Ian Sillitoe

The paper introduces TEDLH, a library of domain HMMs derived from TED annotations, enabling sensitive detection of remote homologues and expanding coverage of sequence space and CATH superfamily diversity.

The paper introduces TED, a resource that segments and classifies over 370 million domains from the AlphaFold Protein Structure Database, expanding known structural domains and uncovering new structural interactions.

The paper predicts human and viral protein variants that enhance SARS-CoV-2 binding affinity and may increase COVID-19 susceptibility.

Chainsaw uses a fully convolutional neural network to predict protein domain boundaries, achieving higher accuracy than existing methods in domain segmentation.

ModelCIF extends the PDBx/mmCIF standard to represent predicted 3D protein models, enabling FAIR data sharing for computational structural biology.

The paper uses AlphaFold2 to analyze protein structures from 21 organisms, identifying 26 novel superfamilies and expanding structural diversity insights.

The paper introduces CATHe, a method using protein language model embeddings to detect remote homologues for CATH superfamilies, achieving high accuracy and validating predictions with AlphaFold structures.

The paper analyzes amino acid composition and structural patterns in peripheral membrane protein interfaces using experimental and AlphaFold models to identify key residues and functional motifs.

The paper collects and predicts structures of ABC transmembrane proteins using AlphaFold2 and presents them via a web application.

The paper predicts structures of disease-associated proteins without known structures, identifies functional sites, and explains 80% of mutations based on their proximity to these sites or structural impact.

This paper introduces ProtTucker, a contrastive learning method using protein embeddings from pLMs to improve recognition of distant homologous relationships in the midnight zone of protein similarity.

3D-Beacons provides a federated network to unify access to protein structure data from multiple sources, enabling comparative analysis of models.

The paper predicts SARS-CoV-2 spike protein interactions with ACE2 orthologues across 215 vertebrates, finds mutations in ACE2 are more detrimental, and shows human strains are present in animals.

The paper assesses the value and sustainability of ELIXIR Core Data Resources, showing their critical role in preserving biological data and highlighting funding challenges.

The paper reports results from the CAFA3 challenge, showing improved computational protein function prediction and new annotations for over 1000 genes through experimental screens in C. albicans, P. aureginosa, and Drosophila.