Chainsaw: protein domain segmentation with fully convolutional neural networks.

ABSTRACT:

Motivation

Protein domains are fundamental units of protein structure and play a pivotal role in understanding folding, function, evolution, and design. The advent of accurate structure prediction techniques has resulted in an influx of new structural data, making the partitioning of these structures into domains essential for inferring evolutionary relationships and functional classification.

Results

This article presents Chainsaw, a supervised learning approach to domain parsing that achieves accuracy that surpasses current state-of-the-art methods. Chainsaw uses a fully convolutional neural network which is trained to predict the probability that each pair of residues is in the same domain. Domain predictions are then derived from these pairwise predictions using an algor

SUBMITTER: Wells J 

PROVIDER: S-EPMC11256964 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature