Utilizing graph machine learning within drug discovery and development T Gaudelet, B Day, AR Jamasb, J Soman, C Regep, G Liu, JBR Hayter, ... Briefings in bioinformatics 22 (6), bbab159, 2021 | 326 | 2021 |
Protein representation learning by geometric structure pretraining Z Zhang, M Xu, A Jamasb, V Chenthamarakshan, A Lozano, P Das, ... ICLR 2023, 2023 | 209 | 2023 |
Structure-based drug design with equivariant diffusion models A Schneuing, C Harris, Y Du, K Didi, A Jamasb, I Igashov, W Du, ... arXiv preprint arXiv:2210.13695, 2022 | 209* | 2022 |
Complete Connectomic Reconstruction of Olfactory Projection Neurons in the Fly Brain AS Bates, P Schlegel, RJV Roberts, N Drummond, IFM Tamimi, ... Current Biology 30 (16), 3183-3199.e6, 2020 | 171 | 2020 |
Functional and anatomical specificity in a higher olfactory centre S Frechter, AS Bates, S Tootoonian, MJ Dolan, J Manton, AR Jamasb, ... Elife 8, e44590, 2019 | 103 | 2019 |
Ethoscopes: An open platform for high-throughput ethomics Q Geissmann, L Garcia Rodriguez, EJ Beckwith, AS French, AR Jamasb, ... PLoS biology 15 (10), e2003026, 2017 | 96 | 2017 |
GAUCHE: A library for Gaussian processes in chemistry RR Griffiths*, L Klarner*, HB Moss*, A Ravuri*, S Truong*, B Rankovic*, ... NeurIPS 2023, 2022 | 79* | 2022 |
Graphein-a Python Library for Geometric Deep Learning and Network Analysis on Biomolecular Structures and Interaction Networks AR Jamasb, RV Torné, EJ Ma, Y Du, C Harris, K Huang, D Hall, P Lio, ... NeurIPS 2022, 2022 | 63* | 2022 |
Data-driven discovery of molecular photoswitches with multioutput Gaussian processes RR Griffiths, JL Greenfield, AR Thawani, AR Jamasb, HB Moss, ... Chemical Science 13 (45), 13541-13551, 2022 | 54* | 2022 |
Posecheck: Generative models for 3d structure-based drug design produce unrealistic poses C Harris, K Didi, A Jamasb, C Joshi, S Mathis, P Lio, T Blundell NeurIPS 2023 Generative AI and Biology (GenBio) Workshop, 2023 | 40* | 2023 |
SARS-CoV-2 3D database: understanding the coronavirus proteome and evaluating possible drug targets AF Alsulami*, SE Thomas*, AR Jamasb*, CA Beaudoin*, I Moghul*, ... Briefings in bioinformatics 22 (2), 769-780, 2021 | 40 | 2021 |
Predicted structural mimicry of spike receptor-binding motifs from highly pathogenic human coronaviruses CA Beaudoin, AR Jamasb, AF Alsulami, L Copoiu, AJ van Tonder, S Hala, ... Computational and Structural Biotechnology Journal 19, 3938-3953, 2021 | 37 | 2021 |
Machine learning-aided generative molecular design Y Du*, AR Jamasb*, J Guo*, T Fu, C Harris, Y Wang, C Duan, P Liò, ... Nature Machine Intelligence, 1-16, 2024 | 29* | 2024 |
Structure-aware generation of drug-like molecules P Drotár, AR Jamasb, B Day, C Cangea, P Liò NeurIPS 2021 Workshop on Machine Learning for Structural Biology, 2021 | 26 | 2021 |
Deep learning for protein–protein interaction site prediction AR Jamasb, B Day, C Cangea, P Liò, TL Blundell Proteomics data analysis, 263-288, 2021 | 22* | 2021 |
gRNAde: Geometric Deep Learning for 3D RNA inverse design CK Joshi, AR Jamasb, R Viñas, C Harris, SV Mathis, A Morehead, ... bioRxiv, 2024 | 14* | 2024 |
On graph neural network ensembles for large-scale molecular property prediction EE Kosasih, J Cabezas, X Sumba, P Bielak, K Tagowski, K Idanwekhai, ... arXiv preprint arXiv:2106.15529, 2021 | 13 | 2021 |
Message passing neural processes C Cangea, B Day, AR Jamasb, P Lio ICLR 2022 Workshop on Geometrical and Topological Representation Learning, 2022 | 10* | 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 | 7* | 2022 |
Evaluating Representation Learning on the Protein Structure Universe AR Jamasb*, A Morehead*, CK Joshi*, Z Zhang*, K Didi, SV Mathis, ... ICLR 2024, 14, 2024 | 5 | 2024 |