CCSR group

The analysis of the complexity of the biological cell is a tricky adventure and still far from being accomplished. The type diversity of molecular players as well as the number diversity of each molecular player spans an enormous combinatorial space. The expression and type variability reflects the biochemical nature of the system and the fine granulated structure of these highly parallelized biochemical reaction networks, fine tuned by a continuum of modifiers/ modifier mechanisms echoing cross-connectivity in-between these cellular sub-networks. The observed mechanisms exhibit a lot of analogies to other complex systems like the human society. Therefore insight into biological systems might also inspire concepts in other sciences and vice versa. We present here some of our activities, put them into a broader context and try to establish a structured archive of our research knowledge.
The basic research effort of our independent group is centered around the biological reaction networks and how they form this robust and adaptive cellular system. For that, we build on i.a. the analysis of expression/ sequence data sets and accompanying simulation studies. The generated mechanistic insights will be employed especially to understand cancer formation and progression in breast and bone cancers. A minor focus deals with the definition of biological marker panels useful in diagnostics. Details of our work can be found amongst others in the section 'RESEARCH--Publications'.

Genetics Congress 2018

Genetics Congress 2018, Tehran, Congress Dome

Rare Disease Meeting Frankfurt

'Rare Disease' Meeting Frankfurt, Georg-Speyer-Building

Rare Disease Meeting Frankfurt

+SysBio TNLIST+CAS MPG+Life Sci Fudan+Statistics Zhejiang+

Sarcom Conference 2014

Sarcom Conference 2014, Berlin

Cancer Biology, Cancer Progression, Systems Biology, Bioinformatics and Computational Biology, Gene Regulation, Gene Expression, Genomics, Biological Networks, Regulation Mechanisms, Biostatistics, Simulation Studies, R, Fortran, C, Next Generation Sequencing, Tissue Microarrays.

Cellular networks associated with our publications:

Osteosarcoma Cell Proliferation:
metabolic miR and TF
signaling miR and TF
co-regulatory network.

Osteosarcoma: get rid of the heterogenous karyotype - look on copy number based functional modules.

Ewing sarcoma: side population with stem cell like features.

academic discourse
Interdependencies in TMA data

get publication :    arXiv