| Integration of multiomics data with graph convolutional networks to identify new cancer genes and their associated molecular mechanisms R Schulte-Sasse, S Budach, D Hnisz, A Marsico Nature Machine Intelligence 3 (6), 513-526, 2021 | 147 | 2021 |
| TriPepSVM: de novo prediction of RNA-binding proteins based on short amino acid motifs A Bressin, R Schulte-Sasse, D Figini, EC Urdaneta, BM Beckmann, ... Nucleic acids research 47 (9), 4406-4417, 2019 | 55 | 2019 |
| Graph convolutional networks improve the prediction of cancer driver genes R Schulte-Sasse, S Budach, D Hnisz, A Marsico Artificial Neural Networks and Machine Learning–ICANN 2019: Workshop and …, 2019 | 36 | 2019 |
| Integration of Multi-Omics Data with Graph Convolutional Networks to Identify Cancer-Associated Genes R Schulte-Sasse PQDT-Global, 2021 | 1 | 2021 |
| Unsupervised learning of DNA sequence features using a convolutional restricted Boltzmann machine W Kopp, R Schulte-Sasse bioRxiv, 183095, 2017 | 1 | 2017 |
| Learning Representatives of Sequences using convoltutional restricted Boltzmann Machines. R Schulte-Sasse Dept. of Computational Molecular Biology, Max Planck Institute for Molecular …, 2016 | | 2016 |
Annalisa MarsicoHelmholtz Munich在 helmholtz-muenchen.de 的电子邮件经过验证
