Graph Theoretic Concepts in the Study of Biological Networks

被引:4
|
作者
Indhumathy, M. [1 ]
Arumugam, S. [1 ,2 ,3 ]
Baths, Veeky [4 ]
Singh, Tarkeshwar [5 ]
机构
[1] Kalasalingam Univ, Natl Ctr Adv Res Discrete Math, Krishnankoil 626126, Tamil Nadu, India
[2] Liverpool Hope Univ, Dept Comp Sci, Liverpool, Merseyside, England
[3] Ball State Univ, Dept Comp Sci, Muncie, IN 47306 USA
[4] Birla Inst Technol & Sci Pilani, Dept Biol Sci, KK Birla Goa Campus,NH-17B, Zuarinagar, Goa, India
[5] Birla Inst Technol & Sci Pilani, Dept Math, KK Birla Goa Campus,NH-17B, Zuarinagar, Goa, India
关键词
Biological networks; Centrality measures; Graph; Motifs; PROTEINS;
D O I
10.1007/978-81-322-3640-5_11
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
The theory of complex networks has a wide range of applications in a variety of disciplines such as communications and power system engineering, the internet and worldwide web (www), food webs, human social networks, molecular biology, population biology and biological networks. The focus of this paper is on biological applications of the theory of graphs and networks. Graph theory and several graph theoretic properties serve as an ideal mathematical tool in the analysis of complex networks. We present the basic concepts and notations from graph theory which is widely used in the study of biological networks. Various biological networks such as Protein interaction networks, Metabolome based reaction network, Gene regulatory network, Gene coexpression network, Protein structure network, Structural brain network, Phylogenetic networks, Ecological networks and Food web networks are described. We also deal with various centrality measures which provide deep insight in the study of biological networks. Applications of biological network analysis in several areas are also discussed.
引用
收藏
页码:187 / 200
页数:14
相关论文
共 50 条
  • [41] A Graph-Theoretic Approach to Distributed Control over Networks
    Swigart, John
    Lall, Sanjay
    PROCEEDINGS OF THE 48TH IEEE CONFERENCE ON DECISION AND CONTROL, 2009 HELD JOINTLY WITH THE 2009 28TH CHINESE CONTROL CONFERENCE (CDC/CCC 2009), 2009, : 5409 - 5414
  • [42] Graph Theoretic Foundations of Cyclic and Acyclic Linear Dynamic Networks
    Johnson, Charles A.
    Woodbury, Nathan
    Warnick, Sean
    IFAC PAPERSONLINE, 2020, 53 (02): : 26 - 33
  • [43] Identifiability of Undirected Dynamical Networks: A Graph-Theoretic Approach
    van Waarde, Henk J.
    Tesi, Pietro
    Camlibel, M. Kanat
    IEEE CONTROL SYSTEMS LETTERS, 2018, 2 (04): : 683 - 688
  • [44] GRAPH INFORMATION THEORETIC MEASURES ON FUNCTIONAL CONNECTIVITY NETWORKS BASED ON GRAPH-TO-SIGNAL TRANSFORM
    Villafane-Delgado, Marisel
    Aviyente, Selin
    2016 IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (GLOBALSIP), 2016, : 1137 - 1141
  • [45] Sub-optimal solutions to track detection problem using graph theoretic concepts
    Nikolopoulos, SD
    Samaras, G
    JOURNAL OF SYSTEMS ARCHITECTURE, 1997, 42 (9-10) : 743 - 760
  • [46] A graph-theoretic perspective on the links-to-concepts ratio expected in cognitive maps
    Georgiou, Ion
    EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2009, 197 (02) : 834 - 836
  • [47] New spectral graph theoretic conditions for synchronization in directed complex networks
    Liu, Hui
    Cao, Ming
    Wu, Chai Wah
    2013 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS), 2013, : 2307 - 2310
  • [48] Graph-theoretic characterizations of monotonicity of chemical networks in reaction coordinates
    David Angeli
    Patrick De Leenheer
    Eduardo Sontag
    Journal of Mathematical Biology, 2010, 61 : 581 - 616
  • [49] Graph-Theoretic Approach for Increasing Participation in Networks With Assorted Resources
    Abbas, Waseem
    Laszka, Aron
    Shabbir, Mudassir
    Koutsoukos, Xenofon
    IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING, 2020, 7 (03): : 930 - 946
  • [50] Graph-theoretic characterizations of monotonicity of chemical networks in reaction coordinates
    Angeli, David
    De Leenheer, Patrick
    Sontag, Eduardo
    JOURNAL OF MATHEMATICAL BIOLOGY, 2010, 61 (04) : 581 - 616