Arian

Jamasb

Deep Learning for Protein-Protein Interaction Site Prediction Arian R. Jamasb, Ben Day, Cătălina Cangea, Pietro Liò, Tom L. Blundell.
Proteomics Data Analysis. Methods in Molecular Biology.

Structure-based Drug Design with Equivariant Diffusion Models. Arne Schneuing, Yuanqi Du, Charles Harris, Kieran Didi, Arian R. Jamasb, Ilia Igashov, Weitao Du, Tom Blundell, Pietro Lió, Carla Gomes, Max Welling, Michael Bronstein, Bruno Correia.
Nature Computational Science

Ensemble Guidance: Towards Generative 3D SBDD in Bioactive Chemical Spaces Charlie Harris, Arian R. Jamasb, Pietro Lio, Tom L. Blundell
ICML-W AI4Science, ICML-W ML4LMS

RNA-FrameFlow: Flow Matching for de novo 3D RNA Backbone Design Rishabh Anand, Chaitanya K. Joshi, Alex Morehead, Arian R. Jamasb, Charlie Harris, Simon V. Mathis, Kieran Didi, Bryan Hooi, Pietro Lio
ICML-W SPIGM (Oral), ICML-W AI4Science (Spotlight)

Structure-based drug design by denoising voxel grids Pedro O. Pinheiro, Arian R. Jamasb, Omar Mahmood, Vishnu Sresht, Saeed Saremi
ICML

Machine Learning-Aided Generative Molecular Design Yuanqi Du*, Arian R. Jamasb*, Jeff Guo*, Tianfan Fu, Charles Harris, Yingheng Wang, Chenru Duan, Pietro Liò, Philippe Schwaller, Tom L. Blundell
Nature Machine Intelligence

Evaluating Representation Learning on the Protein Structure Universe Arian R. Jamasb*, Alex Morehead*, Chaitanya K. Joshi*, Zuobai Zhang*, Kieran Didi, Simon V. Mathis, Charles Harris, Jian Tang, Jianlin Cheng, Pietro Lio, Tom Leon Blundell
ICLR

Benchmarking Generated Poses: How Rational is Structure-based Drug Design with Generative Models? Charlie Harris, Kieran Didi, Arian R. Jamasb, Chaitanya K. Joshi, Simon V. Mathis, Pietro Lio, Tom L. Blundell.
NeurIPS-W MLSB (Oral)

GAUCHE: A Library for Gaussian Processes in Chemistry Ryan-Rhys Griffiths*, Leo Klarner*, Henry Moss*, Aditya Ravuri*, Sang T. Truong*, Bojana Rankovic*, Yuanqi Du*, Arian R. Jamasb*, Aryan Deshwal, Julius Schwartz, Austin Tripp, Gregory Kell, Simon Frieder, Anthony Bourached, Alex Chan, Jacob Moss, Chengzhi Guo, Johannes Durholt, Saudamini Chaurasia, Felix Strieth-Kalthoff, Alpha A. Lee, Bingqing Cheng, Alan Aspuru-Guzik, Philippe Schwaller, Jian Tang
NeurIPS 2023, NeurIPS-W AI4Science, ELLIS-W ML4Molecules (Oral)

Multi-State RNA Design with Geometric Multi-Graph Neural Networks Chaitanya K. Joshi, Arian R. Jamasb, Ramon Viñas, Charles Harris, Simon V. Mathis, Pietro Liò
ICML-W Computational Biology

Protein Representation Learning by Geometric Structure Pretraining Zuobai Zhang, Minghao Xu, Arian R. Jamasb, Vijil Chenthamarakshan, Aurelie Lozano, Payel Das, Jian Tang.
ICLR

Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Biomolecular Structures and Interaction Networks. Arian R. Jamasb, Ramon Vinas Torne, Eric J. Ma, Yuanqi Du, Kexin Huang, Dominic Hall, Pietro Liò, Tom L. Blundell.
NeurIPS

