Date of Publication

5-9-2017

Degree Type

Honors Thesis

Department

Biology

First Advisor

Dr. Rongkun Shen, Associate Professor, Biology

Abstract

MicroRNAs are very short non-coding RNAs. Since microRNAs play important roles in many biological process, the research of microRNAs is a burgeoning field with much promise. Due to the high cost of experimental approaches, many computational techniques and algorithms have been implemented to study microRNAs. However, current methods for determining the targets for miRNAs are far from accurate. To address this issue, we developed algorithms that produced profiles of miRNA recognition elements and features such binding energy threshold and conservation score. These profiles will be used to train a machine learning algorithm for miRNA target prediction.

Available for download on Thursday, July 12, 2018

Included in

Biology Commons

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