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Application of Clinical Bioinformatics pp 23–57Cite as

Biostatistics, Data Mining and Computational Modeling

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Part of the book series: Translational Bioinformatics ((TRBIO,volume 11))

Abstract

With the rapid development of high-throughput experimental technologies, bioinformatics and computational modeling has been a rapid evolving science field concerned with the development of various analysis methods and tools for investigating these large biological data efficiently and rigorously. There are many methods and tools available for the analysis of single omics dataset. It is a great challenge that biological systems are being further investigated by integrating multiple heterogeneous and large omics data. Many powerful methods and algorithmic techniques have been developed to answer important biomedical questions through integrative analysis. In this chapter, in order to help the bench biologist analyze omics data, we introduced various methods from classical statistical techniques for single marker association and multivariate analysis to more recent advances from gene network analysis and integrative analysis of multi-omics data.

*Author contributed equally with all other contributors

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    Authors and Affiliations

    1. Center for Bioinformatics and Genomics, Department of Biostatistics and Bioinformatics, Tulane University, New Orleans, LA, 70112, USA

      Hao He & Jigang Zhang

    2. Center for Bioinformatics and Genomics, Tulane University, New Orleans, LA, USA

      Dongdong Lin & Yuping Wang

    3. Department of Biomedical Engineering, Tulane University, New Orleans, LA, USA

      Dongdong Lin & Yuping Wang

    4. Center for Bioinformatics and Genomics, Department of Biostatistics and Bioinformatics, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA

      Hong-Wen Deng Ph.D.

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    1. Hao He
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    Editors and Affiliations

    1. Shanghai Inst.of Clinical Bioinformatics, Zhongshan Hospital, Fudan University, Shang Hai, China

      Xiangdong Wang

    2. Institute of Health Care Engineering, Graz University of Technology, Graz, Austria

      Christian Baumgartner

    3. School Of Medicine & Medical Science, University College Dublin, Dublin 4, Ireland

      Denis C. Shields

    4. Health and Tropical Medicine, Tulane University School of Public Healt, New Orleans, Louisiana, USA

      Hong-Wen Deng

    5. Section of Clinical Bioinformatics, Swiss Institute of Bioinformatics, Switzerland

      Jacques S Beckmann

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    He, H., Lin, D., Zhang, J., Wang, Y., Deng, HW. (2016). Biostatistics, Data Mining and Computational Modeling. In: Wang, X., Baumgartner, C., Shields, D., Deng, HW., Beckmann, J. (eds) Application of Clinical Bioinformatics. Translational Bioinformatics, vol 11. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-7543-4_2

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