GraphProt is a computational framework for learning sequence- and structure-binding preferences of RNA-binding proteins (RBPs) from high-throughput experimental data such as CLIP-seq data. After model training, the learned sequence or structure models can be applied to predict RBP binding profiles on FASTA sequences. |
hg clone https://toolshed.g2.bx.psu.edu/repos/rnateam/graphprot_predict_profile
Name | Description | Version | Minimum Galaxy Version |
---|---|---|---|
- Train models and predict RBP binding profiles | 1.1.7+galaxy2 | 23.1 |