| POCOVID-Net: automatic detection of COVID-19 from a new lung ultrasound imaging dataset (POCUS) J Born, G Brändle, M Cossio, M Disdier, J Goulet, J Roulin, N Wiedemann ISMB TransMed (arXiv preprint 2004.12084), 2020 | 200* | 2020 |
| Accelerating detection of lung pathologies with explainable ultrasound image analysis J Born, N Wiedemann, M Cossio, C Buhre, G Brändle, K Leidermann, ... Applied Sciences 11 (2), 672, 2021 | 176* | 2021 |
| Toward explainable anticancer compound sensitivity prediction via multimodal attention-based convolutional encoders M Manica*, A Oskooei*, J Born*, V Subramanian, J Sáez-Rodríguez, ... Molecular Pharmaceutics 16 (12), 4797-4806, 2019 | 125 | 2019 |
| CogMol: Target-specific and Selective Drug Design for COVID-19 using Deep Generative Models V Chenthamarakshan, P Das, S Hoffman, H Strobelt, I Padhi, KW Lim, ... Advances in Neural Information Processing Systems, NeurIPS 2020, 2020 | 121* | 2020 |
| Covid-19 control by computer vision approaches: A survey A Ulhaq, J Born, A Khan, DPS Gomes, S Chakraborty, M Paul IEEE Access 8, 179437-179456, 2020 | 111 | 2020 |
| TITAN: T Cell Receptor Specificity Prediction with Bimodal Attention Networks A Weber, J Born, MR Martínez Bioinformatics 37 (ISMB Proceedings), 2021 | 110 | 2021 |
| PaccMannRL: De novo Generation of Hit-like Anticancer Molecules from Transcriptomic Data via Reinforcement Learning J Born*, M Manica*, A Oskooei*, J Cadow, G Markert, MR Martínez iScience 2021 / RECOMB 2020, 2021 | 86* | 2021 |
| On the Role of Artificial Intelligence in Medical Imaging of COVID-19 J Born, D Beymer, D Rajan, A Coy, VV Mukherjee, M Manica, P Prasanna, ... Patterns 2 (6), 100269, 2021 | 78 | 2021 |
| Regression Transformer enables concurrent sequence regression and generation for molecular language modelling J Born, M Manica Nature Machine Intelligence / Spotlight at ICLR Workshop on ML for Drug …, 2023 | 66* | 2023 |
| Unifying Molecular and Textual Representations via Multi-task Language Modelling D Christofidellis, G Giannone, J Born, O Winther, T Laino, M Manica International Conference on Machine Learning, ICML 2023, 2023 | 50 | 2023 |
| PaccMann: a web service for interpretable anticancer compound sensitivity prediction J Cadow*, J Born*, M Manica*, A Oskooei, M Rodríguez Martínez Nucleic acids research 48 (W1), W502-W508, 2020 | 45 | 2020 |
| Data-driven Molecular Design for Discovery and Synthesis of Novel Ligands-A case study on SARS-CoV-2 J Born, M Manica, J Cadow, G Markert, M Filipavicius, NA Mill, ... Machine Learning: Science and Technology / ICML 2020 Workshop on …, 2021 | 39* | 2021 |
| PaccMann: Prediction of Anticancer Compound Sensitivity with Multimodal Attention-based Neural Networks A Oskooei*, J Born*, M Manica*, V Subramanian, J Sáez-Rodríguez, ... NeurIPS Workshop on Molecules and Materials, 2018 | 37* | 2018 |
| Artificial intelligence driven design of catalysts and materials for ring opening polymerization using a domain-specific language NH Park, M Manica, J Born, JL Hedrick, T Erdmann, DY Zubarev, ... Nature Communications 14 (1), 3686, 2023 | 29* | 2023 |
| Active Site Sequence Representations of Human Kinases Outperform Full Sequence Representations for Affinity Prediction and Inhibitor Generation: 3D Effects in a 1D Model J Born, T Huynh, A Stroobants, WD Cornell, M Manica Journal of Chemical Information and Modeling / NeurIPS workshop on ML for …, 2022 | 22 | 2022 |
| Multimodal study of the effects of varying task load utilizing EEG, GSR and eye-tracking J Born, BRN Ramachandran, SA Romero Pinto, S Winkler, R Ratnam ICMB 2017 Short paper (bioRxiv), 798496, 2019 | 19* | 2019 |
| Chemical representation learning for toxicity prediction J Born, G Markert, N Janakarajan, TB Kimber, A Volkamer, MR Martínez, ... Digital Discovery 2 (3), 674-691, 2023 | 17* | 2023 |
| Accelerating material design with the generative toolkit for scientific discovery M Manica, J Born, J Cadow, D Christofidellis, A Dave, D Clarke, ... npj Computational Materials 9 (1), 69, 2023 | 14* | 2023 |
| Trends in Deep Learning for Property-driven Drug Design J Born, M Manica Current Medicinal Chemistry 28 (38), 7862-7886, 2021 | 14 | 2021 |
| Hebbian Learning of Hand-Centred Representations in a Hierarchical Neural Network Model of the Primate Visual System J Born, JM Galeazzi, SM Stringer PLoS One 12(5) / ICCV Workshop on Mutual Benefits of Cognitive and Computer …, 2017 | 12 | 2017 |
Matteo ManicaIBM Research在 zurich.ibm.com 的电子邮件经过验证
