Título

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

Autor

Karla Gisel Carreón Anguiano

Ignacio Rodrigo Islas Flores

Julio Vega-Arreguin

Luis Alfonso Sáenz Carbonell

Blondy Beatriz Canto Canché

Nivel de Acceso

Acceso Abierto

Licencia

http://creativecommons.org/licenses/by-nc-nd/4.0

Referencia de datos

datasetDOI/doi:10.3390/biom10050712

Materias

COMPUTATIONAL PREDICTION - (AUTORES) HOST-PATHOGEN INTERACTION - (AUTORES) EFFECTOR PROTEINS - (AUTORES) FUNGAL SECRETOME - (AUTORES) BIOLOGÍA Y QUÍMICA - (CTI) CIENCIAS DE LA VIDA - (CTI) BIOLOGÍA MOLECULAR - (CTI) BIOLOGÍA MOLECULAR DE PLANTAS - (CTI) BIOLOGÍA MOLECULAR DE PLANTAS - (CTI)

Resumen o descripción

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.

Fecha de publicación

2020

Tipo de publicación

Artículo

Versión de la publicación

Versión publicada

Recurso de información

http://cicy.repositorioinstitucional.mx/jspui/handle/1003/1820

Formato

application/pdf

Fuente

Biomolecules, 10(5), 712, 2020.

Idioma

Inglés

Repositorio Orígen

Repositorio Institucional CICY

Descargas

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