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Institute for Machine Learning
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Assoz.Univ.-Prof. Dipl.-Ing. Dr. Ulrich Bodenhofer

Personal data/education

  • Born 1972
  • MSc in applied mathematics (JKU Linz), May 1996
  • PhD in applied mathematics (JKU Linz), October 1998
  • Habilitation (JKU Linz), June 2003

Research topics

Machine learning in bioinformatics, with special focus on:

  • Deep Learning in genomics
  • Classification of biological sequences using kernel methods
  • Genome-wide association studies involving rare SNPs
  • Clustering of biological sequences using affinity propagation
  • Biomedical data analysis services

Publications

The following list only includes journal articles and contributions to edited books and peer-reviewed conferences since 2006. For a complete list of publications, see my private homepage, opens an external URL in a new window.

2018

[2] V. Steinwandter, M. Šišmiš, P. Sagmeister, U. Bodenhofer, and C. Herwig. Multivariate analytics of chromatographic data: Visual computing based on moving window factor models. J. Chromatogr. B., 1092:179--190, 2018. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]
[1] S. Fischer, C. M. Freuling, T. Müller, F. Pfaff, U. Bodenhofer, D. Höper, M. Fischer, D. A. Marston, A. R. Fooks, T. C. Mettenleitner, F. J. Conraths, and T. Homeier-Bachmann. Defining objective clusters for rabies virus sequences using affinity propagation clustering. PLoS Neglect. Trop. Dis., 12(1):e0006182, 2018. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]

2017

[4] V. Greiff, C. R. Weber, J. Palme, U. Bodenhofer, E. Miho, U. Menzel, and S. T. Reddy. Learning the high-dimensional immunogenomic features that predict public and private antibody repertoires. J. Immunol., 199(8):2985--2997, 2017. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]
[3] E. P. Klement, P. Bauer, U. Bodenhofer, M. Mittendorfer-Holzer, R. Pollak, R. Richter, and H. Exner. PapaGeno --- vollautomatische menschenähnliche Qualitätskontrolle für Aufdrucke auf Compact Discs. In M. Wirth, A. Reichl, and M. Gräser, editors, 50 Jahre Johannes Kepler Universität Linz. Innovationsfelder in Forschung, Lehre und universitärem Alltag, pages 265--282. Böhlau, Vienna, Austria, 2017. [ bib, opens an external URL in a new window ]
[2] U. Bodenhofer, B. Haslinger-Eisterer, A. Minichmayer, G. Hermanutz, and J. Meier. Machine learning-based risk profile classification: A case study for heart valve surgery. In NIPS Workshop on Machine Learning for Health, Long Beach, CA, December 2017. [ bib, opens an external URL in a new window ]
[1] U. Bodenhofer and S. Hochreiter. Position kernels as a key to making sense of very rare and private single-nucleotide variants. In NIPS Workshop on Machine Learning in Computational Biology, Long Beach, CA, December 2017. [ bib, opens an external URL in a new window ]

2016

[4] A. Khaledi, M. Schniederjans, S. Pohl, R. Rainer, U. Bodenhofer, B. Xia, F. Klawonn, S. Bruchmann, M. Preusse, D. Eckweiler, A. Dötsch, and S. Häussler. Transcriptome profiling of antimicrobial resistance in Pseudomonas aeruginosaAntimicrob. Agents Chemother., 60(8):4722--4733, 2016. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]
[3] N. Perualila-Tan, Z. Shkedy, W. Talloen, H. W. H. Göhlmann, The QSTAR Consortium, M. V. Moerbeke, and A. Kasim. Weighted similarity-based clustering of chemical structures and bioactivity data in early drug discovery. J. Bioinform. Comput. Biol., 14:1650018, 2016. [ bib, opens an external URL in a new window |DOI, opens an external URL in a new window ]
[2] N. Perualila-Tan, A. Kasim, W. Talloen, B. Verbist, H. W. H. Göhlmann, The QSTAR Consortium, and Z. Shkedy. A joint modeling approach for uncovering associations between gene expression, bioactivity and chemical structure in early drug discovery to guide lead selection and genomic biomarker development. Stat. Appl. Genet. Mol. Biol., 15(4):291--304, 2016. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]
[1] F. Zehentmayr, C. Hauser-Kronberger, B. Zellinger, F. Hlubek, C. Schuster, U. Bodenhofer, G. Fastner, H. Deutschmann, P. Steininger, R. Reitsamer, T. Fischer, and F. Sedlmayer. Hsa-miR-375 is a predictor of local control in early stage breast cancer. Clin. Epigenetics, 8:28, 2016. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]

