Biological Network Analysis: Trends, Approaches, Graphical Theory and Algorithms

Pietro Hiram Guzzi|Swarup Roy

ISBN 10: 0128193506 / ISBN 13: 9780128193501

Published by Elsevier Science, 2020

About this Item

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 Ne.

Seller Inventory # 335137462

Bibliographic Details

• Title: Biological Network Analysis: Trends, Approaches, Graphical Theory and Algorithms
• Publisher: Elsevier Science
• Publication Date: 2020
• Language: English
• ISBN 10: 0128193506
• ISBN 13: 9780128193501
• Binding: Soft cover
• Condition: New

About this title

Synopsis

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.

• 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

About the Authors

Pietro Hiram Guzzi the Ph.D. degree in biomedical engi- neering from Magna Græcia University, Italy, in 2008. He has been an Associate Professor of computer engineering with Magna Græcia Univer- sity since 2008. He has been a Visiting Researcher with Georgia Tech University, Atlanta. He has authored two books. His research interests include semantic-based and network-based analysis of biological and clinical data. He is a member of the ACM, BITS, ISMB, and NETBIO COSI. He is an Editor of a newsletter of the ACM Special Interest Group on Bioinformatics, Computational Biology, and Biomedical Informatics (SIGBio), and the IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS. He serves the scientific community as a reviewer for many conferenceS. He wrote two books and he edited another one.

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. He has been listed as a data science subject expert by the Department of Science & Technology-Govt of India. He acted as Track Co-Chair for Biological Modelling at 8th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB) 2017, Boston, USA. He is acting as Guest Editor of International Journals such as MDPI Data, MDPI Life, Frontier in Bioinformatics and in the technical committee of many reputed International Journals.