structure and their association. Studies of differential expression and/or regulation provide critical insight into the mechanics of transcription and regulation that occurs during the developmental program of a cell. The time-course experiment, which comprises an in-vivo system and the proposed analyses, is used to determine if annotated and un-annotated portions of genome manifest coordinated differential response to the induced developmental program. We have proposed a novel approach, based on a piece-wise function - to analyze genome-wide differential response. This enables segmentation of the response based on protein-coding and non-coding regions; for genes the methodology also partitions differential response with a 5' versus 3' versus intra-genic bias. The algorithm built upon the framework of Significance Analysis of Microarrays, uses a generalized logic to define regions/patterns of coordinated differential change. By not adhering to the gene-centric paradigm, discordant differential expression patterns between exons and introns have been identified at a FDR of less than 12 percent. A co-localization of differential binding between RNA Polymerase II and tetra-acetylated histone has been quantified at a p-value < 0.003; it is most significant at the 5' end of genes, at a p-value < 10-13. The prototype R code has been made available as supplementary material [see Additional file 1].

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

    Directory of Open Access Journals (Sweden)

    Tang Zuojian

    2009-10-01

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

  20. DNA microarray-based typing of Streptococcus agalactiae isolates.

    Science.gov (United States)

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

    2014-11-01

    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 alleles of the alpha-like protein or capsule types, vary independently of each other, and they also vary independently from the affiliation to their multilocus sequence typing (MLST)-defined sequence types. Thus, it is not possible to assign isolates to sequence types based on the identification of a single distinct marker, such as a capsule type or alp allele. This suggests the occurrence of frequent genomic recombination. For array-based typing, a set of 11 markers (bac, alp, pil1 locus, pepS8, fbsB, capsule locus, hylB, abiG-I/-II plus Q8DZ34, pil2 locus, nss plus srr plus rogB2, and rgfC/A/D/B) was defined that provides a framework for splitting the tested 448 S. agalactiae isolates into 76 strains that clustered mainly according to MLST-defined clonal complexes. There was evidence for region- and host-specific differences in the population structure of S. agalactiae, as well as an overrepresentation of strains related to sequence type 17 among the invasive isolates. The arrays and typing scheme described here proved to be a convenient tool for genotyping large numbers of clinical/veterinary isolates and thus might help obtain insight into the epidemiology of S. agalactiae.

  1. Microarray gene expression analysis of uterosacral ligaments in uterine prolapse.

    Science.gov (United States)

    Ak, Handan; Zeybek, Burak; Atay, Sevcan; Askar, Niyazi; Akdemir, Ali; Aydin, Hikmet Hakan

    2016-11-01

    Pelvic organ prolapse (POP) is a major health problem that impairs the quality of life with a wide clinical spectrum. Since the uterosacral ligaments provide primary support for the uterus and the upper vagina, we hypothesize that the disruption of these ligaments may lead to a loss of support and eventually contribute to POP. In this study, we therefore investigated whether there are any differences in the transcription profile of uterosacral ligaments in patients with POP when compared to those of the control samples. Seventeen women with POP and 8 non-POP controls undergoing hysterectomy for benign conditions were included in the study. Affymetrix® Gene Chip microarrays (Human Hu 133 plus 2.0) were used for whole genome gene expression profiling analysis. There was 1 significantly down-regulated gene, NKX2-3 in patients with POP compared to the controls (p=4.28464e-013). KIF11 gene was found to be significantly down-regulated in patients with ≥3 deliveries compared to patients with <3 deliveries (p=0.0156237). UGT1A1 (p=2.43388e-005), SCARB1 (p=1.19001e-006) and NKX2-3 (p=2.17966e-013) genes were found to be significantly down-regulated in the premenopausal patients compared to the premenopausal controls. UGT1A1 gene was also found to be significantly down-regulated in the post menopausal patients compared to the postmenopausal controls (p=0.0005). This study provides evidence for a significant down-regulation of the genes that take role in cell cycle, proliferation and embryonic development along with cell adhesion process on the development of POP for the first time. Copyright © 2016 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

  2. Tissue microarrays: one size does not fit all

    Directory of Open Access Journals (Sweden)

