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, NA Mill, M Filipavicius, ... Machine Learning: Science and Technology 2 (2), 025024, 2021 | 37* | 2021 |
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 | 11 | 2023 |
A fully differentiable set autoencoder N Janakarajan, J Born, M Manica Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 5 | 2022 |
Attention-based interpretable regression of gene expression in histology M Graziani, N Marini, N Deutschmann, N Janakarajan, H Müller, ... International Workshop on Interpretability of Machine Intelligence in …, 2022 | 4 | 2022 |
Language Models in Molecular Discovery N Janakarajan, T Erdmann, S Swaminathan, T Laino, J Born NeurIPS 2023 AI for Science Workshop, 2023 | 2 | 2023 |
Language models in molecular discovery N Janakarajan, T Erdmann, S Swaminathan, T Laino, J Born arXiv:2309.16235, 2023, 2023 | 2 | 2023 |
Survboard: standardised benchmarking for multi-omics cancer survival models D Wissel, N Janakarajan, A Grover, E Toniato, MR Martínez, V Boeva bioRxiv, 2022.11. 18.517043, 2022 | 1 | 2022 |
Signature Informed Sampling for Transcriptomic Data N Janakarajan, M Graziani, MR Martinez bioRxiv, 2023.10. 26.564263, 2023 | | 2023 |