menu
  • Summary
  • Team

Project INF

Principal Investigators: Dr. Ekaterina Shelest, Prof. Dr. Reinhard Guthke

Information Infrastructure / Pattern Recognition


This project is to support the web-based sharing and exchange of data, models and expertise across the ChemBioSys consortium to provide an integrated platform to foster the collaboration between the project partners. Within INF, experimental data (i.e., the raw data together with metadata and pre-processed data) will be managed, stored and processed in standardized manner using the data warehouse that will be embedded in a SYSMO-DB compatible way (seek.sysmo-db.org/).

Data flow between the project areas and the role of INF.

Moreover, INF will provide integrated analysis of different data by mathematical modeling for further discussion, interpretation and to draw conclusions for follow-up experiments. Pattern recognition and machine learning methods will be applied to predict chemical structure of yet unknown secondary metabolites. Network model inference will support the understanding of the roles of chemical mediators in structuring communities. The context-dependent and diverse interaction of chemical mediators in complex biosystems of bacterial, fungal, microalgal, plant, animal and even human cells will be analyzed and modeled to understand its roles in structuring communities. That includes the analysis of transcriptome, proteome and metabolome data as well as the modeling of gene regulation. Pattern recognition and computational modeling will help to unveil new chemical entities, in particular secondary metabolites, and offer new strategies to modulate and control consortia. Pattern recognition and network modeling together with model-based experimental design will direct to experimentally investigate the structure, regulation, activity and function of natural products within complex biotic and abiotic communities. Finally, pattern recognition and network modeling will provide a comprehensive overview on the mode of action of natural products that shape complex communities.

 

login INTRANET

Team INF

Dr. Ekaterina Shelest


Systems Biology and Bioinformatics

Leibniz Institute for Natural Product Research and Infection Biology – Hans-Knöll-Institute

homepage
email

Prof. Dr. Reinhard Guthke


Systems Biology and Bioinformatics

Leibniz Institute for Natural Product Research and Infection Biology – Hans-Knöll-Institute

homepage
email

Ing. Wolfgang Schmidt-Heck


Systems Biology and Bioinformatics

Leibniz Institute for Natural Product Research and Infection Biology – Hans-Knöll-Institute

email

Sagar Gore


Systems Biology and Bioinformatics

Leibniz Institute for Natural Product Research and Infection Biology – Hans-Knöll-Institute

email