Biological Network Analysis Trends, Approaches, Graph Theory, and Algorithms
Auteurs : Guzzi Pietro Hiram, Roy Swarup
Biological Network Analysis: Trends, Approaches, Graph Theory, and Algorithms considers three major biological networks, including Gene Regulatory Networks (GRN), Protein-Protein Interaction Networks (PPIN), and Human Brain Connectomes. The book's authors discuss various graph theoretic and data analytics approaches used to analyze these networks with respect to available tools, technologies, standards, algorithms and databases for generating, representing and analyzing graphical data. As a wide variety of algorithms have been developed to analyze and compare networks, this book is a timely resource.
1. Introduction2. Preliminaries of Graph Theory3. Graph Analysis4. Complex Network Models5. Graph Databases in Bioinformatics and Computational Biology6. Gene Regulatory Networks-Inference and Analysis7. Protein Protein Interaction Networks8. Brain Connectomes and Analysis9. Conclusion
Students and researchers in biomedical engineering and computational biology who are interested in biological network analysis for biological modelling
Swarup Roy is a Professor in Computer Science at Sikkim (Central) University, Gangtok. He received his M.Tech. and PhD (Comp. Sc. & Engg.) from Tezpur (Central) University. He worked as a Post-Doctoral Fellow (PDF) at University of Colorado at Colorado Springs, USA and Indian Institute of Technology (IIT), Guwahati. His research interest includes Machine Learning, Data Science, Network
Science, Intrusion Detection and Computational Biology. He has published 80+ research articles in high impact international journals and leading world conferences across the globe in machine
learning and bioinformatics. He authored the book “Biological Network Analysis- Trends, Approaches, Graphical Theory and Algorithms published by Elsevier, USA . He was a recipient of Best Doctoral Thesis Award from IIT-Roorkee and University Gold Medal. He was selected for Overseas Research Associate Fellowship from DBT, Govt. of India in 2015 to conduct research in the foreign laboratories and funding from DST-SERB to visit SPAIN in 2012 to present his research paper. He taught undergraduate and graduate students of computer science at University of Colorado, USA as visiting professor. H
- Presents recent advances in biological network analysis, combining Graph Theory, Graph Analysis, and various network models
- Discusses three major biological networks, including Gene Regulatory Networks (GRN), Protein-Protein Interaction Networks (PPIN) and Human Brain Connectomes
- Includes a discussion of various graph theoretic and data analytics approaches
Date de parution : 05-2020
Ouvrage de 210 p.
19x23.4 cm
Thèmes de Biological Network Analysis :
Mots-clés :
Adjacency matrix; Average path length; Brain; Brain graph; Centrality analysis; Clustering; Clustering coefficient; Coexpression network; Community discovery; Complete graph; Complex detection; Connectomes; Degree; Directed and undirected graphs; Functional connectivity; Graph data; Graph databases; Graph querying; Graph theory; Graph traversal; Interactomes; Languages for data modeling; Micro-array; Modularity; MRI; Network alignments; Network analysis; Network modules; Network visualization; No-SQL databases; Parcelation; Path; Prediction; Proteins; Regular graph; Regulatory network; Rich-club coefficient; RNA-seq; Scale-free network; Small-world network