RTG 2424/1: Computational Methods for Oncology, Team Leser

Recent advances in DNA sequencing and molecular profiling have triggered a major shift in cancer research. Traditional coarse-grained and phenomenological examinations and therapy decisions are replaced by individualized approaches that integrate molecular insights on tumor etiology and progression. Various forms of systematic molecular profiling of tumors combined with complex computational analyses are increasingly used to stratify patients and to devise suitable therapies. This shift has triggered a dramatic increase in the importance of computational methods in cancer research, as more and more complex, increasingly large, and ever more heterogeneous data sets must be properly integrated and analyzed to ultimately extract actionable biomedical and clinical knowledge. Development and application of such methods requires profound knowledge in both molecular biology and clinical aspects of cancer, as well as in advanced computational biology. This poses a major challenge for graduate education, as such future ‘computational oncologists’ need state-of-the-art supervision and training not only in computational sciences, mathematics, and statistics, but also in acquiring a thorough understanding of translational research, clinical issues and molecular biology. Here we propose the establishment of a research training group (RTG) on computational ap-proaches in cancer research. Within our program, all students will work on computational research problems targeting research questions in precision oncology. As such research requires the close interaction of various disciplines, the proposed graduate program Comp-Cancer builds on an interdisciplinary faculty who’s expertise ranges from computer science to bioinformatics and systems biology/systems medicine to molecular biology, molecular pathology and clinical oncology. All students will be co-supervised by a least one expert in computational research in oncology and by one clinical/experimental researcher, ensuring expert supervision in both areas. A specifically designed training program will ensure that PhD students become experts in computational biology and gaining an expert understanding of cancer biology and its translational aspects.

Leser, Ulf Prof. Dr.-Ing. (Details) (Knowledge Management in Bioinformatics)

DFG: Graduiertenkollegs - Beteiligungen

Duration of Project
Start date: 06/2019
End date: 11/2023

Research Areas
Bioinformatics and Theoretical Biology

Research Areas
Bioinformatik, Onkologie, Systemmedizin, Translationale Medizin

Last updated on 2020-01-06 at 19:56