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http://cicy.repositorioinstitucional.mx/jspui/handle/1003/1820| EffHunter: A tool for prediction of effector protein candidates in fungal proteomic databases | |
| Karla Gisel Carreón Anguiano Ignacio Rodrigo Islas Flores Julio Vega-Arreguin Luis Alfonso Sáenz Carbonell Blondy Beatriz Canto Canché | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| doi:10.3390/biom10050712 | |
| COMPUTATIONAL PREDICTION HOST-PATHOGEN INTERACTION EFFECTOR PROTEINS FUNGAL SECRETOME | |
| 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. | |
| 2020 | |
| Artículo | |
| Biomolecules, 10(5), 712, 2020. | |
| Inglés | |
| BIOLOGÍA MOLECULAR DE PLANTAS | |
| Versión publicada | |
| publishedVersion - Versión publicada | |
| Aparece en las colecciones: | Artículos de Investigación Arbitrados |
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|---|---|---|---|
| 2020_Carreón_Anguiano.pdf | 1.02 MB | Adobe PDF | Visualizar/Abrir |