A computational/functional genomics approach for the enrichment of the retinal transcriptome and the identification of positional candidate retinopathy genes.

ABSTRACT: Grouping genes by virtue of their sequence similarity, functional association, or spatiotemporal distribution is an important first step in investigating function. Given the recent identification of >30,000 human genes either by analyses of genomic sequence or by derivation/assembly of ESTs, automated means of discerning gene function and association with disease are critical for the efficient processing of this large volume of data. We have designed a series of computational tools to manipulate the EST sequence database (dbEST) to predict EST clusters likely representing genes expressed exclusively or preferentially in a specific tissue. We implemented this tool by extracting 40,000 human retinal ESTs and performing in silico subtraction against 1.4 million human ESTs. This process yielde

SUBMITTER: Katsanis N 

PROVIDER: S-EPMC137883 | biostudies-literature | 2002 Oct

REPOSITORIES: biostudies-literature