Processing of Chromosome Conformance Capture (3C/Hi-C) Data
Im Rahmen des Projekts Bioinformatics


keywords: bioinformatics, 3c, hic, data compression, 3d reconstruction, resolution enhancement.

The structure of genomes in three-dimensional (3D) space is crucial for DNA replication, genome stability, and tissue differentiation. It helps us to understand the complex system of epigenetic activities. Chromosome Conformation Capture (3C) quantifies the interaction between two specific loci (genomic regions), while Hi-C quantifies all interactions between all possible pairs of loci on all chromosomes simultaneously. The scale of a Hi-C experiment allows us to identify of long-range interactions. Unfortunately, the raw 3C and Hi-C data contain not only missing data but also noisy data. Therefore, in order to use the data for an analysis, a further processing is required. In this project, we are developing machine learning and deep learning models for the preprocessing purposes to improve the quality of the data. In addition, the sheer number of interactions generates a huge amount of data. We are also developing algorithms to store the data efficiently.

Focus of this project are:
  • Data Compression
  • 3D Reconstruction
  • Resolution Enhancement
Readings (all papers are open access):

In this project I have regular opportunities to offer (thesis, hiwi, etc.). Explicit topics for a thesis that I give out is individualized and on request, if available. If you are motivated and interested in this project, please send me a short email with the most important information about you and why you are interested. The following knowledge, qualities and experiences are helpful for the thesis:


  • Motivated
  • Can work independently
  • Knowledge:
  • Good programming skill:
    • Python
      • Numpy
      • Pandas
      • Scipy
      • (depends on topic) Sklearn
      • (depends on topic) PyTorch
    • (depends on topic) C++

Contact person: Yeremia G. Adhisantoso