ProbeMatchDB—a web database for finding equivalent probes
  across microarray platforms and species

Wang, Pinglang; Ding, Fei; Chiang, Hsienyuan; Thompson, Robert C.; Watson, Stanley J.; Meng, Fan

doi:10.1093/bioinformatics/18.3.488

Cited by 21 publications

(14 citation statements)

References 2 publications

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“…We downloaded .CSV-formatted annotation data for the Affymetrix HGU133Av2 human oligonucleotide microarray from the support section of the Affymetrix website (version 25, dated 3/18/08). The ProbeMatchDB database identified cross-species orthologs by UniGene ID (83).…”

Section: Methodsmentioning

confidence: 99%

Highly conserved transcriptional responses to mechanical ventilation of the lung

Kompass¹,

Deslée

Moore

et al. 2010

Physiological Genomics

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Cross-species analysis of microarray data has shown improved discriminating power between healthy and diseased states. Computational approaches have proven effective in deciphering the complexity of human disease by identifying upstream regulatory elements and the transcription factors that interact with them. Here we used both methods to identify highly conserved transcriptional responses during mechanical ventilation, an important therapeutic treatment that has injurious side effects. We generated control and ventilated whole lung samples from the premature baboon model of bronchopulmonary dysplasia (BPD), processed them for microarray, and combined them with existing whole lung oligonucleotide microarray data from 85 additional control samples from mouse, rat, and human and 19 additional ventilated samples from mouse and rat. Of the 2,531 orthologs shared by all 114 samples, 60 were modulated by mechanical ventilation [false discovery rate (FDR)-adjusted q value ( qFDR) = 0.005, ANOVA]. These included transcripts encoding the transcription factors ATF3 and FOS. Because of compelling known roles for these transcription factors, we used computational methods to predict their targets in the premature baboon model of BPD, which included elastin (ELN), gastrin-releasing polypeptide (GRP), and connective tissue growth factor (CTGF). This approach identified highly conserved transcriptional responses to mechanical ventilation and may facilitate identification of therapeutic targets to reduce the side effects of this valuable treatment.

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Section: Methodsmentioning

confidence: 99%

Highly conserved transcriptional responses to mechanical ventilation of the lung

Kompass¹,

Deslée

Moore

et al. 2010

Physiological Genomics

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show abstract

“…In addition, errors in links can easily be corrected. Platform-specific or overall coupling files can be retrieved from the Affymetrix website [31] and from sources such as Resourcerer [32], KARMA [33], GeneHopper [34], ProbeMatchDB [35], DAVID [36], EnsMart [37], and Source [38]. Using these resources, microarray datasets from different platforms can be linked.…”

Section: Resultsmentioning

confidence: 99%

Storing, linking, and mining microarray databases using SRS

et al. 2005

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Background: SRS (Sequence Retrieval System) has proven to be a valuable platform for storing, linking, and querying biological databases. Due to the availability of a broad range of different scientific databases in SRS, it has become a useful platform to incorporate and mine microarray data to facilitate the analyses of biological questions and non-hypothesis driven quests. Here we report various solutions and tools for integrating and mining annotated expression data in SRS.

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“…For various types of genetic marker names and genomic/chromosome location queries, we use a powerful genetic marker search function developed in our group for the SNP Function Portal, which is designed to provide extensive molecular level function annotation for SNPs (Wang et al, 2006). To support gene/protein accession numbers and GeneChip IDs, we include the ProbeMatchDB functionality in the MarkerInfoFinder (Wang et al, 2002). In addition, Section 3.3 describes the ability to use genetic disease names directly in the search.…”

Section: System Designmentioning

confidence: 99%

Medline search engine for finding genetic markers with biological significance

et al. 2007

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Motivation: Genome-wide high density SNP association studies are expected to identify various SNP alleles associated with different complex disorders. Understanding the biological significance of these SNP alleles in the context of existing literature is a major challenge since existing search engines are not designed to search literature for SNPs or other genetic markers. The literature mining of gene and protein functions has received significant attention and effort while similar work on genetic markers and their related diseases is still in its infancy. Our goal is to develop a web-based tool that facilitates the mining of Medline literature related to genetic studies and gene/protein function studies. Our solution consists of four main function modules for (1) identification of different types of genetic markers or genetic variations in Medline records (2) distinguishing positive versus negative linkage or association between genetic markers and diseases (3) integrating marker genomic location data from different databases to enable the retrieval of Medline records related to markers in the same linkage disequilibrium region (4) and a web interface called MarkerInfoFinder to search, display, sort and download Medline citation results. Tests using published data suggest MarkerInfoFinder can significantly increase the efficiency of finding genetic disorders and their underlying molecular mechanisms. The functions we developed will also be used to build a knowledge base for genetic markers and diseases. Availability: The MarkerInfoFinder is publicly available at:

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ProbeMatchDB—a web database for finding equivalent probes across microarray platforms and species

Abstract: The database is accessible at http://brainarray.mhri.med.umich.edu/MARRAY/BC_ASP/brainarray.htm by clicking the 'Query ProbeMatchDB' link.

Cited by 21 publications

References 2 publications

Highly conserved transcriptional responses to mechanical ventilation of the lung

Highly conserved transcriptional responses to mechanical ventilation of the lung

Storing, linking, and mining microarray databases using SRS

Medline search engine for finding genetic markers with biological significance

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