He has received postdoctoral training at the U. Centers for Disease Control and Prevention and a clinical microbiology fellowship at the Mayo Clinic. Tang has research interests in the development and validation of molecular techniques and has published over peer-reviewed original articles, reviews, and book chapters in the field of diagnostic molecular microbiology. We request your email address only to inform the recipient that it was you who recommended this article, and that it is not junk mail.
We do not retain these email addresses. Skip to main content. Miller , Yi-Wei Tang. View inline View popup. Comparison of microarray platforms a. Mutation discovery in bacterial genomes: Easy and fast detection and genotyping of high-risk human papillomavirus by dedicated DNA microarrays.
Pathotyping Escherichia coli by using miniaturized DNA microarrays. Rapid diagnosis of bacteremia by universal amplification of 23S ribosomal DNA followed by hybridization to an oligonucleotide array. Detection of mutations in Mycobacterium tuberculosis genome determining resistance to fluoroquinolones by hybridization on biological microchips. Rapid detection of specific gene mutations associated with isoniazid or rifampicin resistance in Mycobacterium tuberculosis clinical isolates using non-fluorescent low-density DNA microarrays.
Suspension arrays for high throughput, multiplexed single nucleotide polymorphism genotyping. Fast DNA serotyping of Escherichia coli by use of an oligonucleotide microarray. Electronic microarray analysis of 16S rDNA amplicons for bacterial detection. Signature gene expression profiles discriminate between isoniazid-, thiolactomycin-, and triclosan-treated Mycobacterium tuberculosis. GoldenGate assay for DNA methylation profiling. High-throughput DNA methylation profiling using universal bead arrays.
Quantitative gene expression profiling in formalin-fixed, paraffin-embedded tissues using universal bead arrays. Eight-plex PCR and liquid-array detection of bacterial and viral pathogens in cerebrospinal fluid from patients with suspected meningitis. Genomic-scale analysis of bacterial gene and protein expression in the host. Genomic scale analysis of Pasteurella multocida gene expression during growth within the natural chicken host.
Direct screening of clinical specimens for multiple respiratory pathogens using the Genaco Respiratory Panels 1 and 2.
Automated liquid handling and high-throughput preparation of polymerase chain reaction-amplified DNA for microarray fabrication. Identifying antimicrobial resistance genes with DNA microarrays. A network-based analysis of systemic inflammation in humans. Genomic profiling of cancer-related genes in archived esophageal normal and carcinoma tissues.
A microsphere-based assay for multiplexed single nucleotide polymorphism analysis using single base chain extension. Making and reading microarrays. Diagnosis of a critical respiratory illness caused by human metapneumovirus by use of a pan-virus microarray. Microarray detection of human parainfluenzavirus 4 infection associated with respiratory failure in an immunocompetent adult.
Microarray analysis of microbial virulence factors. Detection and genotyping of human group A rotaviruses by oligonucleotide microarray hybridization. Optimization of probe length and the number of probes per gene for optimal microarray analysis of gene expression. Molecular diagnostics in sepsis: Identification and characterization of bacterial pathogens causing bloodstream infections by DNA microarray.
Sepsis gene expression profiling: Monitoring cellular responses to Listeria monocytogenes with oligonucleotide arrays. Functional genomics of innate host defense molecules in normal human monocytes in response to Aspergillus fumigatus. Rapid microarray-based method for monitoring of all currently known single-nucleotide polymorphisms associated with parasite resistance to antimalaria drugs. DNA microarray-based identification of genes associated with glycopeptide resistance in Staphylococcus aureus. The Affymetrix GeneChip platform: Culture versus polymerase chain reaction for the etiologic diagnosis of community-acquired pneumonia in antibiotic-pretreated pediatric patients.
