UTR prediction programs for trypanosoma brucei

In the past few years, the field of bioinformatics has seen a rapid increase in the need for use of various sequence analysis tools. As we advance in the fields of science and technology, new programs and software are constantly being developed in this field. Rapidly expanding gene sequence databases and rapidly evolving sequence analysis tools are providing researchers with ways to search for highly similar query sequences whether they are nucleotide, protein, or gene databases. This thesis will focus on sequence alignment tools, specifically concentrating on tools that help determine/predict non-coding regions of sequences also known as untranslated regions of sequence or UTRs. These regions tend to exhibit less cross-species conservation than do coding sequences. There are many software packages available today for use in determining UTRs, most of which are only available for use by not-for-profit organizations such as universities. Such programs include BLAST and ORBIT. However, not all tools are the same, requiring the researcher to modify each query accordingly. In addition, not all tools give the same results back to a specific query, some lack flexibility, and others lack user-friendliness. So how does a scientist know which one to choose? Which one is more accurate and how often is it accurate? These are the questions this thesis will answer, by running sequences on both platforms and checking the results against PatSearch.

Name thesis:degree_name

Master of Science in Computational Biology - (M.S.)

Discipline thesis:degree_discipline

Computer Science

Year

2008

Author dc:creator

• Moutafis, Maria

Contributors dc:contributor

• Jason T. L. Wang
• Vincent Oria
• Dimitri Theodoratos

• Gene sequencing
• Untranslated regions of sequence
• Biostatistics
• Computer Sciences

Repository record dc:identifier

https://digitalcommons.njit.edu/theses/331

OAI identifier oai:identifier

oai:digitalcommons.njit.edu:theses-1330