| Equivariant 3D-conditional diffusion model for molecular linker design I Igashov, H Stärk, C Vignac, A Schneuing, VG Satorras, P Frossard, ... Nature Machine Intelligence, 1-11, 2024 | 88 | 2024 |
| Structure-based drug design with equivariant diffusion models A Schneuing, Y Du, C Harris, A Jamasb, I Igashov, W Du, T Blundell, P Lió, ... arXiv preprint arXiv:2210.13695, 2022 | 83 | 2022 |
| VoroCNN: deep convolutional neural network built on 3D Voronoi tessellation of protein structures I Igashov, K Olechnovič, M Kadukova, Č Venclovas, S Grudinin Bioinformatics 37 (16), 2332-2339, 2021 | 33 | 2021 |
| Modeling SARS‐CoV‐2 proteins in the CASP‐commons experiment A Kryshtafovych, J Moult, WM Billings, D Della Corte, K Fidelis, S Kwon, ... Proteins: Structure, Function, and Bioinformatics 89 (12), 1987-1996, 2021 | 19 | 2021 |
| A new age in protein design empowered by deep learning H Khakzad, I Igashov, A Schneuing, C Goverde, M Bronstein, B Correia Cell Systems 14 (11), 925-939, 2023 | 16 | 2023 |
| Spherical convolutions on molecular graphs for protein model quality assessment I Igashov, N Pavlichenko, S Grudinin Machine Learning: Science and Technology 2 (4), 045005, 2021 | 15 | 2021 |
| Retrobridge: Modeling retrosynthesis with markov bridges I Igashov, A Schneuing, M Segler, M Bronstein, B Correia arXiv preprint arXiv:2308.16212, 2023 | 7 | 2023 |
| 6DCNN with roto-translational convolution filters for volumetric data processing D Zhemchuzhnikov, I Igashov, S Grudinin Proceedings of the AAAI Conference on Artificial Intelligence 36 (4), 4707-4715, 2022 | 4 | 2022 |
| Decoding surface fingerprints for protein-ligand interactions I Igashov, AR Jamasb, A Sadek, F Sverrisson, A Schneuing, P Lio, ... bioRxiv, 2022.04. 26.489341, 2022 | 4 | 2022 |
| The Second Learning on Graphs Conference: Preface S Villar, B Chamberlain, Y Du, H St, CK Joshi, A Deac, I Duta, J Robinson, ... Learning on Graphs Conference, i-xix, 2024 | | 2024 |
| Flexible Structure-based Design of Small Molecules with Equivariant Diffusion Models A Schneuing, Y Du, C Harris, K Didi, A Jamasb, I Igashov, W Du, ... PROTEIN SCIENCE 32 (12), 2023 | | 2023 |
| The First Learning on Graphs Conference: Preface B Rieck, R Pascanu, Y Du, H Stärk, D Lim, CK Joshi, A Deac, I Duta, ... Learning on Graphs Conference, i-xxiii, 2022 | | 2022 |
| Towards Structure-based Drug Design with Protein Flexibility A Schneuing, I Igashov, T Castiglione, MM Bronstein, B Correia ICLR 2024 Workshop on Generative and Experimental Perspectives for …, 0 | | |
