RNA Structure Prediction

1. Auflage 2023
ISBN: 978-1-0716-2770-9
Verlag: Springer US

Buch, Englisch, 290 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 598 g

Reihe: Methods in Molecular Biology

This book explores recent progress in RNA secondary, tertiary structure prediction, and its application from an expansive point of view. Because of advancements in experimental protocols and devices, the integration of new types of data as well as new analysis techniques is necessary, and this volume discusses additional topics that are closely related to RNA structure prediction, such as the detection of structure-disrupting mutations, high-throughput structure analysis, and 3D structure design. Written for the highly successful Methods in Molecular Biology series, chapters feature the kind of detailed implementation advice that leads to quality research results.
Authoritative and practical, RNA Structure Prediction serves as a valuable guide for both experimental and computational RNA researchers.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Iwakiri, Junichi

Kawaguchi, Risa Karakida

Fachgebiete

• Naturwissenschaften Biowissenschaften Biowissenschaften Genetik und Genomik (nichtmedizinisch)
• Naturwissenschaften Chemie Physikalische Chemie Quantenchemie, Theoretische Chemie

Inhaltsverzeichnis

Rtools: A Web Server for Various Secondary Structural Analyses on Single RNA Sequences.- Linear-Time Algorithms for RNA Structure Prediction.- Genome-Wide RNA Secondary Structure Prediction.- Nucleic Acid Structure Prediction Including Pseudoknots through Direct Enumeration of States: A User's Guide to the LandscapeFold Algorithm.- Metrics for RNA Secondary Structure Comparison.- RNA Secondary Structure Prediction Based on Energy Models.- RNA Secondary Structure Alteration Caused by Single Nucleotide Variants.- Evolutionary Conservation of RNA Secondary Structure.- Network-Based Structural Alignment of RNA Sequences Using TOPAS.- Fast RNA-RNA Interaction Prediction Methods for Interaction Analysis of Transcriptome-Scale Large Datasets.- Web Services for RNA-RNA Interaction Prediction.- ResidualBind: Uncovering Sequence-Structure Preferences of RNA-Binding Proteins with Deep Neural Networks.- RNA Structure Determination by High-Throughput Structural Analysis.- RNA 3D Modeling with FARFAR2, Online.- Automated 3D Design and Evaluation of RNA Nanostructures with RNAMake.- RNA 3D Structure Comparison Using RNA-Puzzles Toolkit.