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230515 ||| eng |
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|a 9781800644113
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|a OBP.0291
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|a 9781800644106
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| 100 |
1 |
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|a Sauter, Thomas
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| 245 |
0 |
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|a Introduction to Systems Biology
|h Elektronische Ressource
|b Workbook for Flipped-classroom Teaching
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| 260 |
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|a Cambridge
|b Open Book Publishers
|c 2023
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| 300 |
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|a 1 electronic resource (170 p.)
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| 653 |
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|a thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general::GPS Research methods: general
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| 653 |
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|a thema EDItEUR::U Computing and Information Technology::UN Databases::UNC Data capture and analysis
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| 653 |
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|a systems biology;introduction;interdisciplinary framework;mathematical concepts;biological entities;physics concepts
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| 653 |
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|a thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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| 653 |
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|a thema EDItEUR::P Mathematics and Science::PS Biology, life sciences
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| 653 |
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|a thema EDItEUR::K Economics, Finance, Business and Management::KJ Business and Management::KJM Management and management techniques::KJMV Management of specific areas::KJMV6 Research and development management
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| 653 |
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|a thema EDItEUR::U Computing and Information Technology::UN Databases::UNF Data mining
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| 653 |
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|a thema EDItEUR::M Medicine and Nursing::MB Medicine: general issues::MBF Medical and health informatics
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| 700 |
1 |
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|a Albrecht, Marco
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b DOAB
|a Directory of Open Access Books
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| 500 |
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|a Creative Commons (cc), https://creativecommons.org/licenses/by-nc/4.0/
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| 024 |
8 |
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|a 10.11647/OBP.0291
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| 856 |
4 |
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|u https://library.oapen.org/bitstream/20.500.12657/61678/1/9781800644120.pdf
|7 0
|x Verlag
|3 Volltext
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| 856 |
4 |
2 |
|u https://directory.doabooks.org/handle/20.500.12854/98240
|z DOAB: description of the publication
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|a 333
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|a 500
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|a 530
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|a 610
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|a 600
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|a 330
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|a This book is an introduction to the language of systems biology, which is spoken among many disciplines, from biology to engineering. Authors Thomas Sauter and Marco Albrecht draw on a multidisciplinary background and evidence-based learning to facilitate the understanding of biochemical networks, metabolic modeling and system dynamics. Their pedagogic approach briefly highlights core ideas of concepts in a broader interdisciplinary framework to guide a more effective deep dive thereafter. The learning journey starts with the purity of mathematical concepts, reveals its power to connect biological entities in structure and time, and finally introduces physics concepts to tightly align abstraction with reality. This workbook is all about self-paced learning, supports the flipped-classroom concept, and kick-starts with scientific evidence on studying. Each chapter comes with links to external YouTube videos, learning checklists, and Integrated real-world examples to gain confidence in thinking across scientific perspectives. The result is an integrated approach that opens a line of communication between theory and application, enabling readers to actively learn as they read. This overview of capturing and analyzing the behavior of biological systems will interest adherers of systems biology and network analysis, as well as related fields such as bioinformatics, biology, cybernetics, and data science.
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