Overview
The main objective of this project in Bioinformatics is to contribute a suite of (semi)-automated computational methods for producing SHAPE data, and interpret it on a structural level. The collaboration will provide efficient combinatorial algorithms, implemented within efficient computational methods, to accurately predict the structure(s) of RNA from SHAPE experiments.
Contrasting with previous effort, which typically derive a single secondary structure model from a single SHAPE profile, our method will attempt to produce a set of tentative 3D structures, along with relative frequencies, which best explain available SHAPE data. Another originality of our approach is the simultaneous analysis of SHAPE profiles associated with the original RNA on the one hand, and a collection of randomly-generated mutants on the other, produced by our experimental partner (B. Sargueil group – Faculté de pharmacie – Paris V) using a novel experimental protocol.
Aside from the development of the main modeling method, whose development is the object of ongoing research within AMIB, one of the main challenges is the development of accurate fragment-based strategies, based on the development of prior methods developed by the Canadian partners.
