Holger Fröhlich

Short Curriculum Vitae:

• Since 06.2006: Postdoctorial researcher at the German Cancer Research Center Heidelberg (DKFZ), Div. Molecular Genome Analysis (formerly: Prof. Dr. A. Poustka)
  
• 03.2003 - 06.2006: Research assistant/PhD student at Centre for Bioinformatics Tübingen (ZBIT). Supervisor: Prof. Dr. A. Zell
  
• 05.2002 - 12.2002: Diploma (Masters) thesis at the Max-Planck-Institute for Biological Cybernetics, Tübingen. Supervisor: Prof. Dr. B. Schökopf
  
• 1998: exchange student at Washington State University (USA)
  
• 1996 - 2002: studies of computer science at the University of Marburg
  

Degrees:

• Diploma (Masters) in computer science - 03.2003
  University of Marburg. Subjects: computer science, economics (Mark: 1.3)
  Thesis: "Feature Selection for Support Vector Machines by Means of Genetic Algorithms"
• PhD in computer science (Dr. rer. nat.) - 12.2006
  University of Tuebingen (magna cum laude )
  Thesis: "Kernel Methods in Chemo- and Bioinformatics"

Publications (peer reviewed)

2009

• Nested Effects Models for Learning Signaling Networks from Perturbation Data
  H. Fröhlich, A. Tresch, T. Beißbarth, Biometrical Journal, 2, 2009, accepted
  
  
• Modeling ERBB receptor-regulated G1/S transition to find novel targets for de novo trastuzumab resistance
  Ö. Sahin, H. Fröhlich, C. Löbke, U. Korf, S. Burmester, M. Majety, J. Mattern, I. Schupp, C. Chaouiya, D. Thieffry, A. Poustka, S. Wiemann, T. Beißbarth, D. Arlt, BMC Systems Biology, 2009, accepted
  
  

  2008

• A Bayesian Network View on Nested Effects Models
  C. Zeller, H. Fröhlich, A. Tresch, EURASIP Journal on Bioinformatics and Systems Biology, 2008, in Press
  
  
• Analyzing Gene Perturbation Screens With Nested Effects Models in R and Bioconductor
  H. Fröhlich, T. Beißbarth, A. Tresch, D. Kostka, J. Jacob, R. Spang, F. Markowetz, Bioinformatics, 8, 2008; doi:10.1093/bioinformatics/btn446
  
  
• Predicting Pathway Membership via Domain Signatures
  H. Fröhlich, M. Fellmann, H. Sültmann, A. Poustka, T. Beißbarth, Bioinformatics, 24:2137-2142, 2008; doi: 10.1093/bioinformatics/btn403
  
  
• Bioinformatical evaluation of modified nucleosides as biomedical markers in diagnosis of breast cancer
  D. Bullinger, H. Fröhlich, F. Klaus, H. Neubauer, A. Frickenschmidt, C. Henneges, A. Zell, S. Laufer, C. Gleiter, H. Liebich, B. Kammerer, Analytica Chimica Acta, 618(1):29 - 34, 2008
  
  
• Metabonomics in cancer diagnosis: Mass spectrometry based profiling of urinary nucleosides from breast cancer patients
  A. Frickenschmidt, H. Fröhlich, D. Bullinger, A. Zell, S. Laufer, C. Gleiter, H. Liebich, B. Kammerer, Biomarkers, 13(4):435 - 449, 2008
  
  
• Estimating Large Scale Signaling Networks through Nested Effects Models from Intervention Effects in Microarray Data
  H. Fröhlich, M. Fellmann, H. Sültmann, A. Poustka, T. Beißbarth, Bioinformatics, 24:2650-2656, 2008
  
  

  2007

• Large Scale Statistical Inference of Signaling Pathways from RNAi and Microarray Data
  H. Fröhlich, M. Fellmann, H. Sültmann, A. Poustka, T. Beißbarth, BMC Bioinformatics, 8:386, 2007
  
  
• Automated Classification of the Behavior of Rats in the Forced Swimming Test with Support Vector Machines
  H. Fröhlich, A. Hoenselaar, J. Eichner, H. Rosenbrock, G. Birk, A. Zell, Neural Networks, 21(1):92 - 101.
  
  
• Estimating Large Scale Signaling Networks through Nested Effects Models from Intervention Effects in Microarray Data
  H. Fröhlich, M. Fellmann, H. Sültmann, A. Poustka, T. Beißbarth, Proc. German Conf. Bioinformatics (GCB), pp. 45 - 54, 2007
  
  
• GOSim - An R-Package for Computation of Information Theoretic GO Similarities Between Terms and Gene Products
  H. Fröhlich, N. Speer, A. Poustka, T. Beißbarth, BMC Bioinformatics, 8:166, 2007
  
  
• Gene Regulatory Network Inference via Regression Based Topological Refinement
  Jochen Supper, Holger Fröhlich and Andreas Zell, Series on Adv. in Bioinformatics and Comp. Biol., 5:267 - 276, 2007
  
  
• Infering Gene Regulatory Networks by Machine Learning Methods
  Jochen Supper, Holger Fröhlich, Christian Spieth, Andreas Dräger and Andreas Zell, Series on Adv. in Bioinformatics and Comp. Biol., 5:247 - 256, 2007
  
  

  2006

• Kernel Functions for Attributed Molecular Graphs - A New Similarity Based Approach To ADME Prediction in Classification and Regression
  H. Fröhlich, J. Wegner, F. Sieker, A. Zell, QSAR & Combinatorial Science, 25(4):317 - 326, 2006
  
