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      Gapped sequence alignment using artificial neural networks: application to the MHC class I system.

      Bioinformatics (Oxford, England)

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          Abstract

          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.

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          Journal
          26515819
          10.1093/bioinformatics/btv639

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