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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Computational Methods for Rna-RNA Interactions

Computational Methods for Rna-RNA Interactions

Varadarajan, Swetha

Hardcover

Series: Methods in Molecular Biology, Book 3079

General Mathematics

PREORDER - Expected ship date November 11, 2026

ISBN10: 1071655663
ISBN13: 9781071655665
Publisher: Humana
Published: Nov 11 2026
Pages: 621
Language: English
This volume looks at the latest approaches for RNA-RNA interaction prediction, with particular emphasis on machine learning and deep learning methodologies. The chapters in this book provide a structured and in-depth exploration of computational methods for RNA-RNA interaction prediction and analysis, with focus on specific machine learning or deep learning technique and its application to RNA-RNA interactions (RRIs)-related problems. Some of the topics covered in this book include support vector machines, decision trees, and random forests; recurrent neural networks and graph neural networks; polyhedral modeling; evolutionary and genetic algorithms; machine learning versus deep learning approaches; and emerging trends in RNA-RNA interaction prediction, including multimodal data integration and model interpretability. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.

Comprehensive and authoritative, Computational Methods for RNA-RNA Interactions: Methods and Protocols integrates biological insight with computational rigor, and aims to support researchers seeking to understand, predict, and analyze RRIs in a systematic and practical manner. The content in this volume is designed for a broad audience, including molecular biologists interested in computational approaches, computer scientists and bioinformaticians entering RNA biology, and interdisciplinary researchers working at the interface of these fields.

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