Patrice Koehl
Department of Computer Science
Genome Center
Room 4319, Genome Center, GBSF
451 East Health Sciences Drive
University of California
Davis, CA 95616
Phone: (530) 754 5121
koehl@cs.ucdavis.edu




Computational Structural Biology: Winter 2024


RNA structure prediction


The central dogma of molecular biology describes the flow of genetic information from DNA to protein via an RNA intermediate. For many years, RNA has been considered simply as a messenger relaying information between DNA and proteins. Recent advances in next generation sequencing technology, bioinformatics, and non-coding RNA biology have highlighted the many important roles of RNA in virtually every biological process. Our understanding of RNA biology has been further enriched by a number of significant advances in probing RNA structures. Here we highlight how we can predict such structures, with a main focus on secondary structure.

Computational approaches to RNA structure prediction usually fall into two categories: those that rely on covariation (requiring a multiple sequence alignment), and those that work on a single sequence, using a free energy model to predict the conformation of that sequence. We analyse both.



Different types of RNA secondary structures



Lecture Notes


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Further Reading









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