Arian Jamasb
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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
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
Protein representation learning by geometric structure pretraining
Z Zhang, M Xu, A Jamasb, V Chenthamarakshan, A Lozano, P Das, ...
ICLR 2023, 2022
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
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
Structure-based drug design with equivariant diffusion models
A Schneuing, Y Du, C Harris, A Jamasb, I Igashov, W Du, T Blundell, P Liˇ, ...
arXiv preprint arXiv:2210.13695, 2022
Graphein-a Python Library for Geometric Deep Learning and Network Analysis on Biomolecular Structures and Interaction Networks
AR Jamasb, RV TornÚ, EJ Ma, Y Du, C Harris, K Huang, D Hall, P Lio, ...
NeurIPS 2022, 2022
GAUCHE: A library for Gaussian processes in chemistry
RR Griffiths, L Klarner, HB Moss, A Ravuri, S Truong, B Rankovic, Y Du, ...
NeurIPS 2023, 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
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
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
Structure-aware generation of drug-like molecules
P Drotßr, AR Jamasb, B Day, C Cangea, P Li˛
arXiv preprint arXiv:2111.04107, 2021
Deep learning for protein–protein interaction site prediction
AR Jamasb, B Day, C Cangea, P Li˛, TL Blundell
Proteomics Data Analysis, 263-288, 2021
Message Passing Neural Processes
C Cangea, B Day, AR Jamasb, P Lio
ICLR 2022 Workshop on Geometrical and Topological Representation Learning, 2022
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
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
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
Multi-State RNA Design with Geometric Multi-Graph Neural Networks
CK Joshi, AR Jamasb, R Vi˝as, C Harris, S Mathis, P Li˛
arXiv preprint arXiv:2305.14749, 2023
Flexible Small-Molecule Design and Optimization with Equivariant Diffusion Models
C Harris, K Didi, A Schneuing, Y Du, AR Jamasb, MM Bronstein, ...
ICLR 2023-Machine Learning for Drug Discovery workshop, 2023
GrapHiC-A Python library for creating bespoke graph datasets from Hi-C & Multi-omics data
D Hall, AR Jamasb, M Rozenwald, P Liˇ
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