The Challenge of Monitoring Biodiversity

Tue, 04 Aug 2015 14:12:04 +0000

a guest blog by Charlie Outhwaite, written for the 2015 Write About Research Competition. Biological diversity, or biodiversity, is a complex term encompassing the variety of life found on Earth. It incorporates not only differences between species but within species themselves and of the environments and ecosystems where they are found. We as humans benefit […]

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MRC Career Development Award for Doug Speed

3 February 2014

Congratulations to Doug Speed who has been successful in gaining an MRC career development award in biostatistics.

The MRC has identified advanced biostatistics as a methodology of strategic importance to UK science.  The MRC Biostatistics Fellowship is one of a number of qualitative and quantitative schemes supported by the MRC under the Strategic Skills Fellowships banner. The scheme expects to make up to 3 awards a year.

The aim of the scheme is to encourage broad training programmes in biostatistics to support talented researchers who have recently completed their PhDs and wish to move into statistically based health related research.

The aim of Doug's fellowship is to develop methods for better understanding the genetics behind complex traits, then to apply these methods to improve prediction and classification of diseases. There are many diseases which we know to be highly heritable, but for which we have struggled to understand the genetic factors influencing risk.  For example, twin and family studies have shown that at least 50% of an individual's risk of developing epilepsy can be explained by genetics, but so far, we have discovered only a handful of genetic mutations impacting risk which in total explain less than 1% of the variation.

To better understand these diseases, we need to devise methods which allow for the fact that there are likely to be many hundreds, if not thousands, of variants affecting risk. Even though we are unlikely to discover the majority of these, we can still benefit greatly by determining which types of variants are causal. This information can then be accommodated in prediction models, which can be used to select individuals at high risk of developing a condition, and also for classification; many diseases, especially neurological traits, are highly heterogeneous, so diagnoses and prognoses will benefit by being able to use genetics to group individuals into subtypes.

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