Instructions Output format Data Software

EffectorP: predicting fungal effector proteins from secretomes using machine learning

Introduction

EffectorP is a machine learning method for fungal effector prediction in secretomes. EffectorP has been trained to distinguish secreted proteins from secreted effectors in plant-pathogenic fungi.


Submission

To run EffectorP, please submit your secreted fungal proteins of interest below. For online submission, the maximum number of protein sequences that can be submitted is 4000. If you want to run EffectorP on your local machine, you can download the current version here.







EffectorP 1.0
EffectorP 2.0



Citation for EffectorP 1.0

  • Sperschneider J, Gardiner DM, Dodds PN, Tini F, Covarelli L, Singh KB, Manners JM, Taylor JM (2015) EffectorP: Predicting Fungal Effector Proteins from Secretomes Using Machine Learning. New Phytologist, doi:10.1111/nph.13794. Abstract

    • Citation for EffectorP 2.0

  • Sperschneider J, Dodds PN, Gardiner DM, Singh KB, Taylor JM (2018) Improved prediction of fungal effector proteins from secretomes with EffectorP 2.0. Molecular Plant Pathology. Abstract

    • Contact

    For comments, suggestions and reporting bugs please contact jana.sperschneider@csiro.au


    Terms of use

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