Multiplex detection of mutations in clinical isolates of rifampin-resistant Mycobacterium tuberculosis by short oligonucleotide ligation assay on DNA chips. Microarray-based pncA genotyping of pyrazinamide-resistant strains of Mycobacterium tuberculosis. Generic detection of coronaviruses and differentiation at the prototype strain level by reverse transcription-PCR and nonfluorescent low-density microarray.
Use of a suspension array for rapid identification of the varieties and genotypes of the Cryptococcus neoformans species complex. Transcriptome analysis of Neisseria meningitidis during infection. Evaluation of differential gene expression in susceptible and resistant clinical isolates of Klebsiella pneumoniae by DNA microarray analysis. Whole genome comparison of Campylobacter jejuni human isolates using a low-cost microarray reveals extensive genetic diversity.
Applications of Luminex xMAP technology for rapid, high-throughput multiplexed nucleic acid detection. Statistical issues in the analysis of Illumina data. R classes and methods for Illumina bead-based data. DNA microarray technology for the microbiologist: Illumina universal bead arrays. BeadArray-based solutions for enabling the promise of pharmacogenomics. A versatile assay for high-throughput gene expression profiling on universal array matrices. Molecular characterization of the acute inflammatory response to infections with gram-negative versus gram-positive bacteria.
Multiplex, bead-based suspension array for molecular determination of common Salmonella serogroups. Evolutionary genomics of Staphylococcus aureus: Whole blood gene expression in infants with respiratory syncytial virus bronchiolitis. Light-directed, spatially addressable parallel chemical synthesis. Detection and identification of Mycobacterium species isolates by DNA microarray. Global transcriptome analysis of the heat shock response of Shewanella oneidensis. Prevalence of and molecular basis for tuberculosis drug resistance in the Republic of Georgia: Microarray-based microbial identification and characterization, p.
Development of a sensitive and specific multiplex PCR method combined with DNA microarray primer extension to detect betapapillomavirus types. Development of a sensitive and specific assay combining multiplex PCR and DNA microarray primer extension to detect high-risk mucosal human papillomavirus types.
Gene expression profile in Neisseria meningitidis and Neisseria lactamica upon host-cell contact: Evaluation of hybridisation on oligonucleotide microarrays for analysis of drug-resistant Mycobacterium tuberculosis. Whole-genome genotyping on bead arrays. Decoding randomly ordered DNA arrays. Making and using spotted DNA microarrays in an academic core laboratory. Simultaneous amplification and identification of 25 human papillomavirus types with Templex technology. Shotgun DNA microarrays and stage-specific gene expression in Plasmodium falciparum malaria.
Quantitative single cell analysis and sorting. Using oligonucleotide suspension arrays for laboratory identification of bacteria responsible for bacteremia. Identification of medically important molds by an oligonucleotide array. High-throughput identification of clinical pathogenic fungi by hybridization to an oligonucleotide microarray. The plasticity of dendritic cell responses to pathogens and their components.
Expression profiling using microarrays fabricated by an ink-jet oligonucleotide synthesizer. Multiplexed single nucleotide polymorphism genotyping by oligonucleotide ligation and flow cytometry. Helicobacter pylori strain-specific differences in genetic content, identified by microarray, influence host inflammatory responses. Applicability of microarray technique for the detection of noro- and astroviruses.
Candidate biomarkers for discrimination between infection and disease caused by Mycobacterium tuberculosis. Insights into host responses against pathogens from transcriptional profiling. Gene expression profiles differentiate between sterile SIRS and early sepsis. Multiplexed genetic analysis using an expanded genetic alphabet. Determination of nucleic acid sequence homologies and relative concentrations by a dot hybridization procedure.
Detection and identification of Escherichia coli , Shigella , and Salmonella by microarrays using the gyrB gene. Reduced immunopathology and mortality despite tissue persistence in a Mycobacterium tuberculosis mutant lacking alternative sigma factor, SigH. Resistance and susceptibility to tuberculosis analysed at the transcriptome level: Single-nucleotide polymorphisms associated with symptomatic infection and differential human gene expression in healthy seropositive persons each implicate the cytoskeleton, integrin signaling, and oncosuppression in the pathogenesis of human parvovirus B19 infection.
Expression of genes encoding innate host defense molecules in normal human monocytes in response to Candida albicans. Pan-viral screening of respiratory tract infections in adults with and without asthma reveals unexpected human coronavirus and human rhinovirus diversity. Use of oligoarrays for characterization of community-onset methicillin-resistant Staphylococcus aureus.
Use of diagnostic microarrays for determination of virulence gene patterns of Escherichia coli K1, a major cause of neonatal meningitis. DNA probe array for the simultaneous identification of herpesviruses, enteroviruses, and flaviviruses. A microbial diagnostic microarray technique for the sensitive detection and identification of pathogenic bacteria in a background of nonpathogens.
Application of DNA microarray technology for detection, identification, and characterization of food-borne pathogens. Extensive polymorphisms observed in HIV-1 clade B protease gene using high-density oligonucleotide arrays. A novel, high-performance random array platform for quantitative gene expression profiling. Detection of 11 common viral and bacterial pathogens causing community-acquired pneumonia or sepsis in asymptomatic patients by using a multiplex reverse transcription-PCR assay with manual enzyme hybridization or automated electronic microarray detection.
High-throughput, sensitive, and accurate multiplex PCR-microsphere flow cytometry system for large-scale comprehensive detection of respiratory viruses. Development of a DNA microarray for detection and identification of fungal pathogens involved in invasive mycoses. Multiplexed molecular assay for rapid exclusion of foot-and-mouth disease.
Simultaneous detection and high-throughput identification of a panel of RNA viruses causing respiratory tract infections. Development of a serotype-specific DNA microarray for identification of some Shigella and pathogenic Escherichia coli strains. Using a resequencing microarray as a multiple respiratory pathogen detection assay.
Universal detection and identification of avian influenza virus by use of resequencing microarrays. Use of oligonucleotide microarrays for rapid detection and serotyping of acute respiratory disease-associated adenoviruses. Genomic polymorphisms in sepsis. Human papillomavirus genotyping by oligonucleotide microarray and p16 expression in uterine cervical intraepithelial neoplasm and in invasive carcinoma in Korean women. Differential expression of Toll-like receptor genes: Genome-wide expression profiling of the response to azole, polyene, echinocandin, and pyrimidine antifungal agents in Candida albicans.
Protein micro- and macroarrays: Microarrays for genotyping human group A rotavirus by multiplex capture and type-specific primer extension. Transcriptional adaptation of Shigella flexneri during infection of macrophages and epithelial cells: Protein microarrays and proteomics. Development of a respiratory virus panel test for detection of twenty human respiratory viruses by use of multiplex PCR and a fluid microbead-based assay.
Automated identification of multiple micro-organisms from resequencing DNA microarrays. Application of an rRNA probe matrix for rapid identification of bacteria and fungi from routine blood cultures. Detection of a soluble form of B CD80 in synovial fluid from patients with arthritis using monoclonal antibodies against distinct epitopes of human B DNA microarrays in the clinic: Identification of rifampin-resistant Mycobacterium tuberculosis strains by hybridization, PCR, and ligase detection reaction on oligonucleotide microchips.
Solid and liquid phase array technologies. Comparative genomics and DNA array-based genotyping of pandemic Staphylococcus aureus strains encoding Panton-Valentine leukocidin.
Rapid genotyping of methicillin-resistant Staphylococcus aureus MRSA isolates using miniaturised oligonucleotide arrays. Microarray-based characterisation of a Panton-Valentine leukocidin-positive community-acquired strain of methicillin-resistant Staphylococcus aureus. Adenosine A2A receptor inactivation increases survival in polymicrobial sepsis. MultiCode-PLx system for multiplexed detection of seventeen respiratory viruses.
