Traditional Chinese Medicine and Diseases

An Omics Big-data Mining Perspective

Éditeur :

Springer

Paru le : 2022-10-03

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 ana...
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À propos

Auteur

Éditeur

Collection
n.c

Parution
2022-10-03

Pages
139 pages

EAN papier
9789811947704

Auteur(s) du livre


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 morethan 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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EAN PDF
9789811947711
Prix
94,94 €
Nombre pages copiables
1
Nombre pages imprimables
13
Taille du fichier
3471 Ko
EAN EPUB
9789811947711
Prix
94,94 €
Nombre pages copiables
1
Nombre pages imprimables
13
Taille du fichier
20849 Ko

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