    Krco Christopher J

    2010-07-01

    Full Text Available Abstract Background Although tissue microarrays (TMAs are commonly employed in clinical and basic-science research, there are no guidelines for evaluating the appropriateness of a TMA for a given biomarker and tumor type. Furthermore, TMA performance across multiple biomarkers has not been systematically explored. Methods A simulated TMA with between 1 and 10 cores was designed to study tumor expression of 6 biomarkers with varied expression patterns (B7-H1, B7-H3, survivin, Ki-67, CAIX, and IMP3 using 100 patients with clear cell renal cell carcinoma (RCC. We evaluated agreement between whole tissue section and TMA immunohistochemical biomarker quantification to assess how many TMA cores are necessary to adequately represent RCC whole tissue section expression. Additionally, we evaluated associations of whole tissue section and TMA expression with RCC-specific death. Results The number of simulated TMA cores necessary to adequately represent whole tissue section quantification is biomarker specific. Although 2-3 cores appeared adequate for B7-H3, Ki-67, CAIX, and IMP3, even as many as 10 cores resulted in poor agreement for B7-H1 and survivin compared to RCC whole tissue sections. While whole tissue section B7-H1 was significantly associated with RCC-specific death, no significant associations were detected using as many as 10 TMA cores, suggesting that TMAs can result in false-negative findings if the TMA is not optimally designed. Conclusions Prior to TMA analysis, the number of TMA cores necessary to accurately represent biomarker expression on whole tissue sections should be established as there is not a one-size-fits-all TMA. We illustrate the use of a simulated TMA as a cost-effective tool for this purpose.

  3. 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.

  4. 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

  5. Microarray meta-analysis database (M2DB: a uniformly pre-processed, quality controlled, and manually curated human clinical microarray database

    Directory of Open Access Journals (Sweden)

    Cheng Wei-Chung

    2010-08-01

    Full Text Available Abstract Background Over the past decade, gene expression microarray studies have greatly expanded our knowledge of genetic mechanisms of human diseases. Meta-analysis of substantial amounts of accumulated data, by integrating valuable information from multiple studies, is becoming more important in microarray research. However, collecting data of special interest from public microarray repositories often present major practical problems. Moreover, including low-quality data may significantly reduce meta-analysis efficiency. Results M2DB is a human curated microarray database designed for easy querying, based on clinical information and for interactive retrieval of either raw or uniformly pre-processed data, along with a set of quality-control metrics. The database contains more than 10,000 previously published Affymetrix GeneChip arrays, performed using human clinical specimens. M2DB allows online querying according to a flexible combination of five clinical annotations describing disease state and sampling location. These annotations were manually curated by controlled vocabularies, based on information obtained from GEO, ArrayExpress, and published papers. For array-based assessment control, the online query provides sets of QC metrics, generated using three available QC algorithms. Arrays with poor data quality can easily be excluded from the query interface. The query provides values from two algorithms for gene-based filtering, and raw data and three kinds of pre-processed data for downloading. Conclusion M2DB utilizes a user-friendly interface for QC parameters, sample clinical annotations, and data formats to help users obtain clinical metadata. This database provides a lower entry threshold and an integrated process of meta-analysis. We hope that this research will promote further evolution of microarray meta-analysis.

  6. 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

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

    Science.gov (United States)

    Kong, Xiangrong; Mas, Valeria; Archer, Kellie J

    2008-02-26

    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. 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. 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 reported to be relevant to renal diseases. Further study on the

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

    Science.gov (United States)

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

    2012-02-01

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

  9. MicroGen: a MIAME compliant web system for microarray experiment information and workflow management

    Directory of Open Access Journals (Sweden)

    Pinciroli Francesco

    2005-12-01

    Full Text Available Abstract Background Improvements of bio-nano-technologies and biomolecular techniques have led to increasing production of high-throughput experimental data. Spotted cDNA microarray is one of the most diffuse technologies, used in single research laboratories and in biotechnology service facilities. Although they are routinely performed, spotted microarray experiments are complex procedures entailing several experimental steps and actors with different technical skills and roles. During an experiment, involved actors, who can also be located in a distance, need to access and share specific experiment information according to their roles. Furthermore, complete information describing all experimental steps must be orderly collected to allow subsequent correct interpretation of experimental results. Results We developed MicroGen, a web system for managing information and workflow in the production pipeline of spotted microarray experiments. It is constituted of a core multi-database system able to store all data completely characterizing different spotted microarray experiments according to the Minimum Information About Microarray Experiments (MIAME standard, and of an intuitive and user-friendly web interface able to support the collaborative work required among multidisciplinary actors and roles involved in spotted microarray experiment production. MicroGen supports six types of user roles: the researcher who designs and requests the experiment, the spotting operator, the hybridisation operator, the image processing operator, the system administrator, and the generic public user who can access the unrestricted part of the system to get information about MicroGen services. Conclusion MicroGen represents a MIAME compliant information system that enables managing workflow and supporting collaborative work in spotted microarray experiment production.

