EffectorP: predicting fungal effector proteins from secretomes using machine learning.

By Jana Sperschneider, D. Gardiner, P. Dodds, F. Tini, L. Covarelli, Karam B. Singh, John Manners, Jennifer M. Taylor. New Phytologist, 2016

359 citations recorded by the source corpus.

Subfields: Cell Biology, Molecular Biology, Plant Science

View Paper: https://www.semanticscholar.org/paper/057c8d8fbc57a6170a72460da69a45bf133a1f1b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

1. Jana Sperschneider
2. P. Dodds

In Plant Science

1. Jana Sperschneider
2. P. Dodds

Citations in the corpus

• EffectorP 3.0: prediction of apoplastic and cytoplasmic effectors in fungi and oomycetes (2021, methodology): “However, the current version of EffectorP has been trained only on fungal effectors, not oomycete effectors, and does not return the most likely localization of the effector (Sperschneider et al., 2016; Sperschneider et al., 2018a).”