AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (4.4 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Open Access

A Method for Bio-Sequence Analysis Algorithm Development Based on the PAR Platform

School of Software, Jiangxi Normal University, Nanchang 330022, China
School of Computer and Information Engineering, Jiangxi Normal University, Nanchang 330022, China
Show Author Information

Abstract

The problems of biological sequence analysis have great theoretical and practical value in modern bioinformatics. Numerous solving algorithms are used for these problems, and complex similarities and differences exist among these algorithms for the same problem, causing difficulty for researchers to select the appropriate one. To address this situation, combined with the formal partition-and-recur method, component technology, domain engineering, and generic programming, the paper presents a method for the development of a family of biological sequence analysis algorithms. It designs highly trustworthy reusable domain algorithm components and further assembles them to generate specifific biological sequence analysis algorithms. The experiment of the development of a dynamic programming based LCS algorithm family shows the proposed method enables the improvement of the reliability, understandability, and development efficiency of particular algorithms.

References

【1】
【1】
 
 
Big Data Mining and Analytics
Pages 11-20

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
Shi H, Chen H, Yang Q, et al. A Method for Bio-Sequence Analysis Algorithm Development Based on the PAR Platform. Big Data Mining and Analytics, 2023, 6(1): 11-20. https://doi.org/10.26599/BDMA.2022.9020030

1543

Views

119

Downloads

5

Crossref

2

Web of Science

5

Scopus

1

CSCD

Received: 28 June 2022
Revised: 12 August 2022
Accepted: 17 August 2022
Published: 24 November 2022
© The author(s) 2023.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).