Alperen Dalkıran

On the state of protein function prediction: a report on the fourth CAFA challenge

This paper reports on the fourth CAFA challenge, showing improvements in Gene Ontology term prediction but highlighting challenges in new evaluation settings.

Transfer Learning Enables Drug-Target Interaction Prediction in Data-Scarce One-Carbon Metabolism

The paper uses transfer learning to predict drug-target interactions for mitochondrial one-carbon metabolism enzymes with limited data, identifying potential repurposable drugs.

Molecular Contrastive Learning with Graph Attention Network (MoCL-GAT) for Enhanced Molecular Representation

The paper introduces MoCL-GAT, a self-supervised learning framework for molecular representation, achieving state-of-the-art performance on molecular property prediction tasks.

Signatures of Electron-hole Hopping in Myoglobin Peroxidase Activity Revealed by Deep Mutational Learning

This study uses deep mutational learning to identify myoglobin variants with enhanced peroxidase activity, showing the role of electron-hole hopping in catalytic efficiency.

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

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.