NeoAntigens Prediction@CNB (NAP-CNB)
NeoAntigens Prediction@CNB (NAP-CNB) is a tool for the prediction of neoantigenic peptides from RNA-seq or protein data. It provides a list of putative neoantigens along with some predictions associated with each sequence. NAP-CNB uses variant calling methods for the identification of mutations in the samples. It also uses neural networks to predict on the mutant peptides in order to output a list of putative neoantigens. It allows to analyze protein sequences and RNA-seq sequences obtained by next generation sequencing methods.
Info
Members (researchers): Esteban Veiga Chacón
Research Groups: Bacteria-based immunotherapies against cancer
Contact Email: jr.macias@cnb.csic.es
Tool Repository: https://biocomp.cnb.csic.es/NeoantigensApp/
Documentation: https://biocomp.cnb.csic.es/NeoantigensApp/NeoantigensApp/about/
Publications DOI: http://dx.doi.org/10.21203/rs.3.rs-209367/v1
Applications of Computational Biology, Artificial Intelligence, Bioinformatics Software and Tools, Data Analysis, Deep Learning in Biology, Drug Discovery and design, Genomic Annotation, Genomics, Machine Learning in Biology, Model organisms, Personal medicine, Single-cell omics, Web-service
Technical details
Type of application
- Web-service
Software compatibility
- Linux
- Mac
- Windows
Hardware requirements
Programming language
- BASH
- Java
- JavaScript
- mySQL
- Python
- R
Type of containerization
- Docker
Wrapper type
- None
Input file formats
- json
Output file formats
- csv
- fasta
- tsv

