Ulrich Bodenhofer's Publications
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Articles in Refereed International Journals
| [47] | S. Suessner, N. Niklas, U. Bodenhofer, and J. Meier. Machine learning-based prediction of fainting during blood donations using donor properties and weather data as features. BMC Medical Inform. Decis. Mak., 22:222, 2022. [ bib | DOI ] |
| [46] | B. Zellinger, U. Bodenhofer, I. A. Engländer, C. Kronberger, B. Grambozov, E. Ruznic, M. Stana, J. Karner, G. Fastner, K. Sotlar, F. Sedlmayer, and F. Zehentmayr. Hsa-miR-3651 could serve as a novel predictor for in-breast recurrence via FRMD3. Breast Cancer, 29(2):274–286, 2022. [ bib | DOI ] |
| [45] | J. Meier, T. Tschoellitsch, U. Bodenhofer, and M. W. Dünser. Randomised controlled trials should be analysed using one-sided tests: pro. Anaesth. Crit. Care Pain Med., 40(6):100981, 2021. [ bib | DOI ] |
| [44] | U. Bodenhofer, B. Haslinger-Eisterer, A. Minichmayer, G. Hermanutz, and J. Meier. Machine learning-based risk profile classification of patients undergoing elective heart valve surgery. Eur. J. Cardiothorac. Surg., 60(6):1378–1385, 2021. [ bib | DOI ] |
| [43] | B. Zellinger, U. Bodenhofer, I. A. Engländer, C. Kronberger, P. Strasser, B. Grambozov, G. Fastner, M. Stana, R. Reitsamer, K. Sotlar, F. Sedlmayer, and F. Zehentmayr. Hsa-miR-375/RASD1 signaling may predict local control in early breast cancer. Genes, 11:1404, 2020. [ bib | DOI ] |
| [42] | E. Van Nieuwenhove, V. Lagou, L. Van Eyk, J. Dooley, U. Bodenhofer, C. Roca, M. Vandebergh, A. Goris, S. Humblet-Baron, C. Wouters, and A. Liston. Machine learning identifies an immunological pattern associated with multiple juvenile idiopathic arthritis subtypes. Ann. Rheum. Dis., 78(5):617–628, 2019. [ bib | DOI ] |
| [41] | 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 | DOI ] |
| [40] | 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 | DOI ] |
| [39] | 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 | DOI ] |
| [38] | 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 aeruginosa. Antimicrob. Agents Chemother., 60(8):4722–4733, 2016. [ bib | DOI ] |
| [37] | 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 | DOI ] |
| [36] | 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 | DOI ] |
| [35] | 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 | DOI ] |
| [34] | 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 | DOI ] |
| [33] | 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 | DOI ] |
| [32] | 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 | DOI ] |
| [31] | 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 | DOI ] |
| [30] | 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 | DOI ] |
| [29] | 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 | DOI ] |
| [28] | 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 | DOI ] |
| [27] | U. Bodenhofer, M. Krone, and F. Klawonn. Testing noisy numerical data for monotonic association. Inform. Sci., 245:21–37, 2013. [ bib | DOI ] |
| [26] | 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 | DOI ] |
| [25] | 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 | DOI ] |
| [24] | U. Bodenhofer, A. Kothmeier, and S. Hochreiter. APCluster: an R package for affinity propagation clustering. Bioinformatics, 27(17):2463–2464, 2011. [ bib | DOI ] |
| [23] | 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 | DOI ] |
| [22] | 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 | DOI ] |
| [21] | 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 | DOI ] |
| [20] | 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 | DOI ] |
| [19] | U. Bodenhofer. Orderings of fuzzy sets based on fuzzy orderings. part II: generalizations. Mathware Soft Comput., 15(3):219–249, 2008. [ bib | http | .pdf ] |
| [18] | U. Bodenhofer. Orderings of fuzzy sets based on fuzzy orderings. part I: the basic approach. Mathware Soft Comput., 15(2):201–218, 2008. [ bib | http | .pdf ] |
| [17] | 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 | http | .pdf ] |
| [16] | 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 | DOI ] |
| [15] | L. Běhounek, U. Bodenhofer, and P. Cintula. Relations in Fuzzy Class Theory: Initial steps. Fuzzy Sets and Systems, 159(14):1729–1772, 2008. [ bib | DOI ] |
| [14] | 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 | DOI ] |
| [13] | U. Bodenhofer and P. Bauer. Interpretability of linguistic variables: A formal account. Kybernetika, 41(2):227–248, 2005. [ bib | .pdf ] |
| [12] | U. Bodenhofer and J. Küng. Fuzzy orderings in flexible query answering systems. Soft Computing, 8(7):512–522, 2004. [ bib | DOI ] |
| [11] | U. Bodenhofer and F. Klawonn. A formal study of linearity axioms for fuzzy orderings. Fuzzy Sets and Systems, 145(3):323–354, 2004. [ bib | DOI ] |
| [10] | U. Bodenhofer, M. De Cock, and E. E. Kerre. Openings and closures of fuzzy preorderings: theoretical basics and applications to fuzzy rule-based systems. Int. J. General Systems, 32(4):343–360, 2003. [ bib | DOI ] |
| [9] | U. Bodenhofer. Representations and constructions of similarity-based fuzzy orderings. Fuzzy Sets and Systems, 137(1):113–136, 2003. [ bib | DOI ] |
| [8] | U. Bodenhofer. A unified framework of opening and closure operators with respect to arbitrary fuzzy relations. Soft Computing, 7:220–227, 2003. [ bib | DOI ] |
| [7] | M. Drobics, U. Bodenhofer, and E. P. Klement. FS-FOIL: An inductive learning method for extracting interpretable fuzzy descriptions. Internat. J. Approx. Reason., 32(2–3):131–152, 2003. [ bib | DOI ] |
| [6] | U. Bodenhofer. A note on approximate equality versus the Poincaré paradox. Fuzzy Sets and Systems, 133(2):155–160, 2003. [ bib | DOI ] |
| [5] | S. Saminger, R. Mesiar, and U. Bodenhofer. Domination of aggregation operators and preservation of transitivity. Internat. J. Uncertain. Fuzziness Knowledge-Based Systems, 10(Suppl.):11–35, 2002. [ bib | DOI ] |
| [4] | M. Burger, J. Haslinger, U. Bodenhofer, and H. W. Engl. Regularized data-driven construction of fuzzy controllers. J. Inverse Ill-Posed Probl., 10(4):319–344, 2002. [ bib ] |
| [3] | M. Drobics, U. Bodenhofer, and W. Winiwarter. Mining clusters and corresponding interpretable descriptions — a three-stage approach. Expert Systems, 19(4):224–234, 2002. [ bib | DOI ] |
| [2] | U. Bodenhofer. A similarity-based generalization of fuzzy orderings preserving the classical axioms. Internat. J. Uncertain. Fuzziness Knowledge-Based Systems, 8(5):593–610, 2000. [ bib | DOI ] |
| [1] | U. Bodenhofer. A new approach to fuzzy orderings. Tatra Mt. Math. Publ., 16:21–29, 1999. [ bib | .pdf ] |
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