Cargando…
MHCSeqNet: a deep neural network model for universal MHC binding prediction
BACKGROUND: Immunotherapy is an emerging approach in cancer treatment that activates the host immune system to destroy cancer cells expressing unique peptide signatures (neoepitopes). Administrations of cancer-specific neoepitopes in the form of synthetic peptide vaccine have been proven effective i...
Autores principales: | Phloyphisut, Poomarin, Pornputtapong, Natapol, Sriswasdi, Sira, Chuangsuwanich, Ekapol |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6540523/ https://www.ncbi.nlm.nih.gov/pubmed/31138107 http://dx.doi.org/10.1186/s12859-019-2892-4 |
Ejemplares similares
-
Improved image classification explainability with high-accuracy heatmaps
por: Preechakul, Konpat, et al.
Publicado: (2022) -
Label-free tumor cells classification using deep learning and high-content imaging
por: Piansaddhayanon, Chawan, et al.
Publicado: (2023) -
SVRMHC prediction server for MHC-binding peptides
por: Wan, Ji, et al.
Publicado: (2006) -
NetMHCpan-3.0; improved prediction of binding to MHC class I molecules integrating information from multiple receptor and peptide length datasets
por: Nielsen, Morten, et al.
Publicado: (2016) -
MHCVision: estimation of global and local false discovery rate for MHC class I peptide binding prediction
por: Pearngam, Phorutai, et al.
Publicado: (2021)