Immune2vec: Embedding B/T Cell Receptor Sequences in ℝ ^N Using Natural Language Processing.

ABSTRACT: The adaptive branch of the immune system learns pathogenic patterns and remembers them for future encounters. It does so through dynamic and diverse repertoires of T- and B- cell receptors (TCR and BCRs, respectively). These huge immune repertoires in each individual present investigators with the challenge of extracting meaningful biological information from multi-dimensional data. The ability to embed these DNA and amino acid textual sequences in a vector-space is an important step towards developing effective analysis methods. Here we present Immune2vec, an adaptation of a natural language processing (NLP)-based embedding technique for BCR repertoire sequencing data. We validate Immune2vec on amino acid 3-gram sequences, continuing to longer BCR sequences, and finally to entire repertoi

SUBMITTER: Ostrovsky-Berman M 

PROVIDER: S-EPMC8340020 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature