Details

Autor(en) / Beteiligte

• Sperschneider, Jana
• Dodds, Peter N
• Gardiner, Donald M
• Manners, John M
• Singh, Karam B
• Taylor, Jennifer M
• Sheppard, Donald C

Titel

Advances and challenges in computational prediction of effectors from plant pathogenic fungi

Ist Teil von

• PLoS pathogens, 2015-05, Vol.11 (5), p.e1004806-e1004806

Ort / Verlag

United States: Public Library of Science

Erscheinungsjahr

2015

Quelle

MEDLINE

Beschreibungen/Notizen

•   Apoplastic effectors, in particular, often contain several disulfide bonds [17] and predicted secretomes of pathogenic fungi contain proteins with elevated levels of cysteines compared to all proteins (Fig 1A). [...]the criteria of small and cysteine-rich can be used to mine predicted secretomes for apoplastic effectors and reduce the number of candidates [18,19]. [...]an increase in the number of identified fungal effectors might enable machine learning approaches for unbiased prediction, which could lead to the discovery of protein properties common to fungal effectors.