@article{2702, keywords = {Humans, Signal Transduction, Computational Biology, Algorithms, Reproducibility of Results, Internet, Host-Pathogen Interactions, Transcriptome, Protein Interaction Maps, Protein Interaction Mapping, Gene Regulatory Networks, Bayes Theorem, Immune System, Immune System Diseases, Support Vector Machine, Virus Diseases}, author = {Dmitriy Gorenshteyn and Elena Zaslavsky and Miguel Fribourg and Christopher Park and Aaron Wong and Alicja Tadych and Boris Hartmann and Randy Albrecht and Adolfo Garc{\'\i}a-Sastre and Steven Kleinstein and Olga Troyanskaya and Stuart Sealfon}, title = {Interactive Big Data Resource to Elucidate Human Immune Pathways and Diseases.}, abstract = {

Many functionally important interactions between genes and proteins involved in immunological diseases and processes are unknown. The exponential growth in public high-throughput data offers an opportunity to expand this knowledge. To unlock human-immunology-relevant insight contained in the global biomedical research effort, including all public high-throughput datasets, we performed immunological-pathway-focused Bayesian integration of a comprehensive, heterogeneous compendium comprising 38,088 genome-scale experiments. The distillation of this knowledge into immunological networks of functional relationships between molecular entities (ImmuNet), and tools to mine this resource, are accessible to the public at http://immunet.princeton.edu. The predictive capacity of ImmuNet, established by rigorous statistical validation, is easily accessed by experimentalists to generate data-driven hypotheses. We demonstrate the power of this approach through the identification of unique host-virus interaction responses, and we show how ImmuNet complements genetic studies by predicting disease-associated genes. ImmuNet should be widely beneficial for investigating the mechanisms of the human immune system and immunological diseases.

}, year = {2015}, journal = {Immunity}, volume = {43}, pages = {605-14}, month = {2015 Sep 15}, issn = {1097-4180}, doi = {10.1016/j.immuni.2015.08.014}, language = {eng}, }