Guilherme Viteri

TL;DR: Through the use of highly optimised, in-memory data structures and algorithms, Reactome has achieved a stable, high performance pathway analysis service, enabling the analysis of genome-wide datasets within seconds, allowing interactive exploration and analysis of high throughput data.

TL;DR: The Reactome Knowledgebase as mentioned in this paper provides manually curated molecular details across a broad range of physiological and pathological biological processes in humans, including both hereditary and acquired disease processes, annotated as an ordered network of molecular transformations in a single consistent data model.

TL;DR: The Neo4j graph database and its query language, Cypher, provide efficient access to the complex Reactome data model, facilitating easy traversal and knowledge discovery and the Reactome graph database use case shows the power of NoSQL database engines for complex biological data types.

TL;DR: New developments in the Reactome visualization system are presented that facilitate navigation through the pathway hierarchy and enable efficient reuse of Reactome visualizations for users’ own research presentations and publications.

TL;DR: ReactomeGSA is used to characterize the role of B cells in anti-tumor immunity and greatly reduces the technical barrier for multi-omics, cross-species, comparative pathway analyses.