21st Century lectures in the curation and analysis of scientific and medical information, UCL

Following the first two dates in the C21st Curation public lecture series, we are pleased to provide further details of the third set of lectures focusing on the curation and analysis of scientific and medical information on Wednesday 9th May.
These free lectures will be open to students, professionals and the general public in the Chadwick lecture theatre at UCL from 6.00 -7.15pm. The lectures will be followed by a reception to which speakers and the audience are invited. For further information and directions see http://www.ucl.ac.uk/slais/21st-century-lectures/

The National Cancer Research Institute Informatics Initiative - Dr Fiona Reddington
Abstract: the arrival of high-throughput technologies in cancer science and medicine was heralded as the answer to our prayers; the possibility of truly personalised medicine was within our reach and the potential for knowledge generation was greater than ever before. The reality of the situation is a little different with researchers struggling to analyse the avalanche of information available to them and make the change from a reductionist world to the promised land of truly integrative translational medicine. The need for meaningful data sharing between disciplines and disease areas is becoming ever more pressing.
The NCRI (www.ncri.org.uk) Informatics Initiative aims to maximise the impact of the results of research funded by NCRI Partners by ensuring that data generated through research is put to maximum use by the cancer research community. It was the first ever winner of the Times Higher Research Award. This talk will describe the work of the NCRI Informatics Initiative with respect to promoting the use of common data standards and the facilitation of data sharing in an international context.

Collecting and using large scale data in biomedical research - Dr Paul Kellam, UCL
Abstract: the biomedical sciences are predicted to continue advancing at a tremendous rate in the 21st century. Hypothesis driven reductionist biology has delivered most of our current biological understanding and medical advances. Reductionism is powerful. However, its scope is recognised to be limited in the study of complex systems. Complexity is the study of large collections of small interacting units whose combined properties are greater than the sum of the unit parts. Complex systems can therefore have non-predictable attributes.
The human body is a complex system, the extent of which has now been revealed by determining the sequence of the human genome. The massive increase in large scale data collections for human and other organisms' genomes, genes and proteins means new ways for understanding the data must be developed. Here I will discuss the magnitude and diversity of genome scale data resources, how they can be used immediately to identify new drug treatments and how mathematical models and high performance computing will ultimately be required to understand human biological complexity.


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