2015

[6] U. Bodenhofer, E. Bonatesta, C. Horejš-Kainrath, and S. Hochreiter. msa: an R package for multiple sequence alignment. Bioinformatics, 31(24):3997--3999, 2015. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]
[5] B. M. P. Verbist, G. R. Verheyen, L. Vervoort, M. Crabbe, D. Beerens, C. Bosmans, S. Jaensch, S. Osselaer, W. Talloen, I. Van den Wyngaert, G. Van Hecke, D. Wuyts, The QSTAR Consortium, F. Van Goethem, and H. W. H. Göhlmann. Integrating high-dimensional transcriptomics and image analysis tools into early safety screening: proof of concept for a new early drug development strategy. Chem. Res. Toxicol., 28(10):1914--1925, 2015. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]
[4] J. Palme, S. Hochreiter, and U. Bodenhofer. KeBABS: an R package for kernel-based analysis of biological sequences. Bioinformatics, 31(15):2574--2576, 2015. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]
[3] B. Verbist, G. Klambauer, L. Vervoort, W. Talloen, The QSTAR Consortium, Z. Shkedy, O. Thas, A. Bender, H. W. Göhlmann, and S. Hochreiter. Using transcriptomics to guide lead optimization in drug discovery projects: Lessons learned from the QSTAR project. Drug Discov. Today, 20(5):505--513, 2015. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]
[2] A. C. Ravindranath, N. Perualila-Tan, A. Kasim, G. Drakakis, S. Liggi, S. C. Brewerton, D. Mason, M. J. Bodkin, D. A. Evans, A. Bhagwat, W. Talloen, H. W. Göhlmann, Z. Shkedy, A. Bender, and The QSTAR Consortium. Connecting gene expression data from connectivity map and in silico target predictions for small molecule mechanism-of-action analysis. Mol. Biosyst., 11(1):86--96, 2015. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]
[1] L. Běhounek, U. Bodenhofer, P. Cintula, S. Saminger-Platz, and P. Sarkoci. Graded dominance and related graded properties of fuzzy connectives. Fuzzy Sets and Systems, 262:78--101, 2015. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]

2014

[1] A. M. Lipp, K. Juhasz, C. Paar, C. Ogris, P. Eckerstorfer, R. Thuenauer, J. Hesse, B. Nimmervoll, H. Stockinger, G. J. Schütz, U. Bodenhofer, Z. Balogi, and A. Sonnleitner. Lck mediates signal transmission from CD59 to the TCR/CD3 pathway in Jurkat T cells. PLoS ONE, 9(1):e85934, 2014. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]

2013

[1] U. Bodenhofer, M. Krone, and F. Klawonn. Testing noisy numerical data for monotonic association. Inform. Sci., 245:21--37, 2013. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]

2012

[2] K. Schwarzbauer, U. Bodenhofer, and S. Hochreiter. Genome-wide chromatin remodeling identified at GC-rich long nucleosome-free regions. PLoS ONE, 7(11):e47924, 2012. [ bib, opens an external URL in a new window |DOI, opens an external URL in a new window ]
[1] G. Klambauer, K. Schwarzbauer, A. Mayr, D.-A. Clevert, A. Mitterecker, U. Bodenhofer, and S. Hochreiter. cn.MOPS: mixture of Poissons for discovering copy number variations in next-generation sequencing data with a low false discovery rate. Nucleic Acids Res., 40(9):e69, 2012. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]

