The Innate Immune Database (IIDB)

<p>Abstract</p> <p>Background</p> <p>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...

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Main Authors: Zak Daniel, Gilchrist Mark, Rosenberger Carrie M, Roach Jared C, Kennedy Kathleen A, Hwang Daehee, Li Bin, Battail Christophe, Thorsson Vesteinn, Rust Alistair G, Korb Martin, Johnson Carrie, Marzolf Bruz, Aderem Alan, Shmulevich Ilya, Bolouri Hamid
Format: Article
Language:English
Published: BMC 2008-03-01
Series:BMC Immunology
Online Access:http://www.biomedcentral.com/1471-2172/9/7
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author Zak Daniel
Gilchrist Mark
Rosenberger Carrie M
Roach Jared C
Kennedy Kathleen A
Hwang Daehee
Li Bin
Battail Christophe
Thorsson Vesteinn
Rust Alistair G
Korb Martin
Johnson Carrie
Marzolf Bruz
Aderem Alan
Shmulevich Ilya
Bolouri Hamid
author_facet Zak Daniel
Gilchrist Mark
Rosenberger Carrie M
Roach Jared C
Kennedy Kathleen A
Hwang Daehee
Li Bin
Battail Christophe
Thorsson Vesteinn
Rust Alistair G
Korb Martin
Johnson Carrie
Marzolf Bruz
Aderem Alan
Shmulevich Ilya
Bolouri Hamid
author_sort Zak Daniel
collection DOAJ
description <p>Abstract</p> <p>Background</p> <p>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 <url>http://www.innateImmunity-systemsbiology.org</url>. 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.</p> <p>Description</p> <p>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.</p> <p>Conclusion</p> <p>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 <url>http://db.systemsbiology.net/IIDB</url>.</p>
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spelling doaj.art-c931b141fdfc498ba2fbfc754e45ad892022-12-22T02:48:51ZengBMCBMC Immunology1471-21722008-03-0191710.1186/1471-2172-9-7The Innate Immune Database (IIDB)Zak DanielGilchrist MarkRosenberger Carrie MRoach Jared CKennedy Kathleen AHwang DaeheeLi BinBattail ChristopheThorsson VesteinnRust Alistair GKorb MartinJohnson CarrieMarzolf BruzAderem AlanShmulevich IlyaBolouri Hamid<p>Abstract</p> <p>Background</p> <p>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 <url>http://www.innateImmunity-systemsbiology.org</url>. 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.</p> <p>Description</p> <p>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.</p> <p>Conclusion</p> <p>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 <url>http://db.systemsbiology.net/IIDB</url>.</p>http://www.biomedcentral.com/1471-2172/9/7
spellingShingle Zak Daniel
Gilchrist Mark
Rosenberger Carrie M
Roach Jared C
Kennedy Kathleen A
Hwang Daehee
Li Bin
Battail Christophe
Thorsson Vesteinn
Rust Alistair G
Korb Martin
Johnson Carrie
Marzolf Bruz
Aderem Alan
Shmulevich Ilya
Bolouri Hamid
The Innate Immune Database (IIDB)
BMC Immunology
title The Innate Immune Database (IIDB)
title_full The Innate Immune Database (IIDB)
title_fullStr The Innate Immune Database (IIDB)
title_full_unstemmed The Innate Immune Database (IIDB)
title_short The Innate Immune Database (IIDB)
title_sort innate immune database iidb
url http://www.biomedcentral.com/1471-2172/9/7
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