{"id":344,"date":"2013-10-29T10:23:00","date_gmt":"2013-10-29T10:23:00","guid":{"rendered":"http:\/\/blogs.kent.ac.uk\/biosciences\/?p=344"},"modified":"2013-10-29T15:06:22","modified_gmt":"2013-10-29T15:06:22","slug":"research-seminar-exploiting-protein-evolution-to-predict-protein-functions-and-functional-networks","status":"publish","type":"post","link":"https:\/\/blogs.kent.ac.uk\/biosciences\/2013\/10\/29\/research-seminar-exploiting-protein-evolution-to-predict-protein-functions-and-functional-networks\/","title":{"rendered":"Research Seminar: Exploiting protein evolution to predict protein functions and functional networks"},"content":{"rendered":"

Professor Christine Orengo<\/strong>
\nDepartment of Structural & Molecular Biology, University College London<\/strong><\/p>\n

Monday 4th November, 4.00 p.m., Ingram Lecture Theatre<\/strong><\/p>\n

We have developed a classification of protein domains (CATH-Gene3D) which groups protein domains into evolutionary superfamilies. This currently contains more than 20 million sequences from more than 6000 completed genomes, including model organisms such as human, mouse, rat etc. We are now exploiting homology based methods to predict the functions of uncharacterised proteins in this resource. These approaches allow us to infer functions for a significant proportion of the sequences. We are also predicting the interactions, networks and biological processes in which the proteins participate. This is being done by combining available experimental data with predictions of functional associations. Our network based approaches have proved successful in detecting some \u2018hidden players\u2019 associated with the mitotic spindle and chromatin compaction. They have also revealed the rewiring of protein networks in fission yeast under stress conditions.<\/p>\n

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