Protein Sequence Pattern Matching: Leveraging Application Specific Hardware Accelerators

2014 ◽  
Vol 63 (2) ◽  
pp. 448-460
Author(s):  
Sagi Manole ◽  
Amit Golander ◽  
Shlomo Weiss
Keyword(s):  
Pattern Matching ◽  
Protein Sequence ◽  
Hardware Accelerators ◽  
Sequence Pattern ◽  
Application Specific

PAMA: A FAST STRING MATCHING ALGORITHM

2006 ◽  
Vol 17 (02) ◽  
pp. 357-378
Author(s):  
SHIYONG LU ◽  
FENG CAO ◽  
YI LU
Keyword(s):  
Sequence Analysis ◽  
Pattern Matching ◽  
Protein Sequence ◽  
Text Processing ◽  
String Matching ◽  
Fundamental Operation ◽  
Protein Sequence Analysis ◽  
Matching Algorithm ◽  
Matching Process ◽  
Almost All

String matching is a fundamental operation in computer science, and its performance has great impact on many applications including database query, text processing, DNA and protein sequence analysis. In this paper, we propose a fast string matching algorithm, PAMA (PAttern MAtching). The shift rule used by PAMA not only subsumes both the bad character rule and the good suffix rule employed by the well-known Boyer-Moore algorithm, but also employs an additional key observation to enable faster shifting during the string matching process. Theoretically, we prove that from the same alignment, the next shift of PAMA will be at least as much as that of the Boyer-Moore algorithm. Experimentally, we show that PAMA indeed significantly outperforms the original Boyer-Moore algorithm in almost all cases, and outperforms other Boyer-Moore variants such as Tuned-BM, Turbo-BM and Horspool for long patterns (length ≥ 128) or for small alphabets (size < 8).

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