Modeling the structure of RNA molecules and of their interactions is always a difficult task. RNA molecules are highly flexible and may undergo large conformational changes upon binding. For proteins, knowledge-based (KB) potentials have proven not only to be successful for minimizing the structures but also for selecting decoys in a structure prediction context. A collaborative work aims at extending Monte-Carlo reference states developed by VIGG for proteins for RNA structure and ion binding position predictions.
Pattern matching and word counting are a powerful tool to address some key questions : understanding chromosome dynamics (rearrangements, tandem repeats) or identifying conserved regulatory regions (transcription factor binding sites). This project addresses combinatorial issues arising from Next Generation Sequencing data. Assembly problems are especially studied, and benchmark tools are expected.
