PSIONplusm Server for Accurate Multi-Label Prediction of Ion Channels and Their Types.

Biomolecules
Jianzhao GaoLukasz Kurgan

Abstract

Computational prediction of ion channels facilitates the identification of putative ion channels from protein sequences. Several predictors of ion channels and their types were developed in the last quindecennial. While they offer reasonably accurate predictions, they also suffer a few shortcomings including lack of availability, parallel prediction mode, single-label prediction (inability to predict multiple channel subtypes), and incomplete scope (inability to predict subtypes of the voltage-gated channels). We developed a first-of-its-kind PSIONplusm method that performs sequential multi-label prediction of ion channels and their subtypes for both voltage-gated and ligand-gated channels. PSIONplusm sequentially combines the outputs produced by three support vector machine-based models from the PSIONplus predictor and is available as a webserver. Empirical tests show that PSIONplusm outperforms current methods for the multi-label prediction of the ion channel subtypes. This includes the existing single-label methods that are available to the users, a naïve multi-label predictor that combines results produced by multiple single-label methods, and methods that make predictions based on sequence alignment and domain annotations....Continue Reading

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Methods Mentioned

BETA
sequence-based prediction

Software Mentioned

PSION ION
IonchanPred2
PSION VLG
BLAST
PSION VGS
HIT
PSIONplus m
PSIONplus
PSIONplus predictor
VGIchan

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