Presentations

Background: One of the major challenges in complex multi-disciplinary systems biology projects is to understand and process data from a wide variety of data sources. Computational tools to assist in the analysis of this data are essential.
Method: LigDig is a web server designed to answer questions that previously required several independent queries to diverse data sources. It also performs basic manipulations and analyses of the structures of protein–ligand complexes. The LigDig webserver is
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Talk at Jena Centre for Bioinformatics, 2014-11-20

Presentation at VPH 2014

Talk given at ISGSB 2014 in Durham (UK)

Presentation at WCCM-ECCM-ECFD 2014

Poster for VLN Retreat 2013 in Hünfeld

presentation at SBMC2014

The Portal:
6 dimensions to organize content
easy information about difficult topics
quick and easy to publish the input
visibility to the public, colleagues and funders
presentation of the work of group

Invited talk abstract:

Recent successes have challenged the widely held belief that protein-protein interactions (PPIs) are 'undruggable'. We show that binding pockets defining PPIs and those that define protein-ligand interactions of currently marketed drugs are markedly different. In the case of PPIs, drug discovery methods that simultaneously target several small pockets at the protein-protein interface are likely to increase the chances of success in this new and important field of therapeutics.
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ChemSpot is a named entity recognition tool for identifying mentions of chemicals in natural language texts, including trivial names, drugs, abbreviations, molecular formulas and IUPAC entities. Since the different classes of relevant entities have rather different naming characteristics, ChemSpot uses a hybrid approach combining a Conditional Random Field with a dictionary. It currently achieves an F1 measure of 74.2% on the SCAI corpus.
ChemSpot is released under the Common Public License 1.0.
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The BioCreative IV CHEMDNER Task provides participants with the opportunity to compare their methods for chemical named entity recognition (NER) and indexing in a controlled environment. We contributed to this task with our previous conditional random field based system [1] extended by a number of novel general and domain-speci c features. For the latter, we used features derived from two existing chemical NER systems, ChemSpot [2] and OSCAR [3], as well as various external resources. In this
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Named entity recognition (NER) systems are often based on machine learning techniques to reduce the labor-intensive development of hand-crafted extraction rules and domain-dependent dictionaries. Nevertheless, time-consuming feature engineering is often needed to achieve state-of-the-art performance. In this study, we investigate the impact of such domain-specific features on the performance of recognizing and classifying mentions of pharmacological substances. We compare the performance of a
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Talk given at the Transatlantic Science Forum meeting in the European Parliament, November 12, 2013 (see http://www.tsciencef.org/event.php?id=2)

Overview preliminary results and first version of multi-scale model of human hepatic galactose metabolism.
First simulations of normal state and galactosemias.

See also:
Galactose investigation
http://seek.virtuelle-leber.de/investigations/88
Galactose study
http://seek.virtuelle-leber.de/studies/50
Galactose modelling assay
http://seek.virtuelle-leber.de/assays/71

Poster presented at the VLN Retreat in Hünfeld 2013
A method for statistically assessing uncertainties of model predictions is presented.

The analysis of biological networks for interpreting data is becoming a standard in bioinformatics as it enables us to look at a process from the perspective of pathways and network modules rather than single proteins. To study proteins in the context of a cellular system, it is essential that the molecules with which a protein interacts are identified and the functional consequence of each interaction is understood.
We work on several aspects concerning data integration in protein interaction
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Presentation at ECMTB 2011