Development of algorithms to decipher the complexity of chromation organization

Development of algorithms to decipher the complexity of chromation organization

Internship Description

Cells control gene expression by means of dynamic changes in chromatin. Different functional chromatin states are the result of highly combinatorial patterns of DNA- methylation, histone modifications, sequence specific DNA - binding proteins and chromatin accessory factors. The advent of large-scale, high- throughput experiments has resulted in the generation of an immense array of genome association data ( enrichment profiles) of chromatin components. Computational epigenetics is an interdisciplinary area of research that involves the development of computational methods to analyze and conceptionalize large scale epigenomic data. 

At the Chromatin Biochemistry lab, we are developing computational methods for integrative analysis of Big-Data from ,odENCODE (1) to better understand the complexity of (epi) gennomic information. Decoding the increasingly large volumes of Bid-Data sets involves deciphering signal patterns and to systematically quantify the localization of these signal intensities. 

Deliverables/Expectations

​Develop (or assist/apply) computational method for segmentation of genomes using a combination of epigenomic datasets
Application of machine learning techniques to predict the​ 3D architecture of epigenomic segments
Maintain good log (CVS), submit progress in writing and present results
Final report summarizing and explaining all project work. 

Faculty Name

Wolfgang Fischle

Field of Study

​computational biology, bioinformatics, informatics