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

    Science.gov (United States)

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

    2016-01-01

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

  11. [Modified method of constructing tissue microarray which contains keloid and normal skin].

    Science.gov (United States)

    Zhang, Zhenyu; Chen, Junjie; Cen, Ying; Zhao, Sha; Liao, Dianying; Gong, Jing

    2010-08-01

    To seek for a method of constructing the tissue microarray which contains keloid, skin around keloid, and normal skin. The specimens were gained from patients of voluntary donation between March and May 2009, including the tissues of keloid (27 cases), skin around keloid (13 cases), and normal skin (27 cases). The specimens were imbedded by paraffin as donor blocks. The traditional method of constructing the tissue microarray and section were modified according to the histological characteristics of the keloid and skin tissue and the experimental requirement. The tissue cores were drilled from donor blocks and attached securely on the adhesive platform which was prepared. The adhesive platform with tissue cores in situ was placed into an imbedding mold, which then was preheated briefly. Paraffin at approximately 70 degrees C was injected to fill the mold and then cooled to room temperature. Then HE staining, immunohistochemistry staining were performed and the results were observed by microscope. The constructed tissue microarray block contained 67 cores as designed and displayed smooth surface with no crack. All the cores distributed regularly, had no disintegration or manifest shift. HE staining of tissue microarray section showed that all cores had equal thickness, distinct layer, manifest contradistinction, well-defined edge, and consistent with original pathological diagnosis. Immunohistochemistry staining results demonstrated that all cores contained enough tissue dose to apply group comparison. However, in tissue microarray which was made as traditional method, many cores missed and a few cores shifted obviously. Applying modified method can successfully construct tissue microarray which is composed of keloid, skin around keloid, and normal skin. This tissue microarray will become an effective tool of researching the pathogenesis of keloid.

  12. 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.

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

    Science.gov (United States)

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

    2008-06-18

    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 effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson

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

    Directory of Open Access Journals (Sweden)

    Loraine Ann

    2008-06-01

    Full Text Available 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 effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. Results In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC, that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. Conclusion

  15. 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.

  16. Identifying genes relevant to specific biological conditions in time course microarray experiments.

    Science.gov (United States)

    Singh, Nitesh Kumar; Repsilber, Dirk; Liebscher, Volkmar; Taher, Leila; Fuellen, Georg

    2013-01-01

    Microarrays have been useful in understanding various biological processes by allowing the simultaneous study of the expression of thousands of genes. However, the analysis of microarray data is a challenging task. One of the key problems in microarray analysis is the classification of unknown expression profiles. Specifically, the often large number of non-informative genes on the microarray adversely affects the performance and efficiency of classification algorithms. Furthermore, the skewed ratio of sample to variable poses a risk of overfitting. Thus, in this context, feature selection methods become crucial to select relevant genes and, hence, improve classification accuracy. In this study, we investigated feature selection methods based on gene expression profiles and protein interactions. We found that in our setup, the addition of protein interaction information did not contribute to any significant improvement of the classification results. Furthermore, we developed a novel feature selection method that relies exclusively on observed gene expression changes in microarray experiments, which we call "relative Signal-to-Noise ratio" (rSNR). More precisely, the rSNR ranks genes based on their specificity to an experimental condition, by comparing intrinsic variation, i.e. variation in gene expression within an experimental condition, with extrinsic variation, i.e. variation in gene expression across experimental conditions. Genes with low variation within an experimental condition of interest and high variation across experimental conditions are ranked higher, and help in improving classification accuracy. We compared different feature selection methods on two time-series microarray datasets and one static microarray dataset. We found that the rSNR performed generally better than the other methods.

