| Chapter title |
Data Analysis for Gut Microbiota and Health
|
|---|---|
| Chapter number | 5 |
| Book title |
Healthcare and Big Data Management
|
| Published in |
Advances in experimental medicine and biology, January 2017
|
| DOI | 10.1007/978-981-10-6041-0_5 |
| Pubmed ID | |
| Book ISBNs |
978-9-81-106040-3, 978-9-81-106041-0
|
| Authors |
Xingpeng Jiang, Xiaohua Hu |
| Abstract |
In recent years, data mining and analysis of high-throughput sequencing of microbiomes and metagenomic data enable researchers to discover biological knowledge by characterizing the composition and variation of species across environmental samples and to accumulate a huge amount of data, making it feasible to infer the complex principle of species interactions. The interactions of microbes in a microbial community play an important role in microbial ecological system. Data mining provides diverse approachs to identify the correlations between disease and microbes and how microbial species coexist and interact in a host-associated or natural environment. This is not only important to advance basic microbiology science and other related fields but also important to understand the impacts of microbial communities on human health and diseases. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 5 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 100% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 12 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 50% |
| Other | 1 | 8% |
| Student > Postgraduate | 1 | 8% |
| Unknown | 4 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Immunology and Microbiology | 4 | 33% |
| Business, Management and Accounting | 1 | 8% |
| Neuroscience | 1 | 8% |
| Medicine and Dentistry | 1 | 8% |
| Unknown | 5 | 42% |