Graph-based data structure for enumeration of all
possible generation scenarios of immune receptor sequences
Abstract:
In this work we propose a novel graph-based approach to data analysis of
immune receptor sequences. We propose algorithms for computing generation probabilities
of all possible generation scenarios for both nucleotide and amino acid sequences of
immune receptors, and an algorithm for statistical inference of probabilistic generation
models for immune receptors. To the best of our knowledge, proposed approach is the
first algorithm for computation of immune receptor amino acid sequence's generation
probability. Developed algorithms demonstrated dramatically higher speed in contrast
to algorithms in previous works. Additionally, we developed parallel versions of our
algorithms and tested them on the experimental data.
