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Oliver Kohlbacher: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Clemens Gröpl, Eva Lange, Knut Reinert, Oliver Kohlbacher, Marc Sturm, Christian G. Huber, Bettina M. Mayr, Christoph L. Klein
    Algorithms for the Automated Absolute Quantification of Diagnostic Markers in Complex Proteomics Samples. [Citation Graph (0, 0)][DBLP]
    CompLife, 2005, pp:151-162 [Conf]
  2. Liliana Florea, Bjarni V. Halldórsson, Oliver Kohlbacher, Russell Schwartz, Stephen Hoffman, Sorin Istrail
    Epitope Prediction Algorithms for Peptide based Vaccine Design. [Citation Graph (0, 0)][DBLP]
    CSB, 2003, pp:17-26 [Conf]
  3. Nathanaël Delmotte, Bettina M. Mayr, Andreas Leinenbach, Knut Reinert, Oliver Kohlbacher, Christoph L. Klein, Christian G. Huber
    Evaluation of LC-MS data for the absolute quantitative analysis of marker proteins. [Citation Graph (0, 0)][DBLP]
    Computational Proteomics, 2005, pp:- [Conf]
  4. Christian G. Huber, Oliver Kohlbacher, Knut Reinert
    05471 Executive Summary - Computational Proteomics. [Citation Graph (0, 0)][DBLP]
    Computational Proteomics, 2005, pp:- [Conf]
  5. Christian G. Huber, Oliver Kohlbacher, Knut Reinert
    05471 Abstract Collection - Computational Proteomics. [Citation Graph (0, 0)][DBLP]
    Computational Proteomics, 2005, pp:- [Conf]
  6. Eva Lange, Clemens Gröpl, Oliver Kohlbacher, Andreas Hildebrandt
    High-accuracy peak picking of proteomics data. [Citation Graph (0, 0)][DBLP]
    Computational Proteomics, 2005, pp:- [Conf]
  7. Marc Sturm, Sascha Quinten, Christian G. Huber, Oliver Kohlbacher
    A machine learning approach for prediction of DNA and peptide retention times. [Citation Graph (0, 0)][DBLP]
    Computational Proteomics, 2005, pp:- [Conf]
  8. Marite Sirava, T. Schäfer, Markus Eiglsperger, Michael Kaufmann, Oliver Kohlbacher, Erich Bornberg-Bauer, Hans-Peter Lenhof
    BioMiner - modeling, analyzing, and visualizing biochemical pathways and networks. [Citation Graph (0, 0)][DBLP]
    ECCB, 2002, pp:219-230 [Conf]
  9. Oliver Kohlbacher, Hans-Peter Lenhof
    Rapid Software Prototyping in Computational Molecular Biology. [Citation Graph (0, 0)][DBLP]
    German Conference on Bioinformatics, 1999, pp:81-92 [Conf]
  10. Annette Höglund, Pierre Dönnes, Torsten Blum, Hans-Werner Adolph, Oliver Kohlbacher
    Using N-terminal targeting sequences, amino acid composition, and sequence motifs for predicting protein subcellular localizations. [Citation Graph (0, 0)][DBLP]
    German Conference on Bioinformatics, 2005, pp:45-59 [Conf]
  11. Jochen Supper, Pierre Dönnes, Oliver Kohlbacher
    Analysis of MHC-Peptide Binding Using Amino Acid Property-Based Decision Rules. [Citation Graph (0, 0)][DBLP]
    ICAPR (1), 2005, pp:446-453 [Conf]
  12. Annette Höglund, Torsten Blum, Scott Brady, Pierre Dönnes, John San Miguel, Matthew Rocheford, Oliver Kohlbacher, Hagit Shatkay
    Significantly Improved Prediction of Subcellular Localization by Integrating Text and Protein Sequence Data . [Citation Graph (0, 0)][DBLP]
    Pacific Symposium on Biocomputing, 2006, pp:16-27 [Conf]
  13. Eva Lange, Clemens Gröpl, Knut Reinert, Oliver Kohlbacher, Andreas Hildebrandt
    High-Accuracy Peak Picking of Proteomics Data Using Wavelet Techniques. [Citation Graph (0, 0)][DBLP]
    Pacific Symposium on Biocomputing, 2006, pp:243-254 [Conf]
  14. Russell J. Turner, Kabir Chaturvedi, Nathan Edwards, Daniel P. Fasulo, Aaron L. Halpern, Daniel H. Huson, Oliver Kohlbacher, Jason R. Miller, Knut Reinert, Karin A. Remington, Russell Schwartz, Brian Walenz, Shibu Yooseph, Sorin Istrail
    Visualization challenges for a new cyberpharmaceutical computing paradigm. [Citation Graph (0, 0)][DBLP]
    IEEE Symposium on Parallel and Large-Data Visualization and Graphics, 2001, pp:7-18 [Conf]
