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KIAM Preprint  108, Moscow, 2017
Authors: Nazarov V.I., Klyshinsky E.S.
Graph-based data structure for enumeration of all possible generation scenarios of immune receptor sequences
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.
statistical immunoinformatics, adaptive immunity, T-cell receptors, immunoglobulins, V(D)J recombination
Publication language: russian,  pages: 30
Research direction:
Mathematical modelling in actual problems of science and technics
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About authors:
  • Nazarov Vadim Igorevich,
  • Klyshinsky Eduard Stanislavovich, RAS