|
|
Project PartnersProf. Dr. Joachim Selbig
Core Competency:Development and application of unsupervised and supervised machine learning methods as well as methods from applied graph theory to the analysis and interpretation of complex biological data.Contribution to work programme: Contribution to Work Programme:WP1: Development and application of databases to manage and store heterogeneous data, of methods to compare protein sequences and structures, to analyse gene expression, metabolite and protein profiles as well as flux data with an emphasis on non-linearity, and to analyse and compare biological networks. GoFORSYS Publications of the Group:Basler, G., Z. Nikoloski, et al. (2008). "Biosynthetic potentials from species-specific metabolic networks." Genome Informatics 20: 135–148. Nikoloski, Z., S. Grimbs, et al. (2008). "Metabolic networks are NP-hard to reconstruct." Journal of Theoretical Biology 254(4): 807-816. Nikoloski, Z., S. Grimbs, et al. (2008). Hardness and approximability of the inverse scope problem. Algorithms in Bioinformatics. 8th International Workshop, WABI 2008, Karlsruhe, Germany, Springer-Verlag. Nikoloski, Z., K. Strassburg, et al. (2008). " Properties of the active subnetworks for Saccharomyces cerevisae reflect temperature stress." PLoS Computational Biology. Nikoloski, Z. and J. Selbig (2008). "Origins of scale-freeness in correlation networks." IEEE/ACM Transactions on Computational Biology and Bioinformatics. Schwenk, B., J. Selbig, et al. (2009). "ExPlanes: Exploring Planes in Profile Data." BMC Systems Biology. |
|