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Springer Methodologies of Multi-Omics Data Integration and Data Mining: Techniques and Applications

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Description

This comprehensive guide explores multi-omics big-data integration and data-mining techniques essential for modern biomedical research. The book addresses the challenge of aggregating multi-omics data from diverse sources whilst providing practical solutions for clinical and biomedical applications. Organised across eight chapters, the work systematically covers data integration methodologies, data-mining approaches, and real-world applications in the omics field. Each section is structured around the fundamental questions of "What", "Why" and "How", ensuring readers gain both theoretical understanding and practical implementation knowledge. Part of the Translational Bioinformatics series (volume 19), this resource bridges the gap between complex multi-omics datasets and actionable biomedical insights, making it invaluable for researchers, clinicians and data scientists working with high-dimensional biological data.

Key Features

Eight-chapter structure covering introduction, omics integration techniques, and practical applications in multi-omics research.

Detailed explanations of data integration and data-mining methodologies with supportive examples throughout the Springer publication.

Addresses the challenge of combining multi-omics data from various sources for biomedical and clinical applications.

Part of the Translational Bioinformatics series (volume 19), providing expert-level insights into data mining techniques.

Practical guidance on translating complex multi-omics datasets into clinically relevant biomedical discoveries.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
16 January 2024
Listed Since
20 December 2023

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