Arian R. Jamasb

gRNAde: Geometric Deep Learning for 3D RNA inverse design

gRNAde designs RNA sequences based on 3D backbone structures using geometric deep learning, achieving higher native sequence recovery than Rosetta on benchmark tasks.

Decoding Surface Fingerprints for Protein-Ligand Interactions

The paper introduces a computational framework for fragment-based screening and binding affinity prediction using protein surface descriptors to identify ligands for challenging protein targets.

Predicted structural mimicry of spike receptor-binding motifs from highly pathogenic human coronaviruses

The paper identifies potential structural mimicry of coronavirus spike receptor-binding motifs by human and non-human proteins using structural bioinformatics and docking simulations.

Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Protein Structures and Interaction Networks

Graphein transforms bioinformatics data into machine learning-ready graph representations for geometric deep learning and network analysis.

Complete connectomic reconstruction of olfactory projection neurons in the fly brain

The paper reconstructs the complete connectome of olfactory projection neurons in the Drosophila brain and identifies new connectivity patterns in olfactory circuits.

Functional and Anatomical Specificity in a Higher Olfactory Centre

The paper identifies 165 cell types in the Drosophila lateral horn and shows that 33 of them have stereotyped odor responses, revealing principles of odor categorization in a higher olfactory center.