  15. Ernst Althaus, Oliver Kohlbacher, Hans-Peter Lenhof, Peter Müller
    A combinatorial approach to protein docking with flexible side-chains. [Citation Graph (0, 0)][DBLP]
    RECOMB, 2000, pp:15-24 [Conf]
  16. Oliver Kohlbacher, Andreas Burchardt, Andreas Moll, Andreas Hildebrandt, Peter Bayer, Hans-Peter Lenhof
    A NMR-spectra-based scoring function for protein docking. [Citation Graph (0, 0)][DBLP]
    RECOMB, 2001, pp:184-192 [Conf]
  17. Nicolas Boghossian, Oliver Kohlbacher, Hans-Peter Lenhof
    BALL: Biochemical Algorithms Library. [Citation Graph (0, 0)][DBLP]
    Algorithm Engineering, 1999, pp:331-345 [Conf]
  18. Annette Höglund, Pierre Dönnes, Torsten Blum, Hans-Werner Adolph, Oliver Kohlbacher
    MultiLoc: prediction of protein subcellular localization using N-terminal targeting sequences, sequence motifs and amino acid composition. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2006, v:22, n:10, pp:1158-1165 [Journal]
  19. Oliver Kohlbacher, Hans-Peter Lenhof
    BALL-rapid software prototyping in computational molecular biology. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2000, v:16, n:9, pp:815-824 [Journal]
  20. Andreas Moll, Andreas Hildebrandt, Hans-Peter Lenhof, Oliver Kohlbacher
    BALLView: a tool for research and education in molecular modeling. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2006, v:22, n:3, pp:365-366 [Journal]
  21. Andreas Hildebrandt, Ralf Blossey, Sergej Rjasanow, Oliver Kohlbacher, Hans-Peter Lenhof
    Electrostatic potentials of proteins in water: a structured continuum approach. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2007, v:23, n:2, pp:99-103 [Journal]
  22. Oliver Kohlbacher, Knut Reinert, Clemens Gröpl, Eva Lange, Nico Pfeifer, Ole Schulz-Trieglaff, Marc Sturm
    TOPP - the OpenMS proteomics pipeline. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2007, v:23, n:2, pp:191-197 [Journal]
  23. Oliver Kohlbacher, Knut Reinert
    Differenzielle Proteomanalyse - Experimentelle Methoden, algorithmische Herausforderungen (Differential Analysis in Proteomics: Experimental Methods, Algorithmic Challenges). [Citation Graph (0, 0)][DBLP]
    it - Information Technology, 2004, v:46, n:1, pp:31-38 [Journal]
  24. Ernst Althaus, Oliver Kohlbacher, Hans-Peter Lenhof, Peter Müller
    A Combinatorial Approach to Protein Docking with Flexible Side Chains. [Citation Graph (0, 0)][DBLP]
    Journal of Computational Biology, 2002, v:9, n:4, pp:597-612 [Journal]
  25. Andreas Kerzmann, Dirk Neumann, Oliver Kohlbacher
    SLICK - Scoring and Energy Functions for Protein-Carbohydrate Interactions. [Citation Graph (0, 0)][DBLP]
    Journal of Chemical Information and Modeling, 2006, v:46, n:4, pp:1635-1642 [Journal]
  26. Dirk Neumann, Oliver Kohlbacher, Christian Merkwirth, Thomas Lengauer
    A Fully Computational Model for Predicting Percutaneous Drug Absorption. [Citation Graph (0, 0)][DBLP]
    Journal of Chemical Information and Modeling, 2006, v:46, n:1, pp:424-429 [Journal]
  27. Nicolas Boghossian, Oliver Kohlbacher, Hans-Peter Lenhof
    Rapid Software Prototyping in Molecular Modeling Using the Biochemical Algorithms Library (BALL). [Citation Graph (0, 0)][DBLP]
    ACM Journal of Experimental Algorithms, 2000, v:5, n:, pp:16- [Journal]
  28. Pierre Dönnes, Oliver Kohlbacher
    SVMHC: a server for prediction of MHC-binding peptides. [Citation Graph (0, 0)][DBLP]
    Nucleic Acids Research, 2006, v:34, n:Web-Server-Issue, pp:194-197 [Journal]
  29. Hagit Shatkay, Annette Höglund, Scott Brady, Torsten Blum, Pierre Dönnes, Oliver Kohlbacher
    SherLoc: high-accuracy prediction of protein subcellular localization by integrating text and protein sequence data. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2007, v:23, n:11, pp:1410-1417 [Journal]

