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Functional and Evolutionary Analysis of Yeasts Regulatory Motifs

Student: Sokolov Aleksandr

Supervisor: Mikhail S. Gelfand

Faculty: HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE)

Educational Programme: Applied Mathematics (Bachelor)

Year of Graduation: 2020

The study of transcriptional regulation is one of the relevant areas in bioinformatics. Current work is devoted to search of functional elements and regulatory motifs in yeast based on comparative analysis of a set of closely related genomes (analysis of different strains within same species). Such analysis includes search of conservative islands in the intergenic regions of yeast genomes and the applying of convolutional neural networks (CNN), which show good results in similar problems. Sequences of conservative islands and of features determined by CNN will be checked for potential binding sites of transcription factors (TF). For this purpose, an analysis of overrepresented motifs using MEME [1], and search for binding sites of known TFs using positional weight matrices constructed on the base of TFs binding sites will be used.

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