AWK
AWK is a s a small, C-style programming language designed for text processing and typically used as a data extraction and reporting tool. It is a standard feature of most Unix-like operating systems. Many UNIX utilities generates rows and columns of information, AWK is an excellent tool for processing these rows and columns, and is easier to use AWK than most conventional programming languages.
For queries about this topic, contact Roshan Sood.
Projects
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.
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
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.
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.
Porcupine Basin Project
Louise Watremez
The Porcupine Basin is a narrow failed rift, offshore SW Ireland, featuring extreme crustal thinning. The M61/2 survey (May 2004, T. Reston and B. O'Reilly) allowed for the acquisition of seismic refraction data across and along the basin, along 5 transects. The processing of the data along these transects will give us information about the crustal structure across the basin, faulting due to the crustal extension, nature of the upper-mantle, etc. This project is funded by Petroleum Infrastructure Programme (PIP).
People
Professor, Medicine (FM)
Professor, Medicine (FM)
Professor, Electronics and Computer Science (FPAS)
Professor, Medicine (FM)
Senior Lecturer, Medicine (FM)
Lecturer, Biological Sciences (FNES)
Research Fellow, Ocean & Earth Science (FNES)
Postgraduate Research Student, Medicine (FM)
Postgraduate Research Student, Engineering Sciences (FEE)
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