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

Autor: Haipeng Shi, Huan Chen, Qinghong Yang, Jun Wang, Haihe Shi
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Big Data Mining and Analytics, Vol 6, Iss 1, Pp 11-20 (2023)
Druh dokumentu: article
ISSN: 2096-0654
DOI: 10.26599/BDMA.2022.9020030
Popis: 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.
Databáze: Directory of Open Access Journals