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The Innate Immune Database (IIDB).

Korb M, Rust AG, Thorsson V, Battail C, Li B, Hwang D, Kennedy KA, Roach JC, Rosenberger CM, Gilchrist M, Zak D, Johnson C, Marzolf B, Aderem A, Shmulevich I, Bolouri H - BMC Immunol. (2008)

Bottom Line: For one example transcription factor (ATF3) for which experimental data is available, over 50% of our predicted binding sites coincide with genome-wide chromatin immnuopreciptation (ChIP-chip) results.Our database can be interrogated via a web interface.We present the Innate Immune Database (IIDB) as a community resource for immunologists interested in gene regulatory systems underlying innate responses to pathogens.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute for Systems Biology, 1441 North 34thStreet, Seattle, Washington 98103-8904, USA. mkorb@systemsbiology.org

ABSTRACT

Background: As part of a National Institute of Allergy and Infectious Diseases funded collaborative project, we have performed over 150 microarray experiments measuring the response of C57/BL6 mouse bone marrow macrophages to toll-like receptor stimuli. These microarray expression profiles are available freely from our project web site http://www.innateImmunity-systemsbiology.org. Here, we report the development of a database of computationally predicted transcription factor binding sites and related genomic features for a set of over 2000 murine immune genes of interest. Our database, which includes microarray co-expression clusters and a host of web-based query, analysis and visualization facilities, is available freely via the internet. It provides a broad resource to the research community, and a stepping stone towards the delineation of the network of transcriptional regulatory interactions underlying the integrated response of macrophages to pathogens.

Description: We constructed a database indexed on genes and annotations of the immediate surrounding genomic regions. To facilitate both gene-specific and systems biology oriented research, our database provides the means to analyze individual genes or an entire genomic locus. Although our focus to-date has been on mammalian toll-like receptor signaling pathways, our database structure is not limited to this subject, and is intended to be broadly applicable to immunology. By focusing on selected immune-active genes, we were able to perform computationally intensive expression and sequence analyses that would currently be prohibitive if applied to the entire genome. Using six complementary computational algorithms and methodologies, we identified transcription factor binding sites based on the Position Weight Matrices available in TRANSFAC. For one example transcription factor (ATF3) for which experimental data is available, over 50% of our predicted binding sites coincide with genome-wide chromatin immnuopreciptation (ChIP-chip) results. Our database can be interrogated via a web interface. Genomic annotations and binding site predictions can be automatically viewed with a customized version of the Argo genome browser.

Conclusion: We present the Innate Immune Database (IIDB) as a community resource for immunologists interested in gene regulatory systems underlying innate responses to pathogens. The database website can be freely accessed at http://db.systemsbiology.net/IIDB.

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Related in: MedlinePlus

Searching genes for targets of specific transcription factors. IIDB provides a list of 268 unique transcription factors in the selection box on the left. The user can select several transcription factors, the p-value, the length of promoter region to explore, and any number of target genes. The target gene column is automatically populated if the user selects genes from a previous page (shown). Otherwise the user can add a comma separated list of gene identifiers or chromosomal locations (not shown). Several additional features can be displayed simultaneously on top of the predicted transcription factor binding sites (selection boxes at bottom). A link to a page which details the upload format for a search file for bulk queries is also provided (not shown).
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Figure 3: Searching genes for targets of specific transcription factors. IIDB provides a list of 268 unique transcription factors in the selection box on the left. The user can select several transcription factors, the p-value, the length of promoter region to explore, and any number of target genes. The target gene column is automatically populated if the user selects genes from a previous page (shown). Otherwise the user can add a comma separated list of gene identifiers or chromosomal locations (not shown). Several additional features can be displayed simultaneously on top of the predicted transcription factor binding sites (selection boxes at bottom). A link to a page which details the upload format for a search file for bulk queries is also provided (not shown).

Mentions: A total of 143 PWMs representing 268 transcription factors as 67 transcription factor families and 76 single-factor matrices are stored in our database. A user can search for the binding sites of one or several transcription factor families at once, and compare TFBS locations across multiple genes (Fig. 3). Because IIDB generates standard .gff files on-the-fly, the user can select the set of features to view online or export the data to other genome browsers. Also an easy to use file upload facility is available for specifying a large number of transcription factors and their putative target genes in a query. The user is contacted by email when the analysis is complete.


