Large scale identification and categorization of protein sequences using structured logistic regression.

ABSTRACT:

Background

Structured Logistic Regression (SLR) is a newly developed machine learning tool first proposed in the context of text categorization. Current availability of extensive protein sequence databases calls for an automated method to reliably classify sequences and SLR seems well-suited for this task. The classification of P-type ATPases, a large family of ATP-driven membrane pumps transporting essential cations, was selected as a test-case that would generate important biological information as well as provide a proof-of-concept for the application of SLR to a large scale bioinformatics problem.

Results

Using SLR, we have built classifiers to identify and automatically categorize P-type ATPases into one of 11 pre-defined classes. The SLR-classifiers are compared to a H

SUBMITTER: Pedersen BP 

PROVIDER: S-EPMC3896382 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature