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Computational Systems Biology - A Beginner's Guide

About Computational Systems Biology - A Beginner's Guide

Embark on a journey through the intricate world of Computational Systems Biology with this comprehensive guide. Delve into the fundamental concepts of network biology, exploring the interconnectedness of biological systems at a molecular level. From understanding the basics of network topology to unravelling complex biological phenomena, this book navigates through databases and tools essential for analysing biological networks. Through illuminating case studies, readers gain practical insights into real-world applications, witnessing how computational methods are revolutionizing our understanding of biological systems. Whether you're a seasoned researcher or a curious student, this book equips you with the knowledge and tools to unravel the mysteries of life through the lens of computational systems biology.

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  • Language:
  • English
  • ISBN:
  • 9789999315784
  • Binding:
  • Paperback
  • Pages:
  • 92
  • Published:
  • February 26, 2024
  • Dimensions:
  • 152x5x229 mm.
  • Weight:
  • 148 g.
Delivery: 1-2 weeks
Expected delivery: January 4, 2025
Extended return policy to January 30, 2025
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Description of Computational Systems Biology - A Beginner's Guide

Embark on a journey through the intricate world of Computational Systems Biology with this comprehensive guide. Delve into the fundamental concepts of network biology, exploring the interconnectedness of biological systems at a molecular level. From understanding the basics of network topology to unravelling complex biological phenomena, this book navigates through databases and tools essential for analysing biological networks. Through illuminating case studies, readers gain practical insights into real-world applications, witnessing how computational methods are revolutionizing our understanding of biological systems. Whether you're a seasoned researcher or a curious student, this book equips you with the knowledge and tools to unravel the mysteries of life through the lens of computational systems biology.

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