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Traditional Chinese Medicine and Diseases

Traditional Chinese Medicine and Diseases


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About the Book

Chapter 1. Introduction to multi-omics data and analytical methods for TCM and diseases.- Chapter 2. TCM and diseases: the needs for multi-omics.- Chapter 3. TCM related multi-omics data integration techniques.- Chapter 4. TCM related multi-omics data mining techniques.- Chapter 5. TCM preparation quality control: biological and chemical ingredient analysis.- Chapter 6. TCM preparation source tracking.- Chapter 7. TCM preparation network pharmacology analysis.- Chapter 8. TCM analysis data resources, web services and visualizations.- Chapter 9. TCM geoherbalism examination and authentic TCM identification.
About the Author: Dr. Kang Ning, Professor and Director of Department of Bioinformatics and Systems Biology, School of Life Science and Technology, Huazhong University of Science and Technology. Dr. Ning obtained his BS in Computer Science from University of Science and Technology of China, and PhD in Bioinformatics from National University of Singapore. He obtained his Post-Doc training in Bioinformatics at University of Michigan, Ann Arbor. He has been devoting to bioinformatics research for more than 20 years focusing on omics big-data integration, microbiome analyses, and single-cell analyses. His current research interests include AI methods for multi-omics especially metagenomics data mining and their applications. He is also interested in synthetic biology and TCM omics. Dr. Ning as the leading or corresponding author, published over 100 research articles and reviews on leading journals including PNAS, Gut, Genome Biology, Genome Medicine, Nucleic Acids Research and Bioinformatics, with more than 4,000 citations in total. He is the committee member of several national bioinformatics and biology big-data committees in China. He serves as an editorial board member of the journals including Genomics Proteomics and Bioinformatics, Microbiology Spectrum and Scientific Reports, and served as reviewers for several international funding agencies including UK-BBSRC and UK-NERC.


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Product Details
  • ISBN-13: 9789811947704
  • Publisher: Springer Nature Singapore
  • Binding: Hardback
  • Language: English
  • Returnable: Y
  • Sub Title: An Omics Big-Data Mining Perspective
  • Width: 156 mm
  • ISBN-10: 9811947708
  • Publisher Date: 04 Oct 2022
  • Height: 234 mm
  • No of Pages: 139
  • Spine Width: 10 mm
  • Weight: 440 gr


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