  
• Data and Graph Mining in Chemical Space for ADME and Activity Data Sets
  J. Wegner, H. Fröhlich, H. Mielenz, A. Zell, QSAR & Combinatorial Science, 25(3):205 - 220, 2006
  
  
• Vibration-based Terrain Classification Using Support Vector Machines
  C. Weiss, H. Fröhlich and A. Zell, Proc. IEEE/RSJ Int. Conf. Intel. Robots and Systems (IROS 2006), pp. 4429 - 4434, 2006
  
  
• Kernel Based Functional Gene Grouping
  H. Fröhlich, N. Speer, C. Spieth, and A. Zell, Proc. Int. Joint. Conf. On Neural Networks (IJCNN), pp. 6886 - 6891, 2006
  
  

  2005

• Functional Distances for Genes Based on GO Feature Maps and their Application to Clustering
  N. Speer, H. Fröhlich, C. Spieth, and A. Zell, Proc. Symp. on Comp. Int. in Bioinformatics and Comp. Biology (CIBCB), pp. 142 - 149, 2005
  
  
• Optimal Assignment Kernels for Attributed Molecular Graphs
  H. Fröhlich, J. Wegner, F. Sieker, A. Zell, Proc. Int. Conf. on Machine Learning (ICML), pp. 225 - 232, 2005
  
  
• Which Features Trigger Action Potentials in Cortical Neurons in Vivo?
  H. Fröhlich, B. Naundorf, M. Volgushev, F. Wolf, Proc. Int. Joint Conf. on Neural Networks (IJCNN), pp. 250 - 255, 2005
  
  
• Functional Grouping of Genes Using Spectral Clustering and Gene Ontology
  N. Speer, H. Fröhlich, A. Zell, Proc. Int. Joint Conf. on Neural Networks (IJCNN), pp. 298 - 303, 2005
  
  
• Assignment Kernels For Chemical Compounds
  H. Fröhlich, J. Wegner, A. Zell, Proc. Int. Joint Conf. on Neural Networks (IJCNN), pp. 913 - 918, 2005
  
  
• Efficient Parameter Selection for Support Vector Machines in Classification and Regression via Model-Based Global Optimization
  H. Fröhlich, A. Zell, Proc. Int. Joint Conf. on Neural Networks (IJCNN), pp. 1431 - 1438, 2005
  
  

  2004

• Towards Optimal Descriptor Subset Selection with Support Vector Machines in Classification and Regression
  H. Fröhlich, J. Wegner, A. Zell, QSAR & Combinatorial Science, 23:311 - 318, 2004
  
  
• Feature Selection for Descriptor based Classificiation Models: Part I - Theory and GA-SEC Algorithm
  J. Wegner, H. Fröhlich, A. Zell, Journal of Chemical Information and Computer Science, 44:921 - 930, 2004
  
  
• Feature Selection for Descriptor based Classificiation Models: Part II - Human Intestinal Absorption (HIA)
  J. Wegner, H. Fröhlich, A. Zell, Journal of Chemical Information and Computer Science, 44:931 - 939, 2004
  
  
• Feature Selection for Support Vector Machines using Genetic Algorithms
  H. Fröhlich, O. Chapelle, B. Schölkopf, International Journal on Artificial Intelligence: Special Issue on Selected Papers from the 15th IEEE International Conference on Tools with Artificial Intelligence 2003, 13(4):791 - 800, 2004
  
  
• Feature Subset Selection for Support Vector Machines by Incremental Regularized Risk Minimization
  H. Fröhlich, A. Zell, International Joint Conference on Neural Networks (IJCNN), 3:2041 - 2046, 2004
  
  
• Learning to Detect Proximity to a Gas Source with a Mobile Robot
  A. Lilienthal, H. Ulmer, H. Fröhlich, A. Stützle, F. Werner, A. Zell, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1444 - 1449, 2004
  
  
• Gas Source Declaration with a Mobile Robot
  A. Lilienthal, H. Ulmer, H. Fröhlich, A. Stützle, F. Werner, A. Zell, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pp. 1430 - 1435, 2004
  
  

  2003

• Feature Selection for Support Vector Machines by Means of Genetic Algorithms
  H. Fröhlich, O. Chapelle, B. Schölkopf, 15th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), pp. 142 - 148, 2003
  
  

Publications (other)

• Routine in der biomedizinischen Forschung
  R. Kuner, M. Ruschhaupt, A. Buneß, T. Beißbarth, H. Fröhlich, M. Fellmann, A. Poustka, H. Sültmann, BIOspektrum, 13. Jahrgang, Sonderheft 2007
  
  
• Wie man aus Interventionseffekten über Signalwege in einer Zelle lernen kann
  H. Fröhlich, M. Fellmann, R. Kuner, A. Poustka, H. Sültmann, T. Beißbarth, GenomeXPress, Sonderausgabe 2007
  
  

Software

• SVM feature selection with Relief-F, RFE, Genetic Algorithms (C++)
  
  
• Optimal Assignment Kernels (OAKs) and Marginalized Graph Kernels (MGKs) for attributed molecular graphs (Version 3.1) (Java-Source)
  
  
• GOSim package for computation of information theoretic Gene Ontology similarities between terms and gene products (R)
  
  
• nem package for estimating (cellular) signaling flow from perturbation experiments (R)
  
  
• Predicting KEGG Pathway membership for individual genes via InterPro Domains (R)
  
  

Address

Holger Fröhich