Georg Hinselmann

Background

  • 1999: Abitur at the Schelztor-Gymnasium Esslingen am Neckar
  • Oct. 2000 - Sept. 2006: Studies of Computer Science (Bioinformatics) at the University of Tübingen
  • 2000-2002: Working student at the Festo AG & Co. KG, Esslingen
  • Since Oct. 2006: Research assistant at the Center of Bioinformatics (ZBIT), Department of Computer Architecture, University of Tübingen
  • Aug. 2009 - Oct. 2009: Internship at the group of Dr. Christoph Steinbeck, EMBL-EBI, Cambridge, UK

Research Interests

  • Cheminformatics, Graph Algoritms
  • Machine Learning Using Kernels in Cheminformatics
  • Large Scale Learning Using Linear SVMs
  • Software Development

Current Projects

  • Kernel Methods Based on Molecular Graphs
  • Kernels for Conformer Ensembles
  • Evaluation of Graph Kernels for Virtual Screening
  • Development of a Graph Kernel Library for Molecular Data
  • Development of a Fingerprinting Library for Chemical Compounds
  • Development of a Large Scale Learning Library for the Database Retrieval of Chemical Compounds

Book Chapters

Molecular Descriptors
    Nikolas Fechner, Georg Hinselmann, and Joerg K. Wegner
    Handbook of Chemoinformatics Algorithms
    Chapman & Hall/CRC Mathematical & Computational Biology, to appear 2010

Full Papers

Optimal assignment methods for ligand-based virtual screening
    Andreas Jahn, Georg Hinselmann, Nikolas Fechner, and Andreas Zell
    Journal of Cheminformatics, 2009, 1:14 (Highly Accessed)
    BibTeX

Atomic Local Neighborhood Flexibility Incorporation Into a Structured Similarity Measure for QSAR
    Nikolas Fechner, Andreas Jahn, Georg Hinselmann, and Andreas Zell
    Journal of Chemical Information and Modeling, 2009, 49, 549-560
    BibTeX

Chronic Rat Toxicity Prediction of Chemical Compounds Using Kernel Machines
    Georg Hinselmann, Andreas Jahn, Nikolas Fechner, and Andreas Zell
    Lecture Notes in Computer Science (EvoBIO 2009), Springer-Verlag Berlin Heidelberg, 2009, 5483, 25-36
    BibTeX

Ranking Methods for the Prediction of Frequent Top Scoring Peptides from Proteomics Data
    Carsten Henneges, Georg Hinselmann, Stephan Jung, Johannes Madlung, Wolfgang Schuetz,
    Alfred Nordheim, and Andreas Zell
    Journal of Proteomics & Bioinformatics (2009), 2(5), 226-235
    BibTeX

Oral Presentations

Beyond descriptor vectors: QSAR modelling Using Structural Similarity
    G. Hinselmann, Nikolas Fechner, A. Jahn, and A. Zell
    Chemistry Central Journal 2008, 2(Suppl 1), S3

Chemoinformatik mit Kernel-Ansätzen
    G. Hinselmann and A. Zell
    4. Sitzung des GMA-FA 5.14 Computational Intelligence, 22-23. March 2007, Stuttgart, Germany

Posters and Abstracts

Efficient Extraction of Canonical Spatial Relationships Using a Recursive Enumeration of k-Subsets
     G. Hinselmann, A. Jahn, N. Fechner, and A. Zell
    5th German Conference on Cheminformatics (pdf)

An extension of the pharmacophore kernel using radial atomtype fingerprints
     G. Hinselmann, M. Eckert, T. Holder, A. Jahn, N. Fechner, and A. Zell
    Chemistry Central Journal, 2009, 3(Suppl 1), P11 (pdf)

Assessing the selectivity of serine proteases inhibitors using structural similarity
    N. Fechner, A. Jahn, G. Hinselmann, and A. Zell
    Chemistry Central Journal, 2009, 3(Suppl 1), P10

Two-step hierarchical assignments on molecular graphs
    A. Jahn, N. Fechner, G. Hinselmann, and A. Zell
    Chemistry Central Journal, 2009, 3(Suppl 1), P13

Altered Ligands for Heterodimers of Toll-Like Receptors 1 and 2
    K.-H. Wiesmüller, S. Voss, G. Hinselmann, N. Fechner, R. Spohn, and A. Zell
    12th Japanese-German Symposium on Peptide Science, Akabori, Japan

A Machine Learning Approach for Ranking of proteotypic peptides for MS
    C. Henneges, G. Hinselmann, S. Jung, J. Madlung, T. Lamkemeyer, A. Nordheim, and A. Zell
    HUPO 2008, Amsterdam, the Netherlands

Rational Design of Toll-like Receptor 1 and 2 Agonists and Antagonists as Immunomodulating Agents
    S. Voss, D. Bächle, R. Spohn, G. Hinselmann, N. Fechner, A. Zell, A.J. Ulmer, and K.-H. Wiesmüller
    Tissue Engineering Part A, 15(3), pp. 694-694, 2009

Estimating the Applicability Domain of Kernel Based QSPR Models Using Classical Descriptor Vectors
    N. Fechner, G. Hinselmann, C. Schmiedl, and A. Zell
    Chemistry Central Journal 2008, 2(Suppl 1), P2

Structural Similarity Measures with Kernel Properties for Ligand based Virtual Screening
    N. Fechner, G. Hinselmann, and A. Zell
    NAD Workshop 2007, Rauischholzhausen, Germany

In Silico Lead-Structure Proposal with Support Vector Machines and Implicit Substructure Fingerprints
    N. Fechner, G. Hinselmann, and A. Zell
    German Conference on Bioinformatics 2006, Tübingen, Germany

Implicitly Defined Substructure Fingerprints for Support Vector Machines
    N. Fechner, G. Hinselmann, and A. Zell
    German Conference on Chemoinformatics 2006, Goslar, Germany

Software

I wrote a program that converts molecules from an MDL SD file into descriptors (LIBSVM and ARFF format). Download here.

Address, Phone, Fax, Email

Eberhard-Karls-Universität Tübingen
Wilhelm-Schickard-Institut für Informatik
Lehrstuhl Rechnerarchitektur
Sand 1
D - 72076 Tübingen
 
Germany
Tel: (+49/0) 7071 / 29 77174
Fax: (+49/0) 7071 / 29 5091
Email: georg.hinselmann@uni-tuebingen.de