| From hype to reality: data science enabling personalized medicine H Fröhlich, R Balling, N Beerenwinkel, O Kohlbacher, S Kumar, ... BMC medicine 16, 1-15, 2018 | 401 | 2018 |
| Feature selection for support vector machines by means of genetic algorithm H Frohlich, O Chapelle, B Scholkopf Proceedings. 15th IEEE International Conference on Tools with Artificial …, 2003 | 335* | 2003 |
| miR-155 regulates differentiation of brown and beige adipocytes via a bistable circuit Y Chen, F Siegel, S Kipschull, B Haas, H Fröhlich, G Meister, A Pfeifer Nature communications 4 (1), 1769, 2013 | 311 | 2013 |
| 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, 1-8, 2007 | 243 | 2007 |
| 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, ... BMC systems biology 3, 1-20, 2009 | 241 | 2009 |
| Optimal assignment kernels for attributed molecular graphs H Fröhlich, JK Wegner, F Sieker, A Zell Proceedings of the 22nd international conference on Machine learning, 225-232, 2005 | 212 | 2005 |
| Vibration-based terrain classification using support vector machines C Weiss, H Frohlich, A Zell 2006 IEEE/RSJ international conference on intelligent robots and systems …, 2006 | 208 | 2006 |
| Exosomal microRNA miR-92a concentration in serum reflects human brown fat activity Y Chen, JJ Buyel, MJW Hanssen, F Siegel, R Pan, J Naumann, M Schell, ... Nature communications 7 (1), 11420, 2016 | 171 | 2016 |
| Feature Selection for Support Vector Machines by Means of Genetic Algorithms. H Fröhlich, O Chapelle, B Schölkopf ICTAI 3, 142, 2003 | 166 | 2003 |
| Efficient parameter selection for support vector machines in classification and regression via model-based global optimization H Frohlich, A Zell Proceedings. 2005 IEEE International Joint Conference on Neural Networks …, 2005 | 152 | 2005 |
| Integration of pathway knowledge into a reweighted recursive feature elimination approach for risk stratification of cancer patients M Johannes, JC Brase, H Fröhlich, S Gade, M Gehrmann, M Fälth, ... Bioinformatics 26 (17), 2136-2144, 2010 | 114 | 2010 |
| L‐dopa increases α‐synuclein DNA methylation in Parkinson's disease patients in vivo and in vitro I Schmitt, O Kaut, H Khazneh, L deBoni, A Ahmad, D Berg, C Klein, ... Movement Disorders 30 (13), 1794-1801, 2015 | 108 | 2015 |
| Caution,“normal” BMI: health risks associated with potentially masked individual underweight—EPMA Position Paper 2021 O Golubnitschaja, A Liskova, L Koklesova, M Samec, K Biringer, ... EPMA Journal 12 (3), 243-264, 2021 | 103 | 2021 |
| The impact of pathway database choice on statistical enrichment analysis and predictive modeling S Mubeen, CT Hoyt, A Gemünd, M Hofmann-Apitius, H Fröhlich, ... Frontiers in genetics 10, 1203, 2019 | 99 | 2019 |
| 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, CH Gleiter, ... Biomarkers 13 (4), 435-449, 2008 | 98 | 2008 |
| Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease GI Allen, N Amoroso, C Anghel, V Balagurusamy, CJ Bare, D Beaton, ... Alzheimer's & Dementia 12 (6), 645-653, 2016 | 86 | 2016 |
| Characterizing the genetic basis of innate immune response in TLR4-activated human monocytes S Kim, J Becker, M Bechheim, V Kaiser, M Noursadeghi, N Fricker, ... Nature communications 5 (1), 5236, 2014 | 85 | 2014 |
| Network and data integration for biomarker signature discovery via network smoothed t-statistics Y Cun, H Fröhlich PloS one 8 (9), e73074, 2013 | 80 | 2013 |
| Susceptibility variants on chromosome 7p21.1 suggest HDAC9 as a new candidate gene for male‐pattern baldness FF Brockschmidt, S Heilmann, JA Ellis, S Eigelshoven, S Hanneken, ... British Journal of Dermatology 165 (6), 1293-1302, 2011 | 80 | 2011 |
| Feature selection for descriptor based classification models. 2. Human intestinal absorption (HIA) JK Wegner, H Fröhlich, A Zell Journal of chemical information and computer sciences 44 (3), 931-939, 2004 | 80 | 2004 |
Andreas ZellProfessor für Informatik, Universität Tübingen在 uni-tuebingen.de 的电子邮件经过验证
