Kratika Sunil Naskulwar
M.Sc. Thesis Proposal
Supervisor: Dr. Lourdes Pena-Castillo

sRNA Target Prediction

Department of Computer Science
Friday, September 20, 2019, 12:00 p.m., Room EN 2022

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Abstarct

Bacterial small regulatory RNAs (sRNAs) play a vital role in the regulation of gene expression in
bacteria. sRNAs influence gene expression by interacting with mRNAs or proteins. Bacterial sRNAs are involved in a variety of processes such as environmental stress response, metabolism, and virulence. To understand the functional roles of sRNAs, we need to identify the mRNAs and/or proteins that these sRNAs interact with. These mRNAs or proteins are called targets of the sRNAs. There are several computational tools available for sRNA target prediction, however, these tools have a high number of false positives and hence there is room to increase their accuracy. This research project focuses on building up a machine learning-based method for sRNA target prediction that improves over existing tools. As a result of this research project, a more accurate method for sRNA target prediction will be developed, applicable to any bacterium.