Oligonucleotide microarray for identification of Bacillus anthracis based on intergenic transcribed spacers in ribosomal DNA. Polymerase chain reaction-based fluorescent Luminex assay to detect the presence of human papillomavirus types. Differential cellular gene expression induced by hepatitis B and C viruses. Comparison of the Luminex xTAG respiratory viral panel with in-house nucleic acid amplification tests for diagnosis of respiratory virus infections. Systemic transcriptional analysis in survivor and non-survivor septic shock patients: Panmicrobial oligonucleotide array for diagnosis of infectious diseases.
Rapid quantitative profiling of complex microbial populations. Comparison of reverse hybridization, microarray, and sequence analysis for genotyping hepatitis B virus. Microarray-based detection of 90 antibiotic resistance genes of gram-positive bacteria. MVPlex assay for direct detection of methicillin-resistant Staphylococcus aureus in naris and other swab specimens. Evolutionary genomics of Salmonella: Detection of respiratory viruses and subtype identification of influenza A viruses by GreeneChipResp oligonucleotide microarray.
Unique transcriptome signature of Mycobacterium tuberculosis in pulmonary tuberculosis. Improving signal intensities for genes with low-expression on oligonucleotide microarrays. Comparison of automated microarray detection with real-time PCR assays for detection of respiratory viruses in specimens obtained from children. Genome-wide requirements for Mycobacterium tuberculosis adaptation and survival in macrophages. DNA microarray analysis of differential gene expression in Borrelia burgdorferi , the Lyme disease spirochete. Characterization of a novel coronavirus associated with severe acute respiratory syndrome.
A whole-genome microarray reveals genetic diversity among Helicobacter pylori strains. Genetic requirements for mycobacterial survival during infection. Detection of viruses in human adenoid tissues by use of multiplex PCR. Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Exploring glycopeptide-resistance in Staphylococcus aureus: Molecular detection and identification of influenza viruses by oligonucleotide microarray hybridization. Insights into the pathobiology of hepatitis C virus-associated cirrhosis: Expression of immunomodulatory genes in human monocytes induced by voriconazole in the presence of Aspergillus fumigatus.
Rapid determination of single base mismatch mutations in DNA hybrids by direct electric field control. Use of a high-density DNA probe array for detecting mutations involved in rifampicin resistance in Mycobacterium tuberculosis. Detection of specific sequences among DNA fragments separated by gel electrophoresis. DNA microarray-based detection and identification of fungal pathogens in clinical samples from neutropenic patients. A bead-based method for multiplexed identification and quantitation of DNA sequences using flow cytometry.
Analysis of the function of mycobacterial DnaJ proteins by overexpression and microarray profiling. Use of genome-wide expression profiling and mutagenesis to study the intestinal lifestyle of Campylobacter jejuni. Extending microarray quality control and analysis algorithms to Illumina chip platform. PCR amplification on a microarray of gel-immobilized oligonucleotides: Evaluation of the NanoChip system for detection of influenza A and B, respiratory syncytial, and parainfluenza viruses. Electrochemical DNA array for simultaneous genotyping of single-nucleotide polymorphisms associated with the therapeutic effect of interferon.
Gene-expression profiling of peripheral blood mononuclear cells in sepsis. The use of gene-expression profiling to identify candidate genes in human sepsis. Microarray and allele specific PCR detection of point mutations in Mycobacterium tuberculosis genes associated with drug resistance. Comparison of phenotypic and genotypic techniques for identification of unusual aerobic pathogenic gram-negative bacilli.
StaphPlex system for rapid and simultaneous identification of antibiotic resistance determinants and Panton-Valentine leukocidin detection of staphylococci from positive blood cultures. Flow cytometric platform for high-throughput single nucleotide polymorphism analysis.
Frequency of 23 human papillomavirus types using DNA microarray in women with and without cytological anomalies. Microarray probe selection strategies. Experimental evaluation of the FluChip diagnostic microarray for influenza virus surveillance. European multicenter evaluation of high-density DNA probe arrays for detection of hepatitis B virus resistance mutations and identification of genotypes. Mycobacterium species identification and rifampin resistance testing with high-density DNA probe arrays.
