Standalone command-line package
Run RSLpred-2.0 locally
Download the rice protein localization models, Python utilities, TFLite inference engine, and example inputs for reproducible local analysis.
Protein FASTA
Accepts one or more amino-acid sequences. Nucleotide sequences are not supported.
Two strategies
Choose Fast dipeptide features or Sensitive tripeptide features.
Research software
Download the standalone package for local research use. Reuse rights remain reserved unless a license is added.
Recommended setup
Install with conda
# 1. Extract the package
tar -xvzf RSLpred-2.0.tar.gz
cd RSLpred-2.0
# 2. Create the recommended conda environment
conda env create -f environment.yml
conda activate RSLpred2
# 3. Install RSLpred-2.0
pip3 install .Alternative setup
Install with system Python 3
Use this route only when the required dependencies are already available in your Python environment.
tar -xvzf RSLpred-2.0.tar.gz
cd RSLpred-2.0
pip3 install .Example command
Run a prediction
python RSLpred2.py -i ./example/test.fasta -o output -l level4 -m fast-iInput FASTA file-oOutput directory-lHighest prediction level-mfast or sensitive strategy