Genetics Oxford University
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We are all products of our genes, and Genetics is a major focus of NDM research. Our podcasts on genetics look at a variety of projects, including the study of some common and less-common inherited afflictions, as well as the effects our genes can have on disease susceptibility and the efficacy of treatment. Moreover, NDM researchers lead in studying the genetic variation within and between human populations, to understand the similarities and differences between us all.
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Gastrointestinal cancers
Dr Claire Palles studies whole genome sequencing data and targeted analyses with the aim of discovering genetic variants that affect susceptibility to colorectal cancer and Barrett’s oesophagus. The gastrointestinal track is responsible for more cancers than any other system. A condition called Barrett's oesophagus, characterised by a change in the cells lining the oesophagus, can lead to oesophageal adenocarcinoma. Only few people with Barrett's oesophagus will go on to develop cancer, and genome sequencing studies aim to identify genetic risk factors and therefore better target high-risk patients. Creative Commons Attribution-Non-Commercial-Share Alike 2.0 UK: England & Wales; http://creativecommons.org/licenses/by-nc-sa/2.0/uk/
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Rare neurological disorders
Chorea-Acanthocytosis: ChAc is a rare progressive neurological disorder caused by mutations in a very complex gene. Dr Antonio Velayos-Baeza is interested in two main projects: Chorea-acanthocytosis (ChAc), a rare autosomal-recessive disorder that is characterised by progressive neurodegeneration and red cell acanthocytosis (spiky red blood cells), and Developmental dyslexia, the most common of the childhood learning disorders. Creative Commons Attribution-Non-Commercial-Share Alike 2.0 UK: England & Wales; http://creativecommons.org/licenses/by-nc-sa/2.0/uk/
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Computation and genetics
Resistance to drugs in bacteria can be aquired by swapping genes between individual bacteria. Computer programs developed by Dr Iqbal enable doctors to predict which antibiotics will be met with drug resistance, enabling the selection of the right drug. BIOINFORMATICS & PATHOGEN GENOMICS
Dr Zamin Iqbal studies the DNA of bacteria and parasites, and compares the genomes of individual pathogens to track the spread of antibiotic resistance. Pathogens accumulate small genetic changes over time, and by tracking these changes, it is possible to map the spread of an infection. This enables better surveillance of pathogen evolution, within a host, within a hospital and across the world. Creative Commons Attribution-Non-Commercial-Share Alike 2.0 UK: England & Wales; http://creativecommons.org/licenses/by-nc-sa/2.0/uk/ -
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The Evolution of the Genome
Computational and stastistical methods help us understand evolution as well as genetic disease. Professor Gerton Lunter is interested in investigating the processes of evolution and biology using computational methods. His focus is on sequencing data; Professor Lunter develops methods to investigate evolutionary questions in population genetics. Creative Commons Attribution-Non-Commercial-Share Alike 2.0 UK: England & Wales; http://creativecommons.org/licenses/by-nc-sa/2.0/uk/
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DNA replication and Cancer
DNA replication and Cancer The process of DNA replication is complex, and mistakes can lead to genome instability. Surveillance systems are not always successful which results in mutations that have the potential to inactivate genes or change their activity. This can lead to cancer, and many chemotherapeutic drugs are designed to disrupt DNA replication. A better understanding of these mechanisms can help us develop new drugs with reduced side effects. Creative Commons Attribution-Non-Commercial-Share Alike 2.0 UK: England & Wales; http://creativecommons.org/licenses/by-nc-sa/2.0/uk/
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Big Data
Over the past decade, data-driven science has produced enormous sets of data. The convergence of statistics and computer science, in the field known as machine learning, provide the means to understand these large datasets. Ultimately, machine learning algorithms will be develop into clinical decision making support systems. Creative Commons Attribution-Non-Commercial-Share Alike 2.0 UK: England & Wales; http://creativecommons.org/licenses/by-nc-sa/2.0/uk/