Guan Lab

Department of Computational Medicine & Bioinformatics
Sat, 04/23/2016 - 16:25 -- gyuanfan
TitleA proteogenomic approach to understand splice isoform functions through sequence and expression-based computational modeling.
Publication TypeJournal Article
Year of Publication2016
AuthorsLi H-D, Omenn GS, Guan Y
JournalBrief Bioinform
Date Published2016 Jan 6
ISSN1477-4054
Abstract

The products of multi-exon genes are a mixture of alternatively spliced isoforms, from which the translated proteins can have similar, different or even opposing functions. It is therefore essential to differentiate and annotate functions for individual isoforms. Computational approaches provide an efficient complement to expensive and time-consuming experimental studies. The input data of these methods range from DNA sequence, to RNA selection pressure, to expressed sequence tags, to full-length complementary DNA, to exon array, to RNA-seq expression, to proteomic data. Notably, RNA-seq technology generates quantitative profiling of transcript expression at the genome scale, with an unprecedented amount of expression data available for developing isoform function prediction methods. Integrative analysis of these data at different molecular levels enables a proteogenomic approach to systematically interrogate isoform functions. Here, we briefly review the state-of-the-art methods according to their input data sources, discuss their advantages and limitations and point out potential ways to improve prediction accuracies.

DOI10.1093/bib/bbv109
Alternate JournalBrief. Bioinformatics
PubMed ID26740460