Ribonucleic acid (RNA) is a large class of macromolecules that plays a key role in the communication of biological information between DNA and proteins. RNAs have been also shown to perform enzymatic catalysis. Recently, numerous new RNAs have been identified and shown to perform essential regulatory roles in cells.As with proteins, the function of RNA depends on its structure, which in turn is encoded in the linear sequence. The secondary structure of RNA is defined by canonical base pairs, while the tertiary (3D) structure is formed mostly by non-canonical base pairs that form three-dimensional motifs. RNA is similar to proteins in that the development of methods for 3D structure prediction is absolutely essential to functionally interpret the information encoded in the primary sequence of genes. For proteins there are many freely available methods for automated protein 3D structure prediction that produce reasonably accurate and useful models. There are also methods for objective assessment of the protein model quality. However, there are no such methods for automated 3D structure modelling of RNA. There are only methods for RNA secondary structure prediction and a few methods for manual 3D modelling, but no automated methods for comparative modelling, fold-recognition of RNA, and evaluation of models. Only recently a few methods for de novo folding of RNA appeared, but they can provide useful models only for very short molecules.Recently, inspired by methodology for protein modelling, we have developed prototype tools for both comparative (template-based) and de novo (template-free) modelling of RNA, which allow for building models for very large RNA molecules. These tools will be further optimized and tested. The major goal is to developed tools for RNA modelling to the level of existing protein-modelling methods and to combine RNA and protein-centric methods to allow multiscale modelling of protein-nucleic acid complexes, either with or without the aid of experimental data. This proposal also includes the development of methods for the assessment of model quality and benchmarking of methods. The software tools and the theoretical predictions will be extensively tested (also by experimental verification of models), optimized and applied to biologically and medically relevant RNAs and complexes.In one sentence: The aim of this project is to use bioinformatics and experimental methods to crack the code of sequence-structure relationships in RNA and RNA-protein complexes and to revolutionise the field of RNA & RNP modelling and structure/function analyses.