NDLI: A generic finite automata based approach to implementing lymphocyte repertoire models

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A generic finite automata based approach to implementing lymphocyte repertoire models

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A generic finite automata based approach to implementing lymphocyte repertoire models

Content Provider	ACM Digital Library
Author	Liśkiewicz, Macie Dannenberg, Katharina Textor, Johannes
Abstract	Artificial immune systems (AIS) inspired by lymphocyte repertoires include negative and positive selection, clonal selection, and B~cell algorithms. Such AISs are used in computer science for machine learning and optimization, and in biology for modeling of fundamental immunological processes. In both cases, the necessary size of repertoire models can be huge. Here, we show that when lymphocyte repertoire models based on string patterns can be compactly represented as finite automata (FA), this allows to efficiently perform negative selection, positive selection, insertion into, deletion from, uniform sampling from, and counting the repertoire. Specifically, for r-contiguous pattern matching, all these tasks can be performed in polynomial time. But even in NP-hard cases like Hamming distance matching, the FA representation can still lead to practically important efficiency gains. We demonstrate the feasibility and flexibility of this approach by implementing T~cell positive selection simulations based on human genomic data using four different pattern rules. Hence, FA-based repertoire models generalize previous efficient negative selection algorithms to perform several related algorithmic tasks, are easy to implement and customize, and are applicable to real-world bioinformatic problems.
Starting Page	129
Ending Page	136
Page Count	8
File Format	PDF
ISBN	9781450326629
DOI	10.1145/2576768.2598331
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-07-12
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Immunology Artificial immune systems Negative selection
Content Type	Text
Resource Type	Article

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