title: Leveraging health social networking communities in translational research.
abstract: Health social networking communities are emerging resources for translational research. We have designed and implemented a framework called HyGen, which combines Semantic Web technologies, graph algorithms and user profiling to discover and prioritize novel associations across disciplines. This manuscript focuses on the key strategies developed to overcome the challenges in handling patient-generated content in Health social networking communities. Heuristic and quantitative evaluations were carried out in colorectal cancer. The results demonstrate the potential of our approach to bridge silos and to identify hidden links among clinical observations, drugs, genes and diseases. In Amyotrophic Lateral Sclerosis case studies, HyGen has identified 15 of the 20 published disease genes. Additionally, HyGen has highlighted new candidates for future investigations, as well as a scientifically meaningful connection between riluzole and alcohol abuse.
authors.affiliation: School of Informatics, Indiana University Purdue University, IN, USA. yuwang@umail.iu.edu
authors.forename: Yue W
authors.initials: YW
authors.lastname: Webster
authors.forename: Ernst R
authors.initials: ER
authors.lastname: Dow
authors.forename: Jacob
authors.initials: J
authors.lastname: Koehler
authors.forename: Ranga C
authors.initials: RC
authors.lastname: Gudivada
authors.forename: Mathew J
authors.initials: MJ
authors.lastname: Palakal
mesh_terms: D000465:Algorithms; D000690:Amyotrophic Lateral Sclerosis / Q000235:genetics; D015179:Colorectal Neoplasms / Q000235:genetics; D019058:Community Networks; D019295:Computational Biology / Q000379:methods*; D004194:Disease / Q000235:genetics; D006801:Humans; D020407:Internet; D008962:Models, Theoretical; D012660:Semantics; D012944:Social Support; D057170:Translational Research, Biomedical / Q000379:methods*