title: Computational proteomics: designing a comprehensive analytical strategy.
abstract: The proper combination of proteomics with bioinformatics is highly synergistic, capable of propelling proteomics into a truly high-throughput platform. However, appropriate experimental design and analytical considerations are needed to maximize analytical outcome. This review highlights key issues and caveats in converting raw data to protein identifications, and subsequently biological insight. It offers some insights on how the establishment of highly robust proteomics pipelines can be used for studying novel areas such as computational epigenetics, high performance functional studies and new discovery paradigms for drug targets and biomarkers.
authors.affiliation: Department of Computer Science, National University of Singapore, COM1 Building, 13 Computing Drive, Singapore 117417, Singapore; Department of Computing, Imperial College London, Exhibition Road, London SW7 2AZ, UK.
authors.forename: Wilson Wen Bin
authors.initials: WW
authors.lastname: Goh
authors.affiliation: Department of Computer Science, National University of Singapore, COM1 Building, 13 Computing Drive, Singapore 117417, Singapore. Electronic address: wongls@comp.nus.edu.sg.
authors.forename: Limsoon
authors.initials: L
authors.lastname: Wong
mesh_terms: D015415:Biomarkers / Q000378:metabolism; D019295:Computational Biology / Q000379:methods*; D015195:Drug Design; D044127:Epigenesis, Genetic; D057166:High-Throughput Screening Assays / Q000379:methods; D006801:Humans; D058990:Molecular Targeted Therapy; D011506:Proteins / Q000737:chemistry; D040901:Proteomics / Q000379:methods*
chemical_list: D015415:Biomarkers; D011506:Proteins