title: Challenges and opportunities for oncology biomarker discovery.
abstract: Recent success of companion diagnostics along with the increasing regulatory pressure for better identification of the target population has created an unprecedented incentive for drug discovery companies to invest in novel strategies for biomarker discovery. In parallel with the rapid advancement and clinical adoption of high-throughput technologies, a number of knowledge management and systems biology approaches have been developed to analyze an ever increasing collection of OMICs data. This review discusses current biomarker discovery technologies highlighting challenges and opportunities of knowledge capturing and presenting a perspective of the future integrative modeling approaches as an emerging trend in biomarker prediction.
authors.affiliation: Knowledge Management, Merck Serono, 250 Frankfurterstrasse, Darmstadt 64293, Germany.
authors.forename: Avisek
authors.initials: A
authors.lastname: Deyati
authors.forename: Erfan
authors.initials: E
authors.lastname: Younesi
authors.forename: Martin
authors.initials: M
authors.lastname: Hofmann-Apitius
authors.forename: Natalia
authors.initials: N
authors.lastname: Novac
mesh_terms: D000818:Animals; D014408:Biomarkers, Tumor / Q000032:analysis* / Q000235:genetics; D035843:Biomedical Research / Q000379:methods*; D057225:Data Mining; D005819:Genetic Markers; D023281:Genomics; D057166:High-Throughput Screening Assays; D006801:Humans; D051188:Knowledge Bases; D008495:Medical Oncology / Q000379:methods*; D055432:Metabolomics; D009369:Neoplasms / Q000737:chemistry* / Q000235:genetics / Q000473:pathology / Q000628:therapy; D011237:Predictive Value of Tests; D011379:Prognosis; D040901:Proteomics; D049490:Systems Biology
chemical_list: D014408:Biomarkers, Tumor; D005819:Genetic Markers