  17. A label-free, fluorescence based assay for microarray

    Science.gov (United States)

    Niu, Sanjun

    DNA chip technology has drawn tremendous attention since it emerged in the mid 90's as a method that expedites gene sequencing by over 100-fold. DNA chip, also called DNA microarray, is a combinatorial technology in which different single-stranded DNA (ssDNA) molecules of known sequences are immobilized at specific spots. The immobilized ssDNA strands are called probes. In application, the chip is exposed to a solution containing ssDNA of unknown sequence, called targets, which are labeled with fluorescent dyes. Due to specific molecular recognition among the base pairs in the DNA, the binding or hybridization occurs only when the probe and target sequences are complementary. The nucleotide sequence of the target is determined by imaging the fluorescence from the spots. The uncertainty of background in signal detection and statistical error in data analysis, primarily due to the error in the DNA amplification process and statistical distribution of the tags in the target DNA, have become the fundamental barriers in bringing the technology into application for clinical diagnostics. Furthermore, the dye and tagging process are expensive, making the cost of DNA chips inhibitive for clinical testing. These limitations and challenges make it difficult to implement DNA chip methods as a diagnostic tool in a pathology laboratory. The objective of this dissertation research is to provide an alternative approach that will address the above challenges. In this research, a label-free assay is designed and studied. Polystyrene (PS), a commonly used polymeric material, serves as the fluorescence agent. Probe ssDNA is covalently immobilized on polystyrene thin film that is supported by a reflecting substrate. When this chip is exposed to excitation light, fluorescence light intensity from PS is detected as the signal. Since the optical constants and conformations of ssDNA and dsDNA (double stranded DNA) are different, the measured fluorescence from PS changes for the same

  18. Optimization based tumor classification from microarray gene expression data.

    Directory of Open Access Journals (Sweden)

    Onur Dagliyan

    Full Text Available BACKGROUND: An important use of data obtained from microarray measurements is the classification of tumor types with respect to genes that are either up or down regulated in specific cancer types. A number of algorithms have been proposed to obtain such classifications. These algorithms usually require parameter optimization to obtain accurate results depending on the type of data. Additionally, it is highly critical to find an optimal set of markers among those up or down regulated genes that can be clinically utilized to build assays for the diagnosis or to follow progression of specific cancer types. In this paper, we employ a mixed integer programming based classification algorithm named hyper-box enclosure method (HBE for the classification of some cancer types with a minimal set of predictor genes. This optimization based method which is a user friendly and efficient classifier may allow the clinicians to diagnose and follow progression of certain cancer types. METHODOLOGY/PRINCIPAL FINDINGS: We apply HBE algorithm to some well known data sets such as leukemia, prostate cancer, diffuse large B-cell lymphoma (DLBCL, small round blue cell tumors (SRBCT to find some predictor genes that can be utilized for diagnosis and prognosis in a robust manner with a high accuracy. Our approach does not require any modification or parameter optimization for each data set. Additionally, information gain attribute evaluator, relief attribute evaluator and correlation-based feature selection methods are employed for the gene selection. The results are compared with those from other studies and biological roles of selected genes in corresponding cancer type are described. CONCLUSIONS/SIGNIFICANCE: The performance of our algorithm overall was better than the other algorithms reported in the literature and classifiers found in WEKA data-mining package. Since it does not require a parameter optimization and it performs consistently very high prediction rate on

  19. Microgel Tethering For Microarray-Based Nucleic Acid Diagnostics

    Science.gov (United States)

    Dai, Xiaoguang

    Molecular diagnostics (MDx) have radically changed the process of clinical microbial identification based on identifying genetic information, MDx approaches are both specific and fast. They can identify microbes to the species and strain level over a time scale that can be as short as one hour. With such information clinicians can administer the most effective and appropriate antimicrobial treatment at an early time point with substantial implications both for patient well-being and for easing the burden on the health-care system. Among the different MDx approaches, such as fluorescence in-situ hybridization, microarrays, next-generation sequencing, and mass spectrometry, point-of-care MDx platforms are drawing particular interest due to their low cost, robustness, and wide application. This dissertation develops a novel MDx technology platform capable of high target amplification and detection performance. For nucleic acid target detection, we fabricate an array of electron-beam-patterned microgels on a standard glass microscope slide. The microgels can be as small as a few hundred nanometers. The unique way of energy deposition during electron-beam lithography provides the microgels with a very diffuse water -gel interface that enables them to not only serve as substrates to immobilize DNA probes but do so while preserving them in a highly hydrated environment that optimizes their performance. Benefiting from the high spatial resolution provided by such techniques as position-sensitive microspotting and dip-pen nanolithography, multiple oligonucleotide probes known as molecular beacons (MBs) can be patterned on microgels. Furthermore, nucleic acid target amplification can be conducted in direct contact with the microgel-tethered detection array. Specifically, we use an isothermal RNA amplification reaction - nucleic acid sequence-based amplification (NASBA). ssRNA amplicons of from the NASBA reaction can directly hybridize with microgel-tethered MBs, and the

  20. 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.