A Graph-Based Approach for the DNA Word Design Problem

被引:3
|
作者
Luncasu, Victor [1 ]
Raschip, Madalina [1 ]
机构
[1] Alexandru Ioan Cuza Univ, Fac Comp Sci, Iasi 700483, Romania
关键词
DNA; Hamming distance; Computational modeling; Evolutionary computation; Genetic communication; DNA computing; DNA word design; maximum independent set; ALGORITHMS; SETS;
D O I
10.1109/TCBB.2020.3008346
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
The aim of this paper is to improve the best known solution of an important problem, the DNA Word Design problem, which has its roots in Bioinformatics and Coding Theory. The problem is to design DNA codes that satisfy some combinatorial constraints. The constraints considered are: minimum Hamming distance, fixed GC content and the reverse complement Hamming distance. The problem is modeled as a maximum independent set problem. Existing complex approaches for the maximum independent set problem, suitable for large graphs, were tested. In order to tackle large instances, libraries for external memory computations and sampling techniques were investigated. Eventually, we succeed in finding good lower bounds for the instances that were analyzed.
引用
收藏
页码:2747 / 2752
页数:6
相关论文
共 50 条
  • [41] Hypergraph-based image retrieval for graph-based representation
    Jouili, Salim
    Tabbone, Salvatore
    PATTERN RECOGNITION, 2012, 45 (11) : 4054 - 4068
  • [42] Graph-based Automated Macro-Molecule Assembly
    Spenke, Florian
    Hartke, Bernd
    JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2022, 62 (16) : 3714 - 3723
  • [43] An Balanced, and Scalable Graph-Based Multiview Clustering Method
    Zhao, Zihua
    Nie, Feiping
    Wang, Rong
    Wang, Zheng
    Li, Xuelong
    IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2024, 36 (12) : 7643 - 7656
  • [44] Fast and Accurate Anchor Graph-based Label Prediction
    Fujiwara, Yasuhiro
    Ida, Yasutoshi
    Kumagai, Atsutoshi
    Kanai, Sekitoshi
    Ueda, Naonori
    PROCEEDINGS OF THE 30TH ACM INTERNATIONAL CONFERENCE ON INFORMATION & KNOWLEDGE MANAGEMENT, CIKM 2021, 2021, : 504 - 513
  • [45] Dynamic Graph-Based Anomaly Detection in the Electrical Grid
    Li, Shimiao
    Pandey, Amritanshu
    Hooi, Bryan
    Faloutsos, Christos
    Pileggi, Larry
    IEEE TRANSACTIONS ON POWER SYSTEMS, 2022, 37 (05) : 3408 - 3422
  • [46] Oceanscape: A graph-based framework for autonomous coastal navigation
    Fagerhaug, Eirik S.
    Bye, Robin T.
    Osen, Ottar L.
    Hatledal, Lars Ivar
    OCEAN ENGINEERING, 2025, 320
  • [47] Accurate Complementarity Learning for Graph-Based Multiview Clustering
    Xiao, Xiaolin
    Gong, Yue-Jiao
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2024, 35 (11) : 16106 - 16118
  • [48] Towards a Provably Resilient Scheme for Graph-Based Watermarking
    Souza Bento, Lucila Maria
    Boccardo, Davidson
    Santos Machado, Raphael Carlos
    Pereira de Sa, Vinicius Gusmao
    Szwarcfiter, Jayme Luiz
    GRAPH-THEORETIC CONCEPTS IN COMPUTER SCIENCE, WG 2013, 2013, 8165 : 50 - 63
  • [49] Graph-Based Label Propagation in Digital Media: A Review
    Zoidi, Olga
    Fotiadou, Eftychia
    Nikolaidis, Nikos
    Pitas, Ioannis
    ACM COMPUTING SURVEYS, 2015, 47 (03)
  • [50] GMC: Graph-Based Multi-View Clustering
    Wang, Hao
    Yang, Yan
    Liu, Bing
    IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2020, 32 (06) : 1116 - 1129