Reactome: An Open Knowledgebase of Human Pathways

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Project Summary We seek renewal of the core operating funding for the Reactome Knowledgebase of Human Biological Pathways and Processes. Reactome is a curated, open access biomolecular pathway database that can be freely used and redistributed by all members of the biological research community. It is used by clinicians, geneti- cists, genomics researchers, and molecular biologists to interpret the results of high-throughput experimental studies, by bioinformaticians seeking to develop novel algorithms for mining knowledge from genomic studies, and by systems biologists building predictive models of normal and disease variant pathways. Our curators, PhD-level scientists with backgrounds in cell and molecular biology work closely with in- dependent investigators within the community to assemble machine-readable descriptions of human biological pathways. Each pathway is extensively checked and peer-reviewed prior to publication to ensure its assertions are backed up by the primary literature, and that human molecular events inferred from orthologous ones in animal models have an auditable inference chain. Curated Reactome pathways currently cover 8930 protein- coding genes (44% of the translated portion of the genome) and ~150 RNA genes. We also offer a network of reliable ‘functional interactions’ (FIs) predicted by a conservative machine-learning approach, which covers an additional 3300 genes, for a combined coverage of roughly 60% of the known genome. Over the next five years, we will: (1) curate new macromolecular entities, clinically significant protein sequence variants and isoforms, and drug-like molecules, and the complexes these entities form, into new reac- tions; (2) supplement normal pathways with alternative pathways targeted to significant diseases and devel- opmental biology; (3) expand and automate our tools for curation, management and community annotation; (4) integrate pathway modeling technologies using probabilistic graphical models and Boolean networks for pathway and network perturbation studies; (5) develop additional compelling software interfaces directed at both computational and lab biologist users; and (6) and improve outreach to bioinformaticians, molecular bi- ologists and clinical researchers.