To understand and predict the behavior and function of RNAs, sophisticated tools are required to simulate and analyze their potential for forming structures. This volume discusses the various levels of prediction and algorithmic approaches to RNA folding. The chapters in this book cover topics such as energy parameters of the nearest-neighbor (NN) energy model; classified dynamic programming to address exponential growth of candidate structures that an RNA molecule may fold into; sequence evolution and conserved structures among multiple RNA sequences; the latest framework capable of handling both positive and negative RNA sequence design objectives; and kinetic folding approaches that look at the dynamic nature of RNA folding. 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 prools, and tips on troubleshooting and avoiding known pitfalls.
Cutting-edge and comprehensive,
RNA Folding: Methods and Prools
is a valuable resource for researchers who are interested in learning more about this important and developing field.