| An introductory review of deep learning for prediction models with big data F Emmert-Streib, Z Yang, H Feng, S Tripathi, M Dehmer Frontiers in Artificial Intelligence 3, 4, 2020 | 666 | 2020 |
| A history of graph entropy measures M Dehmer, A Mowshowitz Information Sciences 181 (1), 57-78, 2011 | 642 | 2011 |
| Information processing in complex networks: Graph entropy and information functionals M Dehmer Applied Mathematics and Computation 201 (1-2), 82-94, 2008 | 371 | 2008 |
| Gene regulatory networks and their applications: understanding biological and medical problems in terms of networks F Emmert-Streib, M Dehmer, B Haibe-Kains Frontiers in cell and developmental biology 2, 38, 2014 | 344 | 2014 |
| A review of connectivity map and computational approaches in pharmacogenomics A Musa, LS Ghoraie, SD Zhang, G Glazko, O Yli-Harja, M Dehmer, ... Briefings in bioinformatics 19 (3), 506-523, 2018 | 334 | 2018 |
| Fifty years of graph matching, network alignment and network comparison F Emmert-Streib, M Dehmer, Y Shi Information sciences 346, 180-197, 2016 | 300 | 2016 |
| On structure-sensitivity of degree-based topological indices B Furtula, I Gutman, M Dehmer Applied Mathematics and Computation 219 (17), 8973-8978, 2013 | 290 | 2013 |
| Knowledge discovery and interactive data mining in bioinformatics-state-of-the-art, future challenges and research directions A Holzinger, M Dehmer, I Jurisica BMC bioinformatics 15, 1-9, 2014 | 285 | 2014 |
| Entropy and the complexity of graphs revisited A Mowshowitz, M Dehmer Entropy 14 (3), 559-570, 2012 | 246 | 2012 |
| A new coupled disease-awareness spreading model with mass media on multiplex networks C Xia, Z Wang, C Zheng, Q Guo, Y Shi, M Dehmer, Z Chen Information Sciences 471, 185-200, 2019 | 220 | 2019 |
| Statistical modelling of molecular descriptors in QSAR/QSPR K Varmuza, M Dehmer, D Bonchev Wiley Online Library, 2012 | 208 | 2012 |
| Extremality of degree-based graph entropies S Cao, M Dehmer, Y Shi Information Sciences 278, 22-33, 2014 | 201 | 2014 |
| Information fusion as an integrative cross-cutting enabler to achieve robust, explainable, and trustworthy medical artificial intelligence A Holzinger, M Dehmer, F Emmert-Streib, R Cucchiara, I Augenstein, ... Information Fusion 79, 263-278, 2022 | 200 | 2022 |
| Named entity recognition and relation detection for biomedical information extraction N Perera, M Dehmer, F Emmert-Streib Frontiers in cell and developmental biology 8, 673, 2020 | 181 | 2020 |
| A note on distance-based graph entropies Z Chen, M Dehmer, Y Shi Entropy 16 (10), 5416-5427, 2014 | 179 | 2014 |
| High-dimensional LASSO-based computational regression models: regularization, shrinkage, and selection F Emmert-Streib, M Dehmer Machine Learning and Knowledge Extraction 1 (1), 359-383, 2019 | 166 | 2019 |
| Networks for systems biology: conceptual connection of data and function F Emmert-Streib, M Dehmer IET systems biology 5 (3), 185-207, 2011 | 157 | 2011 |
| Understanding statistical hypothesis testing: The logic of statistical inference F Emmert-Streib, M Dehmer Machine Learning and Knowledge Extraction 1 (3), 945-962, 2019 | 145 | 2019 |
| Introduction to survival analysis in practice F Emmert-Streib, M Dehmer Machine Learning and Knowledge Extraction 1 (3), 1013-1038, 2019 | 143 | 2019 |
| On entropy-based molecular descriptors: Statistical analysis of real and synthetic chemical structures M Dehmer, K Varmuza, S Borgert, F Emmert-Streib Journal of chemical information and modeling 49 (7), 1655-1663, 2009 | 137 | 2009 |
Frank Emmert-StreibProfessor, Tampere University, Predictive Society and AI Labbio-complexity.com의 이메일 확인됨