Instructions Output format Data Software

LOCALIZER: subcellular localization prediction of plant and effector proteins in the plant cell


Introduction

LOCALIZER is a machine learning method for subcellular localization prediction in plant cells. LOCALIZER has been trained to predict either the localization of plant proteins or the localization of eukaryotic effector proteins to chloroplasts, mitochondria or nuclei in the plant cell.

The localization to chloroplasts and mitochondria is predicted using the presence of transit peptides and the localization to nuclei is predicted using a collection of nuclear localization signals (NLSs).



Submission

To run LOCALIZER, please submit your full plant or effector proteins of interest below. LOCALIZER will not use proteins shorter than 40 aas for localization prediction.

For online submission, the maximum number of protein sequences that can be submitted is 2000. If you want to run LOCALIZER on your local machine, you can download the current version here.





Full plant sequences
Full effector sequences with signal peptides (first aas will be deleted)
Mature effector sequences without signal peptides





Citation

  • Sperschneider J et al. (2017) LOCALIZER: subcellular localization prediction of both plant and effector proteins in the plant cell. Scientific Reports

  • Contact

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



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