Display Full Text | Download Full Text
373.45 kB PDF file

Degree

Master of Science, Miami University, Computer Science and Systems Analysis, 2011.

Abstract

This thesis presents several new algorithmic approaches to the problem of clustering conventional ESTs and high throughput gene expression data, which are implemented in the software tool PEACE. The d2 algorithm for sequence comparison is improved and enhanced with a novel two-pass extension, and a minimum spanning tree-based algorithm is used to cluster ESTs, providing an efficient and accurate solution. Furthermore, in order to address the unique challenges of high throughput sequencing technologies such as 454, Illumina and SOLiD sequencing, an adaptive d2 algorithm is introduced to handle variations in fragment length. The resulting tool compares favorably with other leading tools in the literature, including WCD, CAP3, and TGICL, on both EST and next-generation sequencing (NGS) data.

Subject Headings

Bioinformatics; Computer Science

Keywords

clustering gene expressions; EST

Committee / Advisors

John Karro, PhD (Advisor)
Dhananjai Rao, PhD (Committee Member)
Mufit Ozden, PhD (Committee Member)

Pages

40p.

Document number: miami1303482998
Permalink: http://rave.ohiolink.edu/etdc/view?acc_num=miami1303482998

This ETD has been downloaded 70 times (through March 2013)