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.
journal_name
Brief Bioinformjournal_title
Briefings in bioinformaticsauthors
Li HD,Omenn GS,Guan Ydoi
10.1093/bib/bbv109subject
Has Abstractpub_date
2016-11-01 00:00:00pages
1024-1031issue
6eissn
1467-5463issn
1477-4054pii
bbv109journal_volume
17pub_type
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