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Metagenomics and Single-Cell Omics Data Analysis for Human Microbiome Research

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Translational Biomedical Informatics

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 939))

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.

*These authors equally contributed to this chapter.

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  1. Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China

    Maozhen Han, Pengshuo Yang, Hao Zhou, Hongjun Li & Kang Ning

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  1. Maozhen Han
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  1. Center for Systems Biology, Soochow University, Jiangsu, China

    Bairong Shen

  2. School of Informatics and Computing, Indiana University, Bloomington, Indiana, USA

    Haixu Tang

  3. Department of Biomedical Informatics, University of California San Diego, La Jolla, California, USA

    Xiaoqian Jiang

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Han, M., Yang, P., Zhou, H., Li, H., Ning, K. (2016). Metagenomics and Single-Cell Omics Data Analysis for Human Microbiome Research. In: Shen, B., Tang, H., Jiang, X. (eds) Translational Biomedical Informatics. Advances in Experimental Medicine and Biology, vol 939. Springer, Singapore. https://doi.org/10.1007/978-981-10-1503-8_6

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