Discovering Motifs in Biological Sequences Using the Micron Automata Processor

TLDR: This paper proposes a novel algorithm for the (l; d) motif search problem using streaming execution over a large set of non-deterministic finite automata (NFA), designed to take advantage of the micron automata processor, a new technology close to deployment that can simultaneously execute multiple NFA in parallel.

Abstract: Finding approximately conserved sequences, called motifs , across multiple DNA or protein sequences is an important problem in computational biology. In this paper, we consider the $(l,d)$ motif search problem of identifying one or more motifs of length $l$ present in at least $q$ of the $n$ given sequences, with each occurrence differing from the motif in at most $d$ substitutions. The problem is known to be NP-complete, and the largest solved instance reported to date is $(26,11)$ . We propose a novel algorithm for the $(l,d)$ motif search problem using streaming execution over a large set of non-deterministic finite automata (NFA). This solution is designed to take advantage of the micron automata processor, a new technology close to deployment that can simultaneously execute multiple NFA in parallel. We demonstrate the capability for solving much larger instances of the $(l,d)$ motif search problem using the resources available within a single automata processor board, by estimating run-times for problem instances $(39,18)$ and $(40,17)$ . The paper serves as a useful guide to solving problems using this new accelerator technology.