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Traditional Chinese medicine and diseases : an omics big-data mining perspective / Kang Ning, editor.

Ning, Kang, editor.
2022
R602
Available Online
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Title
Traditional Chinese medicine and diseases : an omics big-data mining perspective / Kang Ning, editor.
ISBN
9789811947711 (electronic bk.)
9811947716 (electronic bk.)
9789811947704
9811947708
DOI
https://doi.org/10.1007/978-981-19-4771-1
Published
Singapore : Springer, [2022]
Copyright
©2022
Language
English
Description
1 online resource (ix, 139 pages) : illustrations.
Item Number
10.1007/978-981-19-4771-1 doi
Call Number
R602
Dewey Decimal Classification
610.951
Summary
This book focuses on the multi-omics big-data integration, the data-mining techniques and the cutting-edge omics researches in principles and applications for a deep understanding of Traditional Chinese Medicine (TCM) and diseases from the following aspects: (1) Basics about multi-omics data and analytical methods for TCM and diseases. (2) The needs of omics studies in TCM researches, and the basic background of omics research in TCM and disease. (3) Better understanding of the multi-omics big-data integration techniques. (4) Better understanding of the multi-omics big-data mining techniques, as well as with different applications, for most insights from these omics data for TCM and disease researches. (5) TCM preparation quality control for checking both prescribed and unexpected ingredients including biological and chemical ingredients. (6) TCM preparation source tracking. (7) TCM preparation network pharmacology analysis. (8) TCM analysis data resources, web services, and visualizations. (9) TCM geoherbalism examination and authentic TCM identification. Traditional Chinese Medicine has been in existence for several thousands of years, and only in recent tens of years have we realized that the researches on TCM could be profoundly boosted by the omics technologies. Devised as a book on TCM and disease researches in the omics age, this book has put the focus on data integration and data mining methods for multi-omics researches, which will be explained in detail and with supportive examples the "What", "Why" and "How" of omics on TCM related researches. It is an attempt to bridge the gap between TCM related multi-omics big data, and the data-mining techniques, for best practice of contemporary bioinformatics and in-depth insights on the TCM related questions.
Bibliography, etc. Note
Includes bibliographical references.
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Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed October 17, 2022).
Added Author
Ning, Kang, editor.
Series
Translational bioinformatics ; v. 18.
Available in Other Form
Print version: 9789811947704
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Online Access
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Intro
Preface
About the Book
Contents
Chapter 1: Introduction to Multi-Omics Data and Analytical Methods for TCM and Diseases
1.1 The Importance of TCM Researches
1.2 Multi-Omics Studies for TCM Researches
1.3 Representative Studies
1.4 Conclusions
References
Chapter 2: TCM and Diseases: The Needs for Multi-Omics
2.1 A Brief History and Facts about TCM and TCM Preparations
2.2 Multi-Omics Are Indispensable for TCM Researches and Applications
2.2.1 Multi-Omics Is Essential for TCM Materials Research
2.2.2 Multi-Omics Is Essential for TCM Treating

2.3 Representative Studies on TCM and Diseases
2.4 Current Limitations
2.5 Conclusions
References
Chapter 3: TCM Related Multi-Omics Data Integration Techniques
3.1 Genomics for TCM Researches
3.2 Transcriptomics for TCM Researches
3.3 Proteomics for TCM and Diseases Researches
3.4 Metabolomics for TCM Researches
3.5 Microbiomics for TCM Researches
3.6 Multi-Omics for TCM and Disease Researches
3.7 Representative Studies
3.7.1 Multi-Omics Strategies Used for Myocardial Infarction(MI) Research

3.7.2 Multi-Omics Strategies Used for Urinary Tract Infection (UTI) Research
3.7.3 Multi-Omics Strategies Used for High-Fat Diet Research
3.7.4 Chemoproteomics Strategies Used for Diet-Induced Obesity and Hepatic Steatosis Research
3.8 Conclusions
References
Chapter 4: TCM Related Multi-Omics Data Mining Techniques
4.1 Multi-Omics Data Types for TCM Researches
4.2 Data Mining Techniques for TCM Research
4.2.1 Mining TCM Preparation Omics Data for Ingredient Identifications
4.2.2 Mining TCM Network Pharmacological Data for Possible Disease Treatment

4.2.3 Mining TCM and Human Microbiome for their Complex Interplay and Effects on Human Health
4.3 Representative Studies
4.3.1 Deciphering the Therapeutic Mechanisms of Xiao-Ke-an in Treatment of Type 2 Diabetes by a Multi-Omics Approach
4.4 Conclusions
References
Chapter 5: TCM Preparation Quality Control: Biological and Chemical Ingredient Analysis
5.1 Chemical Ingredient Analysis
5.2 Biological Ingredient Analysis
5.3 Integrating Analysis of the Chemical Ingredients and Biological Ingredients for Quality Assessment of TCM Preparations

5.4 Resources for Quality Evaluation of TCM Preparations
5.5 Conclusions
References
Chapter 6: TCM Preparation Source Tracking
6.1 TCM Preparation Source Tracking: Importance and Current Status
6.2 Methods for Quality Control of TCM Preparations
6.3 Biological Ingredient Complement Chemical Ingredient in the Assessment of the Quality of TCM Preparations
6.4 A Quality Control Framework of TCM Preparations
6.5 Conclusions
References
Chapter 7: TCM Preparation Network Pharmacology Analysis
7.1 TCM in Modernization Period

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