RSLpred 2.0

Rice protein localization

Predict subcellular localization of rice proteins.

RSLpred-2.0 uses rice-specific deep-learning models to predict protein subcellular localization through a four-level classification system.

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Scientific montage of a rice plant, plant cell organelles, a membrane, and a protein structure
TPC features
8,000
prediction levels
4
single classes
10
dual pairs
6

Prediction architecture

Four-level localization framework

The model narrows each sequence from broad localization behavior to the relevant cellular compartment or membrane topology.

  1. 01

    Single vs dual

    Primary routing

  2. 02

    10 classes

    Single localization

  3. 03

    6 pairs

    Dual localization

  4. 04

    Membrane type

    Single- or multi-pass

Method overview

RSLpred2 prediction workflow

Read the guide
RSLpred-2.0 workflow from rice protein sequence through tripeptide composition, convolutional neural networks, and four localization levels
RSLpred-2.0 four-level protein subcellular localization workflow.TPC · 8,000 features · CNN

Publication

Please cite RSLpred2

Duhan, N., & Kaundal, R. (2025). RSLpred2: An Integrated Web Server for the Annotation of Rice Proteome Subcellular Localization Using Deep Learning. Rice, 18, 58.DOI: 10.1186/s12284-025-00767-7