  30. Integer Linear Programming in Computational Biology. [Citation Graph (, )][DBLP]


  31. TOPP goes Rapid The OpenMS Proteomics Pipeline in a Grid-Enabled Web Portal. [Citation Graph (, )][DBLP]


  32. Finding Relevant Biotransformation Routes in Weighted Metabolic Networks. [Citation Graph (, )][DBLP]


  33. KIRMES: Kernel-based Identification of Regulatory Modules in Euchromatic Sequences. [Citation Graph (, )][DBLP]


  34. On Open Problems in Biological Network Visualization. [Citation Graph (, )][DBLP]


  35. Grid-Workflows in Molecular Science. [Citation Graph (, )][DBLP]


  36. Multiple Instance Learning Allows MHC Class II Epitope Predictions Across Alleles. [Citation Graph (, )][DBLP]


  37. Novel Machine Learning Methods for MHC Class I Binding Prediction. [Citation Graph (, )][DBLP]


  38. MetaRoute: fast search for relevant metabolic routes for interactive network navigation and visualization. [Citation Graph (, )][DBLP]


  39. KIRMES: kernel-based identification of regulatory modules in euchromatic sequences. [Citation Graph (, )][DBLP]


  40. FRED - a framework for T-cell epitope detection. [Citation Graph (, )][DBLP]


  41. A novel algorithm for detecting differentially regulated paths based on gene set enrichment analysis. [Citation Graph (, )][DBLP]


  42. Going from where to why - interpretable prediction of protein subcellular localization. [Citation Graph (, )][DBLP]


  43. Statistical learning of peptide retention behavior in chromatographic separations: a new kernel-based approach for computational proteomics. [Citation Graph (, )][DBLP]


  44. BNDB - The Biochemical Network Database. [Citation Graph (, )][DBLP]


  45. LC-MSsim - a simulation software for liquid chromatography mass spectrometry data. [Citation Graph (, )][DBLP]


  46. Peak intensity prediction in MALDI-TOF mass spectrometry: A machine learning study to support quantitative proteomics. [Citation Graph (, )][DBLP]


  47. GeneTrailExpress: a web-based pipeline for the statistical evaluation of microarray experiments. [Citation Graph (, )][DBLP]


  48. OpenMS - An open-source software framework for mass spectrometry. [Citation Graph (, )][DBLP]


  49. MultiLoc2: integrating phylogeny and Gene Ontology terms improves subcellular protein localization prediction. [Citation Graph (, )][DBLP]


  50. KIRMES: kernel-based identification of regulatory modules in euchromatic sequences. [Citation Graph (, )][DBLP]


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