Bioinformatics And Proteomic Approaches To Disease: In Vivo And In Silico Proteome Analysis Tools 879-886
Correspondence
Fakher Rahim Msc. Bioinformatics, Physiology research Center, Ahwaz Jondishapur University of Medical Sciences, Ahwaz, Iran.
The availability of human genome sequences and transcriptomic, proteomic, and metabolomic data provides us with a challenging opportunity to develop computational approaches for systematic analysis of metabolic disorders. Mass spectrometry represents an important set of in vivo technologies for protein expression measurement. Among them, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI TOF-MS), because of its high throughput and on-chip sample processing capability, has become a popular tool for clinical proteomics. Bioinformatics plays a critical role in the analysis of SELDI data, and therefore, it is important to understand the issues associated with the analysis of proteomic data. A variety of protein sequence databases exist, ranging from simple sequence repositories, which store data with little or no manual intervention in the creation of the records, to expertly curated universal databases that cover all species, and in which the original sequence data are enhanced by the manual addition of further information in each sequence record. As the focus of researchers moves from the genome to the proteins encoded by it, these databases play an even more important role as central comprehensive resources of protein information. In this review, we discuss such issues and the bioinformatics strategies and several leading protein sequence databases used for proteomic in silico analysis technologies associated with in vivo techniques.