| Chapter title |
Metagenomics and Single-Cell Omics Data Analysis for Human Microbiome Research.
|
|---|---|
| Chapter number | 6 |
| Book title |
Translational Biomedical Informatics
|
| Published in |
Advances in experimental medicine and biology, November 2016
|
| DOI | 10.1007/978-981-10-1503-8_6 |
| Pubmed ID | |
| Book ISBNs |
978-9-81-101502-1, 978-9-81-101503-8
|
| Authors |
Maozhen Han, Pengshuo Yang, Hao Zhou, Hongjun Li, Kang Ning |
| Editors |
Bairong Shen, Haixu Tang, Xiaoqian Jiang |
| Abstract |
Microbes are ubiquitous on our planet, and it is well known that the total number of microbial cells on earth is huge. These organisms usually live in communities, and each of these communities has a different taxonomical structure. As such, microbial communities would serve as the largest reservoir of genes and genetic functions for a vast number of applications in "bio"-related disciplines, especially in biomedicine. Human microbiome is the area in which the relationships between ourselves as hosts and our microbiomes have been examined.In this chapter, we have first reviewed the researches in microbes on community, population and single-cell levels in general. Then we have focused on the effects of recent metagenomics and single-cell advances on human microbiome research, as well as their effects on translational biomedical research. We have also foreseen that with the advancement of big-data analysis techniques, deeper understanding of human microbiome, as well as its broader applications, could be realized. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Austria | 1 | 17% |
| India | 1 | 17% |
| Unknown | 4 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 100% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 2 | 8% |
| Unknown | 22 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 4 | 17% |
| Student > Postgraduate | 3 | 13% |
| Researcher | 3 | 13% |
| Student > Bachelor | 2 | 8% |
| Professor | 2 | 8% |
| Other | 4 | 17% |
| Unknown | 6 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 7 | 29% |
| Medicine and Dentistry | 4 | 17% |
| Agricultural and Biological Sciences | 3 | 13% |
| Computer Science | 2 | 8% |
| Immunology and Microbiology | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 6 | 25% |