Performance of the Affymetrix GeneChip HIV PRT platform for antiretroviral drug resistance genotyping of human immunodeficiency virus type 1 clades and viral isolates with length polymorphisms. Virulence typing of Escherichia coli using microarrays. Multilocus sequence typing of Staphylococcus aureus with DNA array technology. Microarray-based identification of thermophilic Campylobacter jejuni , C. Microarray-based detection of genetic heterogeneity, antimicrobial resistance, and the viable but nonculturable state in human pathogenic Vibrio spp.
Inhibition of respiration by nitric oxide induces a Mycobacterium tuberculosis dormancy program. Accurate mapping of mutations of pyrazinamide-resistant Mycobacterium tuberculosis strains with a scanning-frame oligonucleotide microarray. This review has given a small outline of the technique behind microarray and the various steps involved. The technique, though limited at present in its applications due to the cost factor, may widen its prospects once there is increase in the availability of commercial products.
The ability to record large number of old samples and analyzing them for various genetic alterations helps in understanding the concept of molecular biology. Microarrays hold much promise for the analysis of diseases in the oral cavity. Classifications of oral disease by DNA, RNA, or protein profiles will greatly enhance our ability to diagnose, prevent, monitor and treat our patients. Currently, microarrays are primarily a research tool. Microarrays promise a more biologically based, individualized, and vastly improved standard for oral care, which will have great clinical impact on the way dentistry will be practiced in the future.
National Center for Biotechnology Information , U.
J Pharm Bioallied Sci. This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 3. This article has been cited by other articles in PMC. Abstract Microarray is one of the most recent advances being used for cancer research; it provides assistance in pharmacological approach to treat various diseases including oral lesions.
Cancer, human genome, microarray, tissue microarray. Microarray Principle mRNA is an intermediary molecule which carries the genetic information from the cell nucleus to the cytoplasm for protein synthesis. Applications In cancer Tumor formation involves simultaneous changes in hundreds of cells and variations in genes.
Antibiotic treatment Increase in the number of resistant bacteria and superadded infections has led to failure of antibiotics.
Early detection of oral precancerous lesions Leukoplakia or white lesions of the oral cavity may result from a myriad of reversible conditions. Conclusion This review has given a small outline of the technique behind microarray and the various steps involved. Footnotes Source of Support: Nil Conflict of Interest: Large-scale identification, mapping, and genotyping of single-nucleotide polymorphisms in the human genome. Loss of heterozygosity analysis of small-cell lung carcinomas using single nucleotide polymorphism arrays.
Accumulative increase of loss of heterozygosity from leukoplakia to foci of early cancerization in leukoplakia of the oral cavity. Brown PO, Botstein D. Exploring the new world of the genome with DNA microarrays. High resolution analysis of DNA copy number variation using comparative genomic hybridization to microarrays. Tissue microarrays for high-throughput molecular profiling of tumor specimens. Microarray analysis reveals a major direct role of DNA copy number alteration in the transcriptional program of human breast tumors.
Biochips to screen for genomic imbalances. Array-based comparative genomic hybridization for genome-wide screening of DNA copy number in bladder tumors. Genome-wide arraybased comparative genomic hybridization reveals genetic homogeneity and frequent copy number increases encompassing CCNE1 in fallopian tube carcinoma. In other words, it is an iterative process of discovery. The complexity of most data analysis algorithms depends on the number of input dimensions, so reducing the number of genes or experimental conditions in a microarray data set is helpful for efficient analysis, as long as the reduced data set maintains important information in the original data Bura and Pfeiffer ; Dai et al.
