COMBAT-TB-NeoDB: fostering tuberculosis research through integrative analysis using graph database technologies | Zendy

Thoba Lose | Zendy; Peter Van Heusden | Zendy; Alan Christoffels | Zendy

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COMBAT-TB-NeoDB: fostering tuberculosis research through integrative analysis using graph database technologies

Author(s) -

Thoba Lose,

Peter Van Heusden,

Alan Christoffels

Publication year - 2019

Publication title -

bioinformatics

Language(s) - Uncategorized

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btz658

Subject(s) - computer science , leverage (statistics) , tuberculosis , biological database , graph , graph database , data science , knowledge graph , database , ontology , knowledge base , world wide web , information retrieval , bioinformatics , biology , medicine , theoretical computer science , pathology , philosophy , epistemology , machine learning

Recent advancements in genomic technologies have enabled high throughput cost-effective generation of 'omics' data from M.tuberculosis (M.tb) isolates, which then gets shared via a number of heterogeneous publicly available biological databases. Albeit useful, fragmented curation negatively impacts the researcher's ability to leverage the data via federated queries.

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