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Computational and Systems Biology

Head of Department: Professor Chris Rawlings

Departmental Secretary: Di Dawkins

The Computational and Systems Biology Department undertakes research and development in mathematical, statistical and computational solutions to biological problems at all levels of biological scale. We are developing methods, models and software which contribute to all of the strategic programmes within Rothamsted Research.

Applied Statistics Group

The group has expertise in a wide range of statistical methods related to the design and analysis of field scale agro-ecology experiments - in particular in the application of mixed modelling methods. The group also works on methods for analysis of metagenomic datasets. The Applied Statistics group collaborates extensively within the Institute providing consulting and training in the design of experiments, data analysis and interpretation.

Applied Bioinformatics Group

The Applied Bioinformatics group has expertise in the development of software tools and application of data integration methods used to support systems and network-based approaches to the analysis of large genetic and genomics datasets. The Bioinformatics group supports a wide range of software and databases being used by Rothamsted scientists and collaborates extensively, providing consulting and training in the analysis of molecular biology data, in particular next generation sequencing datasets.

Bioinformatics

The main focus of the bioinformatics group is on network based data integration for candidate gene prediction and prioritisation, and application to biological processes relevant to plant pathology and crop science. The semantic and syntactic heterogeneity of biological data presents major challenges for integration. Our approach has been to use graph based methods which allow alignment of data from multiple sources and which facilitate the visualisation and analysis of the resulting networks. We are investigating the use of network based approaches to predict genes associated with pathogenicity in plant fungal pathogens. We are also interested in machine learning methods for exploiting the high dimensional data emerging from large scale experiments.

Movement Pattern Modelling Group

Our research on Movement Pattern Modelling uses advances made in the novel physics and mathematics of optimal searching, random walks and turbulence to develop predictive, validated mechanistic models of invertebrate movement patterns over landscape and regional scales.

Climate Change Impacts

Food security has become a major challenge given the projected need to increase world food supply by about 70% by 2050. Global warming, characterized by shifts in weather patterns and increases in climatic variability and extremes, represent an additional challenge to achieve this goal. New wheat cultivars will be required for a rapidly-changing environment putting severe pressure on breeders who should select for climate conditions which can only be predicted with a great degree of uncertainty. We are developing mathematical and simulation models of crop-climate interactions to quantify future threats to crops and hence identify targets for crop improvement in a changing climate.

Population ecology, epidemiology and evolutionary biology group.

The group focuses on the integration of modelling with field and laboratory experiments to study population dynamics/epidemiology and evolutionary ecology of plants and their pests and pathogens. Current key areas include:

sampling and control of invasive pathogens,
evolutionary ecology of plant pests and pathogens and
the sustainability of crop protection.

Key application areas are

forest tree diseases such as sudden oak death (Phytophthora ramorum), acute oak decline (causal organism unknown) and ash dieback (Chalara fraxinea) and
crop diseases such as Stem rust Ug99 (Puccinia graminis f. sp. tritici), a pathogen of wheat threatening recurrent famine in parts of Africa and Asia, cassava virus diseases in Africa and a range of fungal disease of wheat and oilseed rape in the UK.

As well as addressing fundamental research questions in these areas, the group has a strong track-record in collaborating with policy makers, regulatory agencies and industrial stakeholders.