July 11, 2023
Report

Structural- and Functional-Informed Machine Learning for Protein Function Prediction

Abstract

In this project we aimed to extend methods for protein function prediction to include structural prediction data, and benchmark methods against existing tools. We proposed to apply the method to large metagenome datasets, and develop approaches to examine activity-based protein profiling results for protein function-structure patterns. Nitrogen cycle protein families were previously identified and are used here to provide a proof-of-principle for use of structure prediction in protein function classification.

Published: July 11, 2023

Citation

McDermott J.E., S. Feng, C.H. Chang, D.J. Schmidt, and V.G. Danna. 2021. Structural- and Functional-Informed Machine Learning for Protein Function Prediction Richland, WA: Pacific Northwest National Laboratory.

Research topics