title: Computational analysis of alternative splicing using EST tissue information.
abstract: 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.
authors.affiliation: Compugen Inc. 7 Centre Drive, Jamesburg, New Jersey 08831, USA. han@cgen.com
authors.forename: Hanqing
authors.initials: H
authors.lastname: Xie
authors.forename: Wei-yong
authors.initials: WY
authors.lastname: Zhu
authors.forename: Alon
authors.initials: A
authors.lastname: Wasserman
authors.forename: Vladimir
authors.initials: V
authors.lastname: Grebinskiy
authors.forename: Andrew
authors.initials: A
authors.lastname: Olson
authors.forename: Liat
authors.initials: L
authors.lastname: Mintz
mesh_terms: 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