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Study of Transcriptional Fators (TF) in multi-omic single-cell data, for the construction of enhancer-gene links

keywords BIOINFORMATICS, COMPUTATIONAL BIOLOGY, SINGLE-CELL DATA

Reference persons STEFANO DI CARLO

External reference persons Lorenzo Martini

Research Groups DAUIN - GR-24 - SMILIES - reSilient coMputer archItectures and LIfE Sci

Thesis type RESEARCH

Description The main objective of the thesis is to investigate the role of transcription factors in the regulation of gene expression at the single-cell level. In particular, the aim is to explore how transcription factors interact with enhancers and how these interactions influence gene expression. To achieve this goal, single-cell multi-omics data will be used, including information on gene expression and chromatin accessibility. The thesis will first investigate the tools and types of data available in the literature, and then define an approach to the problem. Generally, data will be analyzed using machine learning techniques, and models will be created to investigate correlations between the various elements. The results of this thesis could be used to improve understanding of gene expression regulation at the single-cell level and to identify new therapeutic targets for diseases involving gene expression regulation.

Therefore, the candidate is required to have a strong commitment and willingness to undertake a true research experience in bioinformatics

Required skills Basic knowledge of machine learning is also required, as well as a preferable understanding of R and/or Python.


Deadline 21/04/2024      PROPONI LA TUA CANDIDATURA




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