Direkt zum InhaltDirekt zur SucheDirekt zur Navigation
▼ Zielgruppen ▼
 

Humboldt-Universität zu Berlin - Mathematisch-Naturwissenschaftliche Fakultät - Wissensmanagement in der Bioinformatik

BCB Seminar

Wednesday, May 24th 2006, 4 - 7 pm
Humboldt-Universität zu Berlin
Insitute of Computer Science




Prof. Dr. Stefan Kramer
Technische Universität München

Data Mining for Structure-Activity Relationships of Non-Congeneric Compounds

In the talk, I will present data mining methods for the induction of structure-activity relationships of non-congeneric compounds. The most basic building blocks come from the area of graph mining. We developed two tools particularly tailored for databases of graphs representing small molecules, FreeTreeMiner and gSpan'. These tools are used in a new instance-based approach to structure-activity relationships. Finally, I will show how the paradigm of structure-activity relationships of non-congeneric compounds can be extended to include biological information.




Dipl.-Inf. Andreas Doms
Bioinformatics Group, TU Dresden

Ontology-based literature mining with GoPubMed

GoPubMed.org is an ontology-based literature search engine, which integrates PubMed and the GeneOntology (GO). It allows users to submit queries to PubMed and to explore the search results with GO. Internally, GoPubMed extracts GO terms from all 15.000.000 PubMed abstracts. This wealth of information is useful to understand research fields and current developments. For each topic represented by a GO term, we show how many articles were published over time, which authors are most prolific for the topic, which journals cover the topic best, and which countries publish most on the topic. Furthermore, we analyse journals, authors and places and can show their publishing activity over time and the topics covered.




Prof. Dr. An-Ping Zeng
Technische Universität Hamburg-Harburg

Rekonstruktion und Analyse genom-weiter metabolischer und regulatorischer Netzwerke.

Recent advances in genome sequencing and functional genomics make it now possible to reconstruct large-scale biological networks at different molecular levels. Studies of these genome scale networks have revealed several intrinsic structural and functional properties (e.g. power law and bow-tie structure) of biological systems. In this presentation, a brief overview will be first given on the reconstruction and structural analysis of metabolic and regulatory networks from genomic and functional genomic data. With the example of E. coli I will show in more detail that an integrated analysis of metabolic, regulatory and protein-protein interaction networks is particularly important for understanding both cellular metabolism and its regulation at a systems level. Some of our network-based studies of pathogens (e.g. Pseudomonas aeruginosa), industrially relevant organisms (e.g. yeast and Bacilli) and human cells will be also briefly highlighted, especially with respect to the analysis of transcriptomic and dynamic data.




Guests are welcome!

Rudower Chaussee 25
12489 Berlin
Humboldt-Kabinett