Gapped sequence alignment using artificial neural networks: application to the MHC class I system.
Journal:
Bioinformatics (Oxford, England)
PMID:
26515819
Abstract
MOTIVATION: Many biological processes are guided by receptor interactions with linear ligands of variable length. One such receptor is the MHC class I molecule. The length preferences vary depending on the MHC allele, but are generally limited to peptides of length 8-11 amino acids. On this relatively simple system, we developed a sequence alignment method based on artificial neural networks that allows insertions and deletions in the alignment.