Computational analysis of alternative splicing using EST tissue information.
Expressed sequence tags (ESTs) from normal and tumor tissues have been deposited in public databases. These ESTs and all mRNA sequences were aligned with the human genome sequence using LEADS, Compugen's alternative splicing modeling platform. We developed a novel computational approach to analyze tissue information of aligned ESTs in order to identify cancer-specific alternative splicing and gene segments highly expressed in particular cancers. Several genes, including one encoding a possible pre-mRNA splicing factor, displayed cancer-specific alternative splicing. In addition, multiple candidate gene segments highly expressed in colon cancers were identified.
Xie
Hanqing
H
Compugen Inc. 7 Centre Drive, Jamesburg, New Jersey 08831, USA. han@cgen.com
Zhu
Wei-yong
WY
Wasserman
Alon
A
Grebinskiy
Vladimir
V
Olson
Andrew
A
Mintz
Liat
L
D017398:Alternative Splicing; D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D020224:Expressed Sequence Tags; D015723:Gene Library; D015894:Genome, Human; D006801:Humans; D009928:Organ Specificity / Q000235:genetics