The Innate Immune Database (IIDB).

Korb M, Rust AG, Thorsson V, Battail C, Li B, Hwang D, Kennedy KA, Roach JC, Rosenberger CM, Gilchrist M, Zak D, Johnson C, Marzolf B, Aderem A, Shmulevich I, Bolouri H - BMC Immunol. (2008)

Searching genes for targets of specific transcription factors. IIDB provides a list of 268 unique transcription factors in the selection box on the left. The user can select several transcription factors, the p-value, the length of promoter region to explore, and any number of target genes. The target gene column is automatically populated if the user selects genes from a previous page (shown). Otherwise the user can add a comma separated list of gene identifiers or chromosomal locations (not shown). Several additional features can be displayed simultaneously on top of the predicted transcription factor binding sites (selection boxes at bottom). A link to a page which details the upload format for a search file for bulk queries is also provided (not shown).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2268913&req=5

Figure 3: Searching genes for targets of specific transcription factors. IIDB provides a list of 268 unique transcription factors in the selection box on the left. The user can select several transcription factors, the p-value, the length of promoter region to explore, and any number of target genes. The target gene column is automatically populated if the user selects genes from a previous page (shown). Otherwise the user can add a comma separated list of gene identifiers or chromosomal locations (not shown). Several additional features can be displayed simultaneously on top of the predicted transcription factor binding sites (selection boxes at bottom). A link to a page which details the upload format for a search file for bulk queries is also provided (not shown).
Mentions: A total of 143 PWMs representing 268 transcription factors as 67 transcription factor families and 76 single-factor matrices are stored in our database. A user can search for the binding sites of one or several transcription factor families at once, and compare TFBS locations across multiple genes (Fig. 3). Because IIDB generates standard .gff files on-the-fly, the user can select the set of features to view online or export the data to other genome browsers. Also an easy to use file upload facility is available for specifying a large number of transcription factors and their putative target genes in a query. The user is contacted by email when the analysis is complete.

Bottom Line: For one example transcription factor (ATF3) for which experimental data is available, over 50% of our predicted binding sites coincide with genome-wide chromatin immnuopreciptation (ChIP-chip) results.Our database can be interrogated via a web interface.We present the Innate Immune Database (IIDB) as a community resource for immunologists interested in gene regulatory systems underlying innate responses to pathogens.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute for Systems Biology, 1441 North 34thStreet, Seattle, Washington 98103-8904, USA. mkorb@systemsbiology.org

ABSTRACT

Background: As part of a National Institute of Allergy and Infectious Diseases funded collaborative project, we have performed over 150 microarray experiments measuring the response of C57/BL6 mouse bone marrow macrophages to toll-like receptor stimuli. These microarray expression profiles are available freely from our project web site http://www.innateImmunity-systemsbiology.org. Here, we report the development of a database of computationally predicted transcription factor binding sites and related genomic features for a set of over 2000 murine immune genes of interest. Our database, which includes microarray co-expression clusters and a host of web-based query, analysis and visualization facilities, is available freely via the internet. It provides a broad resource to the research community, and a stepping stone towards the delineation of the network of transcriptional regulatory interactions underlying the integrated response of macrophages to pathogens.

Description: We constructed a database indexed on genes and annotations of the immediate surrounding genomic regions. To facilitate both gene-specific and systems biology oriented research, our database provides the means to analyze individual genes or an entire genomic locus. Although our focus to-date has been on mammalian toll-like receptor signaling pathways, our database structure is not limited to this subject, and is intended to be broadly applicable to immunology. By focusing on selected immune-active genes, we were able to perform computationally intensive expression and sequence analyses that would currently be prohibitive if applied to the entire genome. Using six complementary computational algorithms and methodologies, we identified transcription factor binding sites based on the Position Weight Matrices available in TRANSFAC. For one example transcription factor (ATF3) for which experimental data is available, over 50% of our predicted binding sites coincide with genome-wide chromatin immnuopreciptation (ChIP-chip) results. Our database can be interrogated via a web interface. Genomic annotations and binding site predictions can be automatically viewed with a customized version of the Argo genome browser.

Conclusion: We present the Innate Immune Database (IIDB) as a community resource for immunologists interested in gene regulatory systems underlying innate responses to pathogens. The database website can be freely accessed at http://db.systemsbiology.net/IIDB.

Show MeSH
Related in: MedlinePlus