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Springer Synthetic Biology and iGEM - Omics Big-Data Mining

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Description

Explore the intersection of biological engineering and data science with this comprehensive text from Springer. This book examines synthetic biology through the lens of multi-omics big-data integration and advanced data-mining techniques. While rooted in established fields like systems biology, metabolite engineering, and biological engineering, the content addresses modern research in synthetic biology principles and applications. Readers will gain insights into the systematic design and rational engineering processes that define this new research area. The text provides a detailed look at iGEM, focusing on the sustainability of design and cutting-edge research developments. It is an essential resource for understanding how big-data mining perspectives can be applied to solve complex biological engineering challenges.

Key Features

This Springer publication focuses on biological engineering techniques and multi-omics big-data integration.

The text covers advanced data-mining techniques applied to synthetic biology research.

Learn about the systematic design and rational engineering processes used in modern biological applications.

The book explores the connection between synthetic biology and established fields like systems biology and metabolite engineering.

Detailed discussions include iGEM research and the sustainability of design in the field.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
21 June 2024
Listed Since
22 June 2024

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