Data-driven Discovery of Molecular Photoswitches with Multioutput Gaussian processes Ryan-Rhys Griffiths, Jake L Greenfield, Aditya R Thawani, Arian R. Jamasb, Henry B Moss, Anthony Bourached, Penelope Jones, William McCorkindale, Alexander A Aldrick, Matthew J Fuchter.
Chemical Science

Decoding Surface Fingerprints for Protein-Ligand Interactions Ilia Igashov, Arian R. Jamasb, Ahmed Sadek, Freyr Sverrisson, Arne Schneuing, Pietro Lio, Tom L Blundell, Michael Bronstein, Bruno F. Correia.
ICLR-W MLDD

Message Passing Neural Processes Ben Day, Cătălina Cangea, Arian R. Jamasb, Pietro Liò.
ICLR 2022 Workshop on Geometrical and Topological Representation Learning

Structure-aware Generation of Drug-like Molecules Pavol Drotár, Arian R. Jamasb, Ben Day, Cătălina Cangea, Pietro Liò
NeurIPS-W MLSB (Oral)

Predicted Structural Mimicry of Spike Receptor-Binding Motifs From Highly Pathogenic Human Coronaviruses Christopher A. Beaudoin, Arian R. Jamasb, Ali F. Alsulami, Liviu Copoiu, Andries J. van Tonder, Sharif Hala, Bridget P. Bannerman, Sherine E. Thomas, Sundeep C. Vedithi, Pedro H. M. Torres, Tom L. Blundell.
Computational and Structural Biotechnology Journal

Utilising Graph Machine Learning within Drug Discovery and Development Thomas Gaudelet, Ben Day, Arian R. Jamasb, Jyothish Soman, Cristian Regep, Gertrude Liu, Jeremy B. R. Hayter, Richard Vickers, Charles Roberts, Jian Tang, David Roblin, Tom L. Blundell, Michael M. Bronstein, Jake P. Taylor-King.
Briefings in Bioinformatics

SARS-CoV-2 3D database: Understanding the Coronavirus Proteome and Evaluating Possible Drug Targets Ali Alsulami*, Sherine Thomas*, Arian R. Jamasb*, Christopher Beaudoin*, Ismail Moghul*, Bridget Bannerman, Liviu Copoiu, Sundeep Vedithi*, Pedro Torres*, Tom Blundell.
Briefings in Bioinformatics

Complete Connectomic Reconstruction of Olfactory Projection Neurons in the Fly Brain. Alexander S. Bates*, Philipp Schlegel*, Ruairí J. V. Roberts, Nikolas Drummond, Imaan F. M. Tamimi, Robert G. Turnbull, Xincheng Zhao, Elizabeth C. Marin, Patricia D. Popovici, Serene Dhawan, Arian R. Jamasb, Alexandre Javier, Feng Li, Gerald M. Rubin, Scott Waddell, Davi D. Bock, Marta Costa, Gregory S. X. E. Jefferis.
Current Biology

Functional and Anatomical Specificity in a Higher Olfactory Centre. Shahar Frechter, Alexander S. Bates, Sina Tootoonian, Michael-John Dolan, James D. Manton, Arian R. Jamasb, Johannes Kohl, Davi Bock, Gregory S.X.E. Jefferis.
eLife

Ethoscopes: An open platform for high-throughput ethomics. Quentin Geissmann, Luis Garcia Rodriguez, Esteban J. Beckwith, Alice S. French, Arian R. Jamasb, Giorgio F. Gilestro.
PLOS Biology

Antibody DomainBed: Out-of-Distribution Generalization in Therapeutic Protein Design Nataša Tagasovska, Ji Won Park, Matthieu Kirchmeyer, Nathan C. Frey, Andrew Martin Watkins, Aya Abdelsalam Ismail, Arian R. Jamasb, Edith Lee, Tyler Bryson, Stephen Ra, Kyunghyun Cho
arXiv

On Graph Neural Network Ensembles for Large-Scale Molecular Property Prediction Edward E. Kosasih, Joaquin Cabezas, Xavier Sumba, Piotr Bielak, Kamil Tagowski, Kelvin Idanwekhai, Benedict A. Tjandra, Arian R. Jamasb.
arXiv