Methodologies of Multi-Omics Data Integration and Data Mining ()

Methodologies of Multi-Omics Data Integration and Data Mining ()

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Methodologies of Multi-Omics Data Integration and Data Mining ()

By Kang Ning

By Kang Ning

This book features multi-omics big-data integration and data-mining techniques. In the omics age, paramount of multi-omics data from various sources is the new challenge we are facing, but it also provides clues for several biomedical or clinical applications. This book focuses on data integration and data mining methods for multi-omics research, which explains in detail and with supportive examples the “What”, “Why” and “How” of the topic. The contents are organized into eight chapters, out of which one is for the introduction, followed by four chapters dedicated for omics integration techniques focusing on several omics data resources and data-mining methods, and three chapters dedicated for applications of multi-omics analyses with application being demonstrated by several data mining methods. This book is an attempt to bridge the gap between the biomedical multi-omics big data and the data-mining techniques for the best practice of contemporary bioinformatics and the in-depth insights for the biomedical questions. It would be of interests for the researchers and practitioners who want to conduct the multi-omics studies in cancer, inflammation disease, and microbiome researches.

Product Details

  • Publisher: Springer Nature Singapore, January 2023;
  • Language: English
  • ISBN: 9789811982101
  • ISBN: 9789811982095

The book “Multi-Omics Big-Data Integration and Data-Mining Techniques” written by Kang Ning is a comprehensive guide for researchers and practitioners interested in conducting multi-omics studies in the fields of cancer, inflammation disease, and microbiome research. Published by Springer Nature Singapore in January 2023, this book provides in-depth insights and practical methods for integrating and mining multi-omics data.

In the era of omics, the generation of vast amounts of data from various sources poses challenges but also presents opportunities for biomedical and clinical applications. This book addresses the need to effectively analyze and interpret multi-omics data to gain valuable insights into complex biological systems. With a focus on data integration and data mining techniques, the author explains the “What,” “Why,” and “How” of multi-omics research through detailed explanations and illustrative examples.

The book is divided into eight chapters, covering various aspects of multi-omics research. The first chapter serves as an introduction, providing an overview of the field and setting the stage for the subsequent chapters. The following four chapters delve into omics integration techniques, exploring different omics data resources and data-mining methods. The remaining three chapters showcase the application of multi-omics analyses, demonstrating the use of various data mining techniques.

One of the key strengths of this book is its emphasis on bridging the gap between biomedical multi-omics big data and data-mining techniques. It offers a practical guide for researchers and practitioners, providing them with the tools and knowledge to navigate the complexities of multi-omics research. By combining theoretical foundations with real-world examples, the author enables readers to understand the underlying principles and apply them to their own research projects.

Readers will appreciate the thoroughness with which the author discusses various omics integration techniques. The book covers a wide range of topics, including genomics, transcriptomics, proteomics, metabolomics, and epigenomics. By exploring the strengths and limitations of different data resources and data-mining methods, readers gain a comprehensive understanding of the field and can make informed decisions about their own research approaches.

In addition to the theoretical aspects, the book also focuses on practical applications of multi-omics analyses. The author demonstrates how data mining methods can be used to uncover meaningful patterns and relationships in complex biological datasets. By providing step-by-step instructions and case studies, readers can learn how to apply these techniques to their own research projects and gain novel insights into their data.

Overall, “Multi-Omics Big-Data Integration and Data-Mining Techniques” is a valuable resource for researchers and practitioners in the field of bioinformatics and biomedical research. The book not only provides a comprehensive overview of multi-omics research but also equips readers with the necessary tools and knowledge to conduct their own studies. Whether you are a seasoned expert or a novice in the field, this book offers a wealth of information and guidance to enhance your understanding and practice of multi-omics research.

If you are interested in conducting multi-omics studies or want to stay at the forefront of bioinformatics research, “Multi-Omics Big-Data Integration and Data-Mining Techniques” is a must-have addition to your library. Order your copy today and unlock the potential of multi-omics research!

Product Details

  • Publisher: Springer Nature Singapore, January 2023;
  • Language: English
  • ISBN: 9789811982101
  • ISBN: 9789811982095

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