Systems-Level Modelling of Microbial Communities : Theory and Practice

Ravikrishnan, Aarthi; Raman, Karthik

ISBN 10: 1032241799 / ISBN 13: 9781032241791

Editore: CRC Press, 2021

Riguardo questo articolo

Codice articolo 44022510-n

Dati bibliografici

• Titolo: Systems-Level Modelling of Microbial Communities : Theory and Practice
• Editore: CRC Press
• Data di pubblicazione: 2021
• Lingua: Inglese
• ISBN 10: 1032241799
• ISBN 13: 9781032241791
• Rilegatura: Brossura
• Condizione: New

Descrizione articolo

Riassunto

Systems-Level Modelling of Microbial Communities: Theory and Practice introduces various aspects of modelling microbial communities and presents a detailed overview of the computational methods which have been developed in this area. This book is aimed at researchers in the field of computational/systems biology as well as biologists/experimentalists studying microbial communities, who are keen on embracing the concepts of computational modelling. The primary focus of this book is on methods for modelling interactions between micro-organisms in a community, with special emphasis on constraint-based and network-based modelling techniques. A brief overview of population- and agent-based modelling is also presented. Lastly, it covers the experimental methods to understand microbial communities, and provides an outlook on how the field may evolve in the coming years.

Informazioni sull?autore

Aarthi Ravikrishnan is a senior graduate student at the Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras. She works on integrating computational and experimental approaches to understand microbial interactions in communities.

Karthik Raman is an Associate Professor at the Bhupat and Jyoti Mehta School of Biosciences, IIT Madras. He also coordinates the Initiative for Biological Systems Engineering and is a core member of the Robert Bosch Centre for Data Science and Artificial Intelligence at IIT Madras. His group works on computational approaches to understand and manipulate biological networks, with a focus on applications in metabolic engineering.