2011

[2] U. Bodenhofer, A. Kothmeier, and S. Hochreiter. APCluster: an R package for affinity propagation clustering. Bioinformatics, 27(17):2463--2464, 2011. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]
[1] C. C. Mahrenholz, I. G. Abfalter, U. Bodenhofer, R. Volkmer, and S. Hochreiter. Complex networks govern coiled coil oligomerization --- predicting and profiling by means of a machine learning approach. Mol. Cell. Proteomics, 10(5):M110.004994, 2011. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]

2010

[3] L. Běhounek, P. Cintula, U. Bodenhofer, S. Saminger-Platz, and P. Sarkoci. On a graded notion of t-norm and dominance. In Proc. 40th IEEE Int. Symp. on Multiple-Valued Logic, pages 73--78. IEEE Computer Society, 2010. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]
[2] S. Hochreiter, U. Bodenhofer, M. Heusel, A. Mayr, A. Mitterecker, A. Kasim, T. Khamiakova, S. Van Sanden, D. Lin, W. Talloen, L. Bijnens, H. W. H. Göhlmann, Z. Shkedy, and D.-A. Clevert. FABIA: factor analysis for bicluster acquisition. Bioinformatics, 26(12):1520--1527, 2010. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]
[1] M. Štěpnička, U. Bodenhofer, M. Daňková, and V. Novák. Continuity issues of the implicational interpretation of fuzzy rules. Fuzzy Sets and Systems, 161(14):1959--1972, 2010. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]

2009

[3] D. Soukup, U. Bodenhofer, M. Mittendorfer-Holzer, and K. Mayer. Semi-automatic identification of print layers from a sequence of sample images: a case study from banknote print inspection. Image Vision Comput., 27(8):989--998, 2009. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]
[2] U. Bodenhofer, K. Schwarzbauer, M. Ionescu, and S. Hochreiter. Modeling position specificity in sequence kernels by fuzzy equivalence relations. In J. P. Carvalho, D. Dubois, U. Kaymak, and J. M. C. Sousa, editors, Proc. Joint 13th IFSA World Congress and 6th EUSFLAT Conference, pages 1376--1381, Lisbon, July 2009. [ bib, opens an external URL in a new window | .pdf, opens an external URL in a new window ]
[1] U. Bodenhofer. A survey of applications of fuzzy orderings: from databases to statistics and machine learning. In Proc. 14 Recontres Francophones sur la Logique Floue et ses Applications, pages 3--9, Annecy, November 2009. [ bib, opens an external URL in a new window | .pdf, opens an external URL in a new window ]

2008

[6] U. Bodenhofer. Orderings of fuzzy sets based on fuzzy orderings. part II: generalizations.Mathware Soft Comput., 15(3):219--249, 2008. [ bib, opens an external URL in a new window | http, opens an external URL in a new window | .pdf, opens an external URL in a new window ]
[5] U. Bodenhofer. Orderings of fuzzy sets based on fuzzy orderings. part I: the basic approach.Mathware Soft Comput., 15(2):201--218, 2008. [ bib, opens an external URL in a new window | http, opens an external URL in a new window | .pdf, opens an external URL in a new window ]
[4] U. Bodenhofer and F. Klawonn. Robust rank correlation coefficients on the basis of fuzzy orderings: initial steps. Mathware Soft Comput., 15(1):5--20, 2008. [ bib, opens an external URL in a new window | http, opens an external URL in a new window | .pdf, opens an external URL in a new window ]
[3] U. Bodenhofer and M. Demirci. Strict fuzzy orderings with a given context of similarity.Internat. J. Uncertain. Fuzziness Knowledge-Based Systems, 16(2):147--178, 2008. [ bib, opens an external URL in a new window |DOI, opens an external URL in a new window ]
[2] L. Běhounek, U. Bodenhofer, and P. Cintula. Relations in Fuzzy Class Theory: Initial steps.Fuzzy Sets and Systems, 159(14):1729--1772, 2008. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]
[1] U. Bodenhofer. Lexicographic composition of similarity-based fuzzy orderings. In B. Bouchon-Meunier, C. Marsala, M. Rifqi, and R. R. Yager, editors, Uncertainty and Intelligent Information Systems, chapter 33, pages 457--469. World-Scientific, 2008. [ bib, opens an external URL in a new window | .pdf, opens an external URL in a new window ]

