RStudio
For queries about this topic, contact Marcin Knut.
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Projects
Application of RNA-Seq for gene fusion identification in blood cancers
William Tapper (Investigator), Marcin Knut
Gene fusions are often the cause of different blood cancers. As such, accurate identification of them provides information on the underlying cause of a cancer, ensuring appropriate choice of treatment. However, due to shortcomings of the currently applied methods for gene fusion identification, some of them escape undetected. We are employing RNA-Seq, a cutting-edge method for sequencing RNA, the messenger of genetic information, to investigate gene fusions.
BRECcIA - Building REsearch Capacity for sustainable water and food security In sub-saharan Africa
The BRECcIA project is aimed at developing research and researchers to understand water and food security challenges in sub-Saharan Africa
Characterisation of the Genomic Landscape in Splenic Marginal Zone Lymphoma
Sarah Ennis, Jane Gibson, Jon Strefford (Investigators), Carolina Jaramillo Oquendo, Helen Parker
This project aims to expand the catalogue of mutated genes in splenic marginal zone lymphoma (SMZL) and construct a detailed characterisation of the genetic landscape of this disease. Using next generation sequencing, we aim to identify somatic mutations in over 100 samples, and enrich clinical data with this information to improve patient treatment and prognosis.
Development and application of powerful methods for identifying selective sweeps
Andrew Collins, Reuben Pengelly, Timothy Sluckin, Sarah Ennis (Investigators), Clare Horscroft
This project is about detecting regions of the genome which have experienced selective pressure. To achieve this, mathematical models will be developed and applied to human genomic data sets, as well as to those of other species.
Effects of Sample Contamination on Alternate Allele Frequency
Jane Gibson (Investigator), Roshan Sood
Accurate calling of genetic variants is reliant on the purity of samples, contamination will reduce the accuracy of results. Currently there are few programs able to identify contamination in samples, potentially misinforming a researcher or clinician. To better understand the changes caused by sample contamination in
silico simulations were performed where a known percentage of DNA sequence reads from a contaminating
file were added. Understanding the changes will assist the development of a new method and program to
detect sample contamination.
Mathematical tools for analysis of genome function, linkage disequilibrium structure and disease gene prediction
Mahesan Niranjan, Andrew Collins, Reuben Pengelly (Investigators)
This iPhD project uses a Gaussian Bayesian Networks framework through Machine learning methods to predict which genes are involved in the development of different diseases.
Mathematical tools for analysis of genome function, linkage disequilibrium structure and disease gene prediction
Mahesan Niranjan, Andrew Collins, Reuben Pengelly (Investigators)
This PhD project uses a Monte Carlo molecular simulation processes approach to predict which genes are involved in the development of different diseases.
Mathematical tools for analysis of genome function, linkage disequilibrium structure and disease gene prediction
Andrew Collins, Mahesan Niranjan, Reuben Pengelly (Investigators), Alejandra Vergara Lope
This iPhD project uses a Gaussian Bayesian Networks approaches framework through machine learning approach to predict which genes are involved in the development of different diseases.
SAVE: Solent Achieving Value through Efficiency
Patrick James, Ben Anderson (Investigators), Luke Blunden
Analysis of 15 minute electricity consumption and 10 second instantaneous power data from 4,000+ households in the Solent region collected over 3 years of a randomised control trial study.
Studying microevolution in clinical isolates of Neisseria lactamica
Robert Read (Investigator), Jay Laver, Anish Pandey
We intranasally infected and successfully colonised six volunteers with Neisseria lactamica, a commensal species genetically similar to Neisseria meningitidis. A bioinformatics approach was then used to understand the microevolution of this bacterium and its adaptations to the nasopharynx.
People
Professor, Medicine (FM)
Professor, Medicine (FM)
Professor, Electronics and Computer Science (FPAS)
Professor, Medicine (FM)
Professor, Mathematics (FSHS)
Professor, Medicine (FM)
Senior Lecturer, Civil Engineering & the Environment (FEE)
Senior Lecturer, Medicine (FM)
Lecturer, Biological Sciences (FNES)
Senior Research Fellow, Civil Engineering & the Environment (FEE)
Senior Research Fellow, Medicine (FM)
Research Fellow, Medicine (FM)
Research Fellow, Civil Engineering & the Environment (FEE)
Research Fellow, Social Sciences (FSHS)
Postgraduate Research Student, Mathematics (FSHS)
Postgraduate Research Student, Mathematics (FSHS)
Postgraduate Research Student, Electronics and Computer Science (FPAS)
Postgraduate Research Student, Medicine (FM)
Postgraduate Research Student, Medicine (FM)
Postgraduate Research Student, Biological Sciences (FNES)
Postgraduate Research Student, Medicine (FM)
Postgraduate Research Student, Engineering Sciences (FEE)
Postgraduate Research Student, Engineering Sciences (FEE)
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None, None
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