Automation of Processing NCBI Information for SNP study

Author: Shut-yee Jessica Yeung

Primary Advisor: Craig L. Harris, PhD (co-author)

Committee Members:

Masters thesis, The University of Texas Health Science Center School of Health Information Sciences at Houston.

Abstract:

Transferring and selecting SNPs data from the National Center for Biotechnology Information (NCBI) website in a high throughput manner was explored. By applying Perl, a programming environment and language, to fetch and select data from the NCBI website reduces data acquisition time, improves accuracy and keeps data up-to-date. Many of these data analytical tasks were usually done manually by biologists, yet most of these tasks can be automated with current technology to advance both the speed of getting and processing data, and the data quality. A case study which involved SNP identification was carried out to show how we can use the available technology and information to maximize the efficiency of biomedical research.