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RNA Folding

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Attention for Chapter 12: Developing Complex RNA Design Applications in the Infrared Framework.
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Chapter title
Developing Complex RNA Design Applications in the Infrared Framework.
Chapter number 12
Book title
RNA Folding
Published in
Methods in molecular biology, February 2012
DOI 10.1007/978-1-0716-3519-3_12
Pubmed ID
Book ISBNs
978-1-07-163518-6, 978-1-07-163519-3
Authors

Hua-Ting Yao, Yann Ponty, Sebastian Will, Yao, Hua-Ting, Ponty, Yann, Will, Sebastian

Abstract

Applications in biotechnology and bio-medical research call for effective strategies to design novel RNAs with very specific properties. Such advanced design tasks require support by computational tools but at the same time put high demands on their flexibility and expressivity to model the application-specific requirements. To address such demands, we present the computational framework Infrared. It supports developing advanced customized design tools, which generate RNA sequences with specific properties, often in a few lines of Python code. This text guides the reader in tutorial format through the development of complex design applications. Thanks to the declarative, compositional approach of Infrared, we can describe this development as a step-by-step extension of an elementary design task. Thus, we start with generating sequences that are compatible with a single RNA structure and go all the way to RNA design targeting complex positive and negative design objectives with respect to single or even multiple target structures. Finally, we present a "real-world" application of computational design to create an RNA device for biotechnology: we use Infrared to generate design candidates of an artificial "AND" riboswitch, which activates gene expression in the simultaneous presence of two different small metabolites. In these applications, we exploit that the system can generate, in an efficient (fixed-parameter tractable) way, multiple diverse designs that satisfy a number of constraints and have high quality w.r.t. to an objective (by sampling from a Boltzmann distribution).

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