A Semiautomated Approach to Gene Discovery Through Expressed Sequence Tag Data Mining: Discovery of New Human Transporter Genes

Overview

Journal AAPS PharmSci

Specialty Pharmacology

Date 2003 Apr 26

PMID 12713273

Citations 4

Authors

Shoshana Brown

Jean L Chang

Wolfgang Sadee

Patricia C Babbitt

Affiliations

Soon will be listed here.

Abstract

Identification and functional characterization of the genes in the human genome remain a major challenge. A principal source of publicly available information used for this purpose is the National Center for Biotechnology Information database of expressed sequence tags (dbEST), which contains over 4 million human ESTs. To extract the information buried in this data more effectively, we have developed a semiautomated method to mine dbEST for uncharacterized human genes. Starting with a single protein input sequence, a family of related proteins from all species is compiled. This entire family is then used to mine the human EST database for new gene candidates. Evaluation of putative new gene candidates in the context of a family of characterized proteins provides a framework for inference of the structure and function of the new genes. When applied to a test data set of 28 families within the major facilitator superfamily (MFS) of membrane transporters, our protocol found 73 previously characterized human MFS genes and 43 new MFS gene candidates. Development of this approach provided insights into the problems and pitfalls of automated data mining using public databases.

Citing Articles

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