Dimensionality reduction algorithms can be classified into feature selection and feature extraction. Feature selection is to select k dimensions, out of the original d dimensions, that can best represent the original data set Chen et al. Feature extraction is to find a new set of k dimensions that are some combinations of the original d dimensions. The most popular feature extraction algorithms may be the linear projection method such as principal component analysis PCA for unsupervised learning Li et al. Other methods used in dimension reduction are Independent Component Analysis Saidi et al.
When one has done multiple experiments, under different conditions -different patients, different time points, and etc- one can group the genes, which behave similarly and based on the pattern of the distinguishing genes, one can for example set boundaries between different subtypes of cancer. One can identify samples with similar expression level patterns or genes which are similar across samples. The main aim is to look for the most different features that should be the best at discriminating classes. Supervised approaches are the analyses which are designed to determine the genes that fit a predetermined pattern.
In the case of a supervised learning, one can use the annotation of either the gene or the sample, and create clusters of genes or samples in order to identify patterns that are characteristic for the cluster. In other words one can specify relationships among objects in supervised learning Jirapech-Umpai and Aitken The main goal of supervised learning is data classification and subsequently prediction. Unlike supervised learning, unsupervised methods are used to characterize the components of a data set without the a priori input or knowledge of a training signal; i.
However, annotation information may be taken into account at a later stage in unsupervised learning to make meaningful biological inferences Redestig et al. The most commonly used popular supervised techniques are nearest neighbors Mezghani et al. The most common unsupervised techniques are hierarchical clustering Chipman and Tibshirani ; Makretsov et al. The methods presented up until now are correlative methods. These methods cluster genes together according to the measure of correlation between them. Genes that are clustered together may and only may imply that they participate at the same biological process.
However these methods are computationally cheap and one cannot infer the relationships between the genes. The basic questions in functional genomics are: Perhaps the most recent and the most important part in microarray data analysis is reverse engineering of gene regulatory networks for understanding the dynamics of gene expression. Pathway analysis towards functional enrichment can be fulfilled using two methods one of which is time-series data Dewey ; Filkov et al. In the former approach the amount of expression of a certain gene at a certain time is a function of expression of the other genes at all previous time points.
In the latter approach, the effects of deleting a certain gene on the expression of other genes are inspected and based on the regulation of the other genes; the function of that certain gene in regulation of the other genes is assessed. These methods still lack full applicability, because there is a need for more knowledge on sophisticated networks in the cells in order to identify the hidden role of different molecules in the circuitry of gene regulation.
Understanding the expression dynamics helps us infer innate complexities and phenomenological networks among genes. Defining the true place of the genes in cell networks is the main phase in our understanding of programming and functioning of living cells. Table 2 represents some important softwares available for handling of microarray data. Of these softwares, some of them such as TM4 are freely available while some others such as ImaGen and GeneSight are commercially available.
Among these tools, some deal with gene ontology which may help us towards better understanding of function genomics. Authors are grateful to the Ministry of Health, Care and Medical Education for the financial support. National Center for Biotechnology Information , U. Journal List Bioimpacts v. Published online Aug 4. Yadollah Omidi PhD , Tel.: This article has been cited by other articles in PMC. 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.
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. Introduction Proteins, the amazing molecules of nature are almost involved in any activity in the cells from production of energy and biosynthesis of all component macromolecules to the maintenance of cellular architecture, and the ability to act upon intra- and extracellular stimuli.
Open in a separate window. Schematic steps of DNA microarray technology. Image capturing and analysis plus primary data extraction Fluorophore-tagged representations of mRNA from two treatments, each tagged with a fluorophore emitting a different color light usually green and red , are hybridized to the array of cDNAs and then fluorescence emission at the site of each immobilized cDNA is quantified and finally an image is produced.
Translation of DNA microarray data into clinical applications. Normalization Many sources of errors and inconsistencies may be involved in image processing. Table 1 Considerations in different steps of microarray data management. Analysis step Important considerations References Experimental design and implementation Number of the replicates must be determined carefully Experimental errors should be avoided as much as possible The biological question behind the experiment should be defined carefully Information collection standards MIAME must be met Bolstad ; Churchill ; Foster ; Kerr ; Simon Image acquisition and analysis Image should be scanned at appropriate resolution Gridding step must be manually proofread Good choice of segmentation algorithm should be considered Istepanian ; Kadanga et al.
