Unified Formal Construction and Isabelle Verification of the Dynamic Programming Algorithms for Biological Sequence Alignment

被引:0
|
作者
Shi, Haihe [1 ]
Lan, Sunwen [1 ]
Liu, Riming [1 ]
Shi, Haipeng [2 ]
Wang, Lan [1 ]
Zhong, Linhui [1 ]
机构
[1] School of Computer Information Engineering, Jiangxi Normal University, Nanchang,330022, China
[2] School of Software, Jiangxi Normal University, Nanchang,330022, China
基金
中国国家自然科学基金;
关键词
Application programs - Bioinformatics - Formal specification - Formal verification;
D O I
10.7544/issn1000-1239.202330698
中图分类号
学科分类号
摘要
Sequence alignment is a classical problem in biological sequence analysis, aiming to find out the similarity between sequences, which is of great significance for discovering functional, structural and evolutionary information in biological sequences. The problem can be divided into two categories: pairwise sequence alignment and multiple sequence alignment. The existing work is focused on specific algorithms, and no general solution is designed. In addition, there are few researches on the trustworthy of algorithms. By deeply analyzing the properties of sequence alignment problem and describing the essential characteristics of problem solving, a unified construction framework of sequence alignment dynamic programming algorithm seqAlign is designed based on the problem formal specification and formal method PAR. The process of constructing a multiple sequence alignment algorithm with three sequences by using the framework is further demonstrated, and the constructed results are formally verified by Isabelle theorem prover. Finally, the C++ executable program of the algorithm is generated by the code generation system of PAR platform. The process of mechanized construction of other sequence alignment algorithms using seqAlign framework is analyzed. Through strict specification refinement and formal verification, the reliability of the generated algorithm is effectively guaranteed. The developed seqAlign framework provides a general solution for the class of sequence alignment problems, which significantly improves the efficiency of generating sequence alignment algorithm families. The successful application of the designed seqAlign framework to sequence alignment problem in biological sequence analysis can provide a reference for the construction of highly reliable algorithms in complex bioinformatics field from the perspective of methodology and practice. © 2025 Science Press. All rights reserved.
引用
收藏
页码:119 / 131
相关论文
共 50 条
  • [31] An effective extension of the applicability of alignment-free biological sequence comparison algorithms with Hadoop
    Cattaneo, Giuseppe
    Petrillo, Umberto Ferraro
    Giancarlo, Raffaele
    Roscigno, Gianluca
    JOURNAL OF SUPERCOMPUTING, 2017, 73 (04): : 1467 - 1483
  • [32] An effective extension of the applicability of alignment-free biological sequence comparison algorithms with Hadoop
    Giuseppe Cattaneo
    Umberto Ferraro Petrillo
    Raffaele Giancarlo
    Gianluca Roscigno
    The Journal of Supercomputing, 2017, 73 : 1467 - 1483
  • [33] Performance evaluation of Warshall algorithm and dynamic programming for Markov chain in local sequence alignment
    Mohammad Ibrahim Khan
    Md. Sarwar kamal
    Interdisciplinary Sciences: Computational Life Sciences, 2015, 7 : 78 - 81
  • [34] Performance Evaluation of Warshall Algorithm and Dynamic Programming for Markov Chain in Local Sequence Alignment
    Khan, Mohammad Ibrahim
    Kamal, Md Sarwar
    INTERDISCIPLINARY SCIENCES-COMPUTATIONAL LIFE SCIENCES, 2015, 7 (01) : 78 - 81
  • [35] Toward efficient multiple molecular sequence alignment: A system of genetic algorithm and dynamic programming
    Zhang, C
    Wong, AKC
    IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 1997, 27 (06): : 918 - 932
  • [36] Using the PGAS Programming Paradigm for Biological Sequence Alignment on a Chip Multi-Threading Architecture
    Bakhouya, M.
    Bahra, S. A.
    El-Ghazawi, T.
    PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, VOL 28, 2008, 28 : 137 - 141
  • [37] A novel expert system for the prediction of accurate multiple sequence alignment and phylogenetic tree construction algorithms
    Randriamahenintsoa, Fanaja Harianja
    Raboanary, Toky Hajatiana
    Raboanary, Heriniaina Andry
    Raboanary, Julien Amedee
    2017 IEEE AFRICON, 2017, : 94 - 99
  • [38] A new method based on genetic-dynamic programming technique for multiple DNA sequence alignment
    Hernández-Hernández, José Crispín
    Bonilla-Huerta, Edmundo
    Morales-Caporal, Roberto
    Lecture Notes in Electrical Engineering, 2011, 98 : 567 - 574
  • [39] A memory-efficient dynamic programming algorithm for optimal alignment of a sequence to an RNA secondary structure
    Sean R Eddy
    BMC Bioinformatics, 3
  • [40] A memory-efficient dynamic programming algorithm for optimal alignment of a sequence to an RNA secondary structure
    Eddy, SR
    BMC BIOINFORMATICS, 2002, 3 (1)