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Synopsis
This volume details the development of updated dry lab and wet lab based methods for the reconstruction of Gene regulatory networks (GRN). Chapters guide readers through culprit genes, in-silico drug discovery techniques, genome-wide ChIP-X data, high-Throughput Transcriptomic Data Exome Sequencing, Next-Generation Sequencing, Fuorescence Spectroscopy, data analysis in Bioinformatics, Computational Biology, and S-system based modeling of GRN. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and key tips on troubleshooting and avoiding known pitfalls.
Authoritative and cutting-edge, Reverse Engineering of Regulatory Networks aims to be a useful and practical guide to new researchers and experts looking to expand their knowledge.
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From the Back Cover
This volume details the development of updated dry lab and wet lab based methods for the reconstruction of Gene regulatory networks (GRN). Chapters guide readers through culprit genes, in-silico drug discovery techniques, genome-wide ChIP-X data, high-Throughput Transcriptomic Data Exome Sequencing, Next-Generation Sequencing, Fuorescence Spectroscopy, data analysis in Bioinformatics, Computational Biology, and S-system based modeling of GRN. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and key tips on troubleshooting and avoiding known pitfalls.
Authoritative and cutting-edge, Reverse Engineering of Regulatory Networks aims to be a useful and practical guide to new researchers and experts looking to expand their knowledge.
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Reverse Engineering of Regulatory Networks (eng)
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Reverse Engineering of Regulatory Networks : Methods and Protocols
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Reverse Engineering of Regulatory Networks : Methods and Protocols
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Reverse Engineering of Regulatory Networks (Methods in Molecular Biology, 2719)
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Reverse Engineering of Regulatory Networks
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Springer US, Springer US Okt 2023, 2023
ISBN 10: 1071634607
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This volume details the development of updated dry lab and wet lab based methods for the reconstruction of Gene regulatory networks (GRN). Chapters guide readers through culprit genes, in-silico drug discovery techniques, genome-wide ChIP-X data, high-Throughput Transcriptomic Data Exome Sequencing, Next-Generation Sequencing, Fuorescence Spectroscopy, data analysis in Bioinformatics, Computational Biology, and S-system based modeling of GRN. Written in the highly successfulMethods in Molecular Biologyseries format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and key tips on troubleshooting and avoiding known pitfalls.Authoritative and cutting-edge,Reverse Engineering of Regulatory Networks aims to be auseful and practical guide to new researchers and experts looking to expand their knowledge. 340 pp. Englisch. Seller Inventory # 9781071634608
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Reverse Engineering of Regulatory Networks
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Springer, Berlin|Springer US|Humana, 2023
ISBN 10: 1071634607
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Condition: New. This volume details the development of updated dry lab and wet lab based methods for the reconstruction of Gene regulatory networks (GRN). Chapters guide readers through culprit genes, in-silico drug discovery techniques, genome-wide ChIP-X data, . Seller Inventory # 895960519
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Reverse Engineering of Regulatory Networks
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Buch. Condition: Neu. Reverse Engineering of Regulatory Networks | Sudip Mandal | Buch | Methods in Molecular Biology | x | Englisch | 2023 | Humana | EAN 9781071634608 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Seller Inventory # 127201508
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