2007

[4] U. Bodenhofer, B. De Baets, and J. Fodor. A compendium of fuzzy weak orders: Representations and constructions. Fuzzy Sets and Systems, 158(8):811--829, 2007. [ bib, opens an external URL in a new window |DOI, opens an external URL in a new window ]
[3] U. Bodenhofer, M. Daňková, M. Štěpnička, and V. Novák. A plea for the usefulness of the deductive interpretation of fuzzy rules in engineering applications. In Proc. 16th IEEE Int. Conf. on Fuzzy Systems, pages 1567--1572, London, July 2007. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]
[2] U. Bodenhofer and F. Klawonn. Towards robust rank correlation measures for numerical observations on the basis of fuzzy orderings. In M. Štěpnička, V. Novák, and U. Bodenhofer, editors, Proc. 5th Conference of the European Society for Fuzzy Logic and Technology, volume I, pages 321--327, Ostrava, September 2007. [ bib, opens an external URL in a new window | .pdf, opens an external URL in a new window ]
[1] L. Běhounek, U. Bodenhofer, and P. Cintula. Valverde-style representation results in a graded framework. In M. Štěpnička, V. Novák, and U. Bodenhofer, editors, Proc. 5th Conference of the European Society for Fuzzy Logic and Technology, volume I, pages 153--160, Ostrava, September 2007. [ bib, opens an external URL in a new window | .pdf, opens an external URL in a new window ]

2006

[7] U. Bodenhofer, B. De Baets, and J. Fodor. General representation theorems for fuzzy weak orders. In H. C. M. de Swart, E. Orlowska, M. Roubens, and G. Schmidt, editors, Theory and Applications of Relational Structures as Knowledge Instruments II, volume 4342 of Lecture Notes in Artificial Intelligence, pages 229--244. Springer, Berlin, 2006. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]
[6] U. Bodenhofer, J. Küng, and S. Saminger. Flexible query answering using distance-based fuzzy relations. In H. C. M. de Swart, E. Orlowska, M. Roubens, and G. Schmidt, editors, Theory and Applications of Relational Structures as Knowledge Instruments II, volume 4342 of Lecture Notes in Artificial Intelligence, pages 207--228. Springer, Berlin, 2006. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]
[5] S. Saminger, U. Bodenhofer, E. P. Klement, and R. Mesiar. Aggregration of fuzzy relations and preservation of transitivity. In H. C. M. de Swart, E. Orlowska, M. Roubens, and G. Schmidt, editors, Theory and Applications of Relational Structures as Knowledge Instruments II, volume 4342 of Lecture Notes in Artificial Intelligence, pages 185--206. Springer, Berlin, 2006. [ bib, opens an external URL in a new window |DOI, opens an external URL in a new window ]
[4] B. Moser and U. Bodenhofer. Correspondences between fuzzy equivalence relations and kernels: theoretical results and potential applications. In Proc. 15th IEEE Int. Conf. on Fuzzy Systems, pages 10217--10223, Vancouver, BC, July 2006. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]
[3] R. Bergmair and U. Bodenhofer. Syntax-driven analysis of context-free languages with respect to fuzzy relational semantics. In Proc. 15th IEEE Int. Conf. on Fuzzy Systems, pages 9647--9654, Vancouver, BC, July 2006. [ bib, opens an external URL in a new window | DOI, opens an external URL in a new window ]
[2] U. Bodenhofer. Lexicographic composition of fuzzy orderings. In Proc. 11th Int. Conf. on Information Processing and Management of Uncertainty in Knowledge-Based Systems, volume 3, pages 2430--2437, Paris, July 2006. [ bib, opens an external URL in a new window | .pdf, opens an external URL in a new window ]
[1] E. Lughofer and U. Bodenhofer. Incremental learning of fuzzy basis function networks with a modified version of vector quantization. In Proc. 11th Int. Conf. on Information Processing and Management of Uncertainty in Knowledge-Based Systems, volume 1, pages 56--63, Paris, July 2006. [ bib, opens an external URL in a new window | .pdf, opens an external URL in a new window ]