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Structural genomics is the wide term which describes process of determination of structure representation of information in human genome and at present is limited almost exclusively on proteins. Although in common understanding genetic information means “genes and their encoded protein products”, thousands of human genes produce transcripts which are important in biological point of view but they do not necessarily produce proteins. Furthermore, even though the sequence of the human DNA is known by now, the meaning of the most of the sequences still remains unknown. It is very likely that a large amount of genes has been highly underestimated, mainly because the actual gene finders only work well for large, highly expressed, evolutionary conserved protein-coding genes. Most of those genome elements encode for RNA from which transfer and ribosomal RNAs are the classical examples. But beside these well-known molecules there is a vast unknown world of tiny RNAs that might play a crucial role in a number of cellular processes. Those elements are named Noncoding RNAs (ncRNA) and they perform their function without transcription to the protein product.
Here is proposed development of integrated bioinformatics platform that is specifically addressed for detecting, verifying, and classifying of noncoding RNAs. This complex approach to "Computational RNomics" will provide the pipeline which will be capable of detecting RNA motifs with low sequence conservation. It will also integrate RNA motif prediction which should significantly improve the quality of the RNA homolog search.

PEOPLE-RG-2009-249211

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