title: Network analysis has diverse roles in drug discovery.
abstract: Computational biologists use network analysis to uncover relationships between various data types of interest for drug discovery. For example, signalling and metabolic pathways are commonly used to understand disease states and drug mechanisms. However, several other flavours of network analysis techniques are also applicable in a drug discovery context. Recent advances include networks that encompass relationships between diseases, molecular mechanisms and gene targets. Even social networks that mirror interactions within the scientific community are helping to foster collaborations and novel research. We review how these different types of network analysis approaches facilitate drug discovery and their associated challenges.
authors.affiliation: GlaxoSmithKline, Computational Biology, Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, UK. samiul.x.hasan@gsk.com
authors.forename: Samiul
authors.initials: S
authors.lastname: Hasan
authors.forename: Bhushan K
authors.initials: BK
authors.lastname: Bonde
authors.forename: Natalie S
authors.initials: NS
authors.lastname: Buchan
authors.forename: Matthew D
authors.initials: MD
authors.lastname: Hall
mesh_terms: D019295:Computational Biology; D055808:Drug Discovery; D006801:Humans; D025941:Protein Interaction Mapping; D015398:Signal Transduction; D012944:Social Support