InnateDB: facilitating systems‐level analyses of the mammalian innate immune response |
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Authors: | David J Lynn Geoffrey L Winsor Calvin Chan Nicolas Richard Matthew R Laird Aaron Barsky Jennifer L Gardy Fiona M Roche Timothy H W Chan Naisha Shah Raymond Lo Misbah Naseer Jaimmie Que Melissa Yau Michael Acab Dan Tulpan Matthew D Whiteside Avinash Chikatamarla Bernadette Mah Tamara Munzner Karsten Hokamp Robert E W Hancock Fiona S L Brinkman |
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Affiliation: | 1. Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, British Columbia, Canada;2. Centre for Microbial Diseases and Immunity Research, University of British Columbia, Vancouver, British Columbia, Canada;3. Department of Computer Science, University of British Columbia, Vancouver, British Columbia, Canada;4. Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Ireland |
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Abstract: | Although considerable progress has been made in dissecting the signaling pathways involved in the innate immune response, it is now apparent that this response can no longer be productively thought of in terms of simple linear pathways. InnateDB ( www.innatedb.ca ) has been developed to facilitate systems‐level analyses that will provide better insight into the complex networks of pathways and interactions that govern the innate immune response. InnateDB is a publicly available, manually curated, integrative biology database of the human and mouse molecules, experimentally verified interactions and pathways involved in innate immunity, along with centralized annotation on the broader human and mouse interactomes. To date, more than 3500 innate immunity‐relevant interactions have been contextually annotated through the review of 1000 plus publications. Integrated into InnateDB are novel bioinformatics resources, including network visualization software, pathway analysis, orthologous interaction network construction and the ability to overlay user‐supplied gene expression data in an intuitively displayed molecular interaction network and pathway context, which will enable biologists without a computational background to explore their data in a more systems‐oriented manner. |
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