Sulfur-Containing Compound Genes (SCCGs) Prediction Model
Screen protein sequences for candidate genes associated with sulfur-containing compound biology.
About this model
The SCCGs prediction service classifies FASTA protein sequences with support vector machine models based on K-mer and pseudo-amino-acid-composition features. Predictions provide candidates for downstream annotation and experimental assessment.
- Input
- One or more protein sequences in FASTA format.
- Models
- SVM with K-mer, or K-mer combined with PC-PseAAC features.
- Output
- Sequence-level SCCG prediction results.
SCCGs prediction workspace
The SCCP analysis interface is embedded below.
This is a computational prediction service. Confirm candidate functions with independent annotation or experiments. If the interface does not load, use Open in new window.