RF-Phos: A Novel General Phosphorylation Site Prediction Tool Based on Random Forest.

Abstract:

:Protein phosphorylation is one of the most widespread regulatory mechanisms in eukaryotes. Over the past decade, phosphorylation site prediction has emerged as an important problem in the field of bioinformatics. Here, we report a new method, termed Random Forest-based Phosphosite predictor 2.0 (RF-Phos 2.0), to predict phosphorylation sites given only the primary amino acid sequence of a protein as input. RF-Phos 2.0, which uses random forest with sequence and structural features, is able to identify putative sites of phosphorylation across many protein families. In side-by-side comparisons based on 10-fold cross validation and an independent dataset, RF-Phos 2.0 compares favorably to other popular mammalian phosphosite prediction methods, such as PhosphoSVM, GPS2.1, and Musite.

journal_name

Biomed Res Int

authors

Ismail HD,Jones A,Kim JH,Newman RH,Kc DB

doi

10.1155/2016/3281590

subject

Has Abstract

pub_date

2016-01-01 00:00:00

pages

3281590

eissn

2314-6133

issn

2314-6141

journal_volume

2016

pub_type

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