New sequencing technologies
give rise to implement more efficient and adapted algorithms for the analysis
of sequences. The development of new methods that help to detect diseases
like cancer on the basis of -omics data will be an interesting and challenging
task for me. Considering that, I can imagine to extract disease-specific signals
from the sequences by using various statistical approaches.
2010-1013: Dual Programme: Bachelor of Science in Scientific Programming at University of Applied Sciences Aachen, Campus Jülich;
2013-2016: Master of Science in Bioinformatics at University of Hamburg
since 2016: PhD student at IMPRS-CBSC supervised by Prof. Dr. Knut Reinert
- K Reinert, TH Dadi, M Ehrhardt, H Hauswedell, S Mehringer, R Rahn, J
Kim, C Pockrandt, J Winkler, E Siragusa, G Urgese, D Weese (2017). The
SeqAn C++ template library for efficient sequence analysis: A
resource for programmers.
J Biotechnol., 261: 157-168
Organizational Unit (Department, Group, Facility):
- International Max Planck Research School for Computational Biology and Scientific Computing