Dealing with missing values The gene expression data matrix may have missing values due to non-systematic inconsistencies such as pollution on the glass, image corruption during scanning, low resolution images, as well as systematic errors occurring in the microarray manufacturing process. Identification of differentially expressed genes All microarray experiments are carried out to find genes which are differentially expressed between two or more samples of cells ; Abiko et al. Higher level analysis of microarray data Once differentially expressed genes have successfully been distinguished, high level analyses or data mining of microarray data begins.
Dimension reduction The complexity of most data analysis algorithms depends on the number of input dimensions, so reducing the number of genes or experimental conditions in a microarray data set is helpful for efficient analysis, as long as the reduced data set maintains important information in the original data Bura and Pfeiffer ; Dai et al. Clustering and classification When one has done multiple experiments, under different conditions -different patients, different time points, and etc- one can group the genes, which behave similarly and based on the pattern of the distinguishing genes, one can for example set boundaries between different subtypes of cancer.
Schematic illustration of Euclidean distance clustering of expressed genes G. Reverse engineering of gene regulatory networks Perhaps the most recent and the most important part in microarray data analysis is reverse engineering of gene regulatory networks for understanding the dynamics of gene expression. Free trial version at http: Analysis tools are also available for time- course experiments.
Complete and professional for data mining of microarray results Integrated error handling and hypothesis testing tools http: EASE provides statistical methods for discovering enriched biological themes within gene lists, generates gene annotation tables, and enables automated linking to online analysis tools. EGAN Exploratory Gene Association Networks Visualizing and interpreting the results of high-throughput exploratory assays in an interactive hypergraph of genes, relationships protein-protein interactions, literature co-occurrence, etc.
EGAN provides comprehensive, automated enrichment analysis Links to external web resources including more than articles at PubMed, hypergeometric and GSEA-like enrichment statistics FunCluster Detecting co-regulated biological processes involving FunCluster's functional analysis relies on GO and KEGG annotations and is currently available for three organisms: Homo sapiens, Mus musculus and Saccharomyces cerevisiae.
FunNet A tool for exploring transcriptional interactions in gene expression datasets. FunNet is provided both as a web-based tool and as a standalone R package. The confidence analyzer tool can use replicated gene expression data for identifying genes having true differential expression. GeneSight can easily import array data contained in any text-based file format.
Different packages are available in the Bioconductor website. When released BioC 2. For more information refer to http: Useful mostly for paired microarray data. Free and user-friendly software http: It dynamically determines the latest names, symbols, functions, and genome position for each gene and includes these in the relevance networks output. MeV identifies patterns of gene expression and differentially expressed genes MADAM is a java-based application to load and retrieve microarray data to and from a database.
TIGR Spotfinder is an image processing software. MIDAS is a microarray data quality filtering and normalization tool. It offers links to genomic websites for gene annotation and analysis tools for pathway analysis. ExpressYourself investigates the quality of experiments by measuring hybridization consistency within single slides and across replicated experiments.
The data quality step calculates the overall performance of experiments and highlights problematic array regions. Freely available at http: It supports hierarchical clustering and SOMs for data clustering. On-line tutorials are available from main web server http: CARMAweb is freely available at https: GoMiner GoMiner is a program for visualizing the genes on a list within the context of the structure of the GO.
Instead of analyzing microarray results with a gene-by-gene approach, GoMiner classifies the genes into biologically coherent categories and assesses these categories. Affymetrix platform and high-level analysis of gene expression microarrays and SNP microarrays. High-level analysis in dChip includes comparing samples, hierarchical clustering, viewing expression and SNP data along chromosome http: Ethical Issues None to be declared.
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