Data Mining and Knowledge Discovery Tools for Human Microbiome Big Data

被引:0
|
作者
Geman, Oana [1 ]
Chiuchisan, Iuliana [2 ]
Covasa, Mihai [1 ,3 ,4 ]
机构
[1] Stefan Cel Mare Univ Suceava, Dept Hlth & Human Dev, Suceava, Romania
[2] Stefan Cel Mare Univ Suceava, Comp Elect & Automat Dept, Suceava, Romania
[3] Stefan Cel Mare Univ Suceava, Dept Basic Med Sci, Suceava, Romania
[4] Western Univ Hlth Sci, Pomona, CA USA
关键词
Data Mining; Knowledge Discovery Date; Classification and Clustering; Big Data; Human Microbiome; GUT MICROBIOTA; INTESTINAL MICROBIOTA; OBESITY;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The human microbiome is a fundamental component of human physiology, with an estimated one-third of circulating metabolites being a product of the gut microbiota. Changes in the microbiome can trigger changes in human cellular activities, resulting in disease or contribute to its progression. Microbiota is considered to be a virtual "code" or a system emerging, with the properties that must be integrated into the biology and physiology of the human. Unlike the other components, the functions of this "code" are not yet fully understood but can be quite easily disturbed by diet, diseases, and the various treatments. Recently, it becomes more and more clear that these functions can be beneficial both and with the negative impact on the health status of the human host. The recognition of the role of soil microflora in the intestinal diseases and neurological or in metabolic diseases of systemic triggered an avalanche of studies which also were aimed at the elucidation of the human microbiome (Human Microbiome Project), but also a complicated interaction between the bi-directional relationship between the human and the intestinal bacteria. An important step represents the discovery of potential methods of use of human microbiota in prevention and treatment of diseases such as autism, asthma, Parkinson disease, obesity, and diabetes. There is an impressive collection of data (Human Microbiome Big Date) which can be analyzed and classified using the algorithms of Data Mining or Knowledge Discovery Date Tools.
引用
收藏
页码:91 / 96
页数:6
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