Backward Pattern Matching on Elastic-Degenerate Strings

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F23%3A00368321" target="_blank" >RIV/68407700:21240/23:00368321 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1007/s42979-023-01760-x" target="_blank" >https://doi.org/10.1007/s42979-023-01760-x</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s42979-023-01760-x" target="_blank" >10.1007/s42979-023-01760-x</a>

Result language

angličtina

Original language name

Backward Pattern Matching on Elastic-Degenerate Strings

Original language description

Recently, the concept of Elastic Degenerate Strings (EDS) was introduced as a way of representing a sequenced population of the same species. Several on-line Elastic Degenerate String Matching (EDSM) algorithms were presented so far. Some of them provide practical implementation. We propose a new on-line EDSM algorithm BNDM-EDS. Our algorithm combines two traditional algorithms BNDM and the Shift-And that were adapted to the specifics needed by Elastic Degenerate Strings. BNDM-EDS is running in O (Nmd w m e) worst-case time. This implies O (Nm) time for small patterns, where m is the length of the searched pattern, N is the size of EDS, and w is the size of the computer word. The algorithm uses O (N + n) space, where n is the length of EDS. BNDM-EDS requires a simple preprocessing step with time and space O(m). Experimental results on real genomic data show superiority of BNDM-EDS over state-of-the-art algorithms.

Czech name

—

Czech description

—

Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/GA19-20759S" target="_blank" >GA19-20759S: Efficient String Matching for Bioinformatics</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

SN Computer Science

ISSN

2662-995X

e-ISSN

—

Volume of the periodical

4

Issue of the periodical within the volume

5

Country of publishing house

SG - SINGAPORE

Number of pages

19

Pages from-to

—

UT code for WoS article

—

EID of the result in the Scopus database

2-s2.0-85161854588