Project B7

Predicting the constrained evolution of tumors

Andreas Beyer, U Cologne | web | email

This project takes a systems-biology modelling approach to tumor evolution, based on tissue-specific genomic and epigenetic factors influencing mutation rates. Combined with selection estimates from molecular network and pathway data, this project will predict the tissue-specific likelihood of mutations driving tumor evolution.

Predictability in Evolution

Collaborative Research Center 1310


Convergent network effects along the axis of gene expression during prostate cancer progression

Charmpi, K., Guo, T., Zhong, Q. et al., Beyer A., Genome Biol 21, 302, 14. December 2020,

Pyruvate kinase variant of fission yeast tunes carbon metabolism, cell regulation, growth and stress resistance

Kamrad S., Grossbach J., Rodríguez‐López M., Mülleder M., Townsend S.J, Cappelletti V., Stojanovski G., Correia‐Melo C., Picotti P., Beyer A., Ralser M., Bähler J., Mol Syst Biol (2020)16:e9270, 1. April 2020,

Multi-region proteome analysis quantifies spatial heterogeneity of prostate tissue biomarkers

Guo T., Li L., Zhong Q., Rupp N.J., Charmpi K., Wong C.E., Wagner U., Rueschoff J.H., Jochum W., Fankhauser C.D., Saba K., Poyet C., Wild P.J., Aebersold R., Beyer A., Life Science Alliance, 29. May 2018,

regNet: an R package for network-based propagation of gene expression alterations

Seifert M., Beyer A., Bioinformatics Volume 34 Issue 2:308–311, 15. January 2018,

Detection of COPB2 as a KRAS synthetic lethal partner through integration of functional genomics screens

Christodoulou E.G., Yang H., Lademann F., Pilarsky C., Beyer A., Schroeder M., Oncotarget 8:34283-34297, 10. March 2017,