RNA 3D Structure Analysis and Prediction (Paperback)

Neocles Leontis

ISBN 10: 3642445691 / ISBN 13: 9783642445699

Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin, 2014

About this Item

Paperback. With the dramatic increase in RNA 3D structure determination in recent years, we now know that RNA molecules are highly structured. Moreover, knowledge of RNA 3D structures has proven crucial for understanding in atomic detail how they carry out their biological functions. Because of the huge number of potentially important RNA molecules in biology, many more than can be studied experimentally, we need theoretical approaches for predicting 3D structures on the basis of sequences alone. This volume provides a comprehensive overview of current progress in the field by leading practitioners employing a variety of methods to model RNA 3D structures by homology, by fragment assembly, and by de novo energy and knowledge-based approaches. With the dramatic increase in RNA 3D structure determination in recent years, we now know that RNA molecules are highly structured. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9783642445699

Bibliographic Details

• Title: RNA 3D Structure Analysis and Prediction (Paperback)
• Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin
• Publication Date: 2014
• Language: English
• ISBN 10: 3642445691
• ISBN 13: 9783642445699
• Binding: Paperback
• Condition: new

About this title

Synopsis

With the dramatic increase in RNA 3D structure determination in recent years, we now know that RNA molecules are highly structured. Moreover, knowledge of RNA 3D structures has proven crucial for understanding in atomic detail how they carry out their biological functions. Because of the huge number of potentially important RNA molecules in biology, many more than can be studied experimentally, we need theoretical approaches for predicting 3D structures on the basis of sequences alone. This volume provides a comprehensive overview of current progress in the field by leading practitioners employing a variety of methods to model RNA 3D structures by homology, by fragment assembly, and by de novo energy and knowledge-based approaches.