Research

Bioinformatics research in the school of Veterinary Medicine and Science, University of Nottingham. 

Research interests are in bioinformatics, comparative genomics and molecular evolution particularly in the fields of pathogen biology and animal health and disease.

Major Collaborators:

Current Research

Bioinformatics is a cohesive discipline bringing together computer science statistics and biology. I collaborate widely with experimental and computational biologists. Current areas of active research include:

i) Comparison of complex biological datasets.

Biologists are fortunate to be researching in a data rich age, where gene and genome sequences from multiple species are available and can be linked either independently or through specialist databases to data types as diverse as structure, function, expression and evolutionary history. The successful mining and combination of this data can bolster traditional bench research by providing a filter or by generation of novel avenues of research. The advent of cost effective high throughput DNA sequencing has revolutionised biomedical research with increased emphasis on stratified or personalised medicine. ADAC has experience in the identification and functional prioritisation of genomic variants related to human and animal health including the development of methods and software for bespoke analysis [1-5]. To fully understand a biological system requires effective integration of high throughput data from different systems (genomic/proteomic/transcriptomics.) whilst these individual methods are becoming commonplace, the integration of them is still a specialist endeavour. ADAC has demonstrable experience in gaining external funding to undertake these studies [e.g BBSRC grants BB/M017524/1, BB/M018520/1 and BB/K017810/1] importantly ADAC has developed recognised infrastructure to ensure the effective delivery of large scale studies e.g as the centre for transcriptomics analysis for EU Prohealth [EU FP7 #613574].

1Epigenetics. 2014 Sep;9(9):1228-37; 2 Hum Mol Genet. 2014 Jul 1;23(13):3362-74; 3J Med Genet. 2014 Jan;51(1):61-7; 4Am J Hum Genet. 2013 Nov 7;93(5):932-44; 5Am J Hum Genet. 2013 Aug 8;93(2):346-56.

ii) Identification and characterization of the genes and molecular mechanisms underlying fertility in insects acting as vectors for infectious diseases.

Malaria is transmitted only by the female mosquito of some species of Anopheles. Most of our understanding on reproductive biology of the mosquito originates from studies done in An. gambiae, the most effective malaria vector. The vectorial capacity of An. gambiae, among other elements of mosquito biology largely depends on the high reproductive rate of these mosquitoes. Interestingly, the high reproductive capacity is guaranteed by a single mating event and multiple blood feeding. A mated female can generate more than a hundred eggs from the blood obtained by a single bite. After copulation, significant behavioural and physiological changes occur in the female, including permanent loss of receptivity to further insemination, and stimulus to oviposition. Our aim is to identify the genes and molecular mechanisms controlling such physiological and behavioural changes, as promising starting point for developing effective population control measures based on reducing reproduction success (Neafsey et al Science 2015, Dottorini et al Faseb J 2013; Dottorini et al PNAS 2007).

iii) Comparative genomics of the mammalian synapse proteome.

Analysis of the post-synaptic proteome, a defined group of proteins with known importance in the processes of learning and memory, offers an insight into the development and evolution of the synapse, the basic building block of cognition. In collaboration with Seth Grant, The Sanger Institute, we are leading investigations into the evolutionary origin and subsequent modification of the protein networks of the mammalian synapse (see Emes et al Nature Neuroscience 2008, Nithianantharajah et al Nature Neuroscience 2013 and Emes and Grant Annual Reviews in Neuroscience 2012).

iv) Implementation of new approaches for the understanding and diagnosis of infectious diseases in animals and humans.

The current interests are in the development of original methods and algorithms to gain deeper insight in biological problems related to animal health and welfare and develop diagnostic tools. To this purpose different disciplines and knowledge/skills are merged, including: machine learning methods, ‘omics and bioinformatics to develop predictive models and solve data mining tasks, in particular in scenarios involving large-data (phenotype, genotype, behaviour, environment) combined with disease-related data. (Dottorini et al. Plos One 2013, Dottorini et al, BMC Bioinformatics 2011, Dottorini et al, BMC Bioinformatics 2011, Patent: PCT/GB2011/050302).

Future Research

Bioinformatics is a fast changing discipline, my lab aims to be analyzing important and interesting findings using the latest technologies.

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