EnsembleFam: towards more accurate protein family prediction in the twilight zone.

ABSTRACT:

Background

Current protein family modeling methods like profile Hidden Markov Model (pHMM), k-mer based methods, and deep learning-based methods do not provide very accurate protein function prediction for proteins in the twilight zone, due to low sequence similarity to reference proteins with known functions.

Results

We present a novel method EnsembleFam, aiming at better function prediction for proteins in the twilight zone. EnsembleFam extracts the core characteristics of a protein family using similarity and dissimilarity features calculated from sequence homology relations. EnsembleFam trains three separate Support Vector Machine (SVM) classifiers for each family using these features, and an ensemble prediction is made to classify novel proteins into these families. Ext

SUBMITTER: Kabir MN 

PROVIDER: S-EPMC8919565 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature