EffHunter: A tool for prediction of effector protein candidates in fungal proteomic databases

Pathogens are able to deliver small-secreted, cysteine-rich proteins into plant cells to enable infection. The computational prediction of effector proteins remains one of the most challenging areas in the study of plant fungi interactions. At present, there are several bioinformatic programs that can help in the identification of these proteins; however, in most cases, these programs are managed independently. Here, we present EffHunter, an easy and fast bioinformatics tool for the identification of effectors. This predictor was used to identify putative effectors in 88 proteomes using characteristics such as size, cysteine residue content, secretion signal and transmembrane domains.

Bibliographic Details

Main Authors:	Karla Gisel Carreón Anguiano, Ignacio Rodrigo Islas Flores, Julio Vega-Arreguin, Luis Alfonso Sáenz Carbonell, Blondy Beatriz Canto Canché
Format:	info:eu-repo/semantics/article biblioteca
Language:	eng
Subjects:	info:eu-repo/classification/Autores/COMPUTATIONAL PREDICTION, info:eu-repo/classification/Autores/HOST-PATHOGEN INTERACTION, info:eu-repo/classification/Autores/EFFECTOR PROTEINS, info:eu-repo/classification/Autores/FUNGAL SECRETOME, info:eu-repo/classification/cti/2, info:eu-repo/classification/cti/24, info:eu-repo/classification/cti/2415, info:eu-repo/classification/cti/241502,
Online Access:	http://cicy.repositorioinstitucional.mx/jspui/handle/1003/1820
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