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Predicts if a protein is localized to the plant apoplast. ApoplastP is a data-driven machine learning approach. It outperforms the common approach of selecting apoplastic effectors from secretomes based on a high cysteine content, improving prediction accuracy by over 13%. This method also recognizes the localization of cytoplasmic effectors with high accuracy, even if they enter the plant cell cytoplasm from apoplast.

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ApoplastP versioning

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ApoplastP classification

ApoplastP specifications

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Command line interface
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ApoplastP support


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Centre for Environment and Life Sciences, CSIRO Agriculture and Food, Perth, WA, Australia; Black Mountain Laboratories, CSIRO Agriculture and Food, Canberra, ACT, Australia; Centre for Crop and Disease Management, Department of Environment and Agriculture, Curtin University, Bentley, Western Australia, Australia

Funding source(s)

Supported by a CSIRO OCE Postdoctoral Fellowship.

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