Skip to content

David Wedge

  • Research Fellow
  • University of Manchester School of Chemistry
  • 0ReadersNumber of instances of David's publications in Mendeley libraries. Updated daily.
  • 16PublicationsNumber of items in David's My Publications folder on Mendeley.

Research interests

metabolomicsNeural Networks; cancerGenetic ProgrammingBayesian Networks

About

I am a Research Fellow in cancer metabolomics and bioinformatics at the University of Manchester. I use a variety of statistical and machine learning techniques to gain insights into the progress and treatment of cancers via the proteomic and metabolomic analysis of serum and plasma samples. The main machine learning paradigms that I use are Genetic Programming and Bayesian networks. Most of my work uses a 'systems' approach, in which biological systems are treated as a single system made up of interacting parts. My previous research is very varied but revolves around the idea of developing machine learning techniques to solve a variety of real-world problems. It has included: the identification of low-abundance proteins via N-terminal enrichment of tryptic peptides (2009-10); the detection of airborne pollutants using arrays of organic-field effect transistors (2006-9); psychological profiling through neural network processing of facial images extracted from video footage (2006); and the estimation of wave-overtopping rates at sea-walls using hybrid neural networks (2002-5).

Followers (12)

Explore network

Following (9)

Explore network

Publications (5)

  • Analysis of a complete DNA-protein affinity landscape.

    • Rowe W
    • Platt M
    • Wedge D
    • et al.
    N/AReaders
    N/ACitations
    Get full text
  • Convergent evolution to an aptamer observed in small populations on DNA microarrays

    • Rowe W
    • Platt M
    • Wedge D
    • et al.
    N/AReaders
    N/ACitations
  • Predictive models for population performance on real biological fitness landscapes

    • Rowe W
    • Wedge D
    • Platt M
    • et al.
    N/AReaders
    N/ACitations
  • Aptamer evolution for array-based diagnostics.

    • Platt M
    • Rowe W
    • Wedge D
    • et al.
    N/AReaders
    N/ACitations
    Get full text
  • Wave Overtopping Prediction Using Global-Local Artificial Neural Networks

    • Wedge D
    N/AReaders
    N/ACitations

Professional experience

Research Fellow

University of Manchester, School of Chemistry

April 2010 - Present

Education history

PhD Computer Science

Manchester Metropolitan University

October 2002 - November 2005(3 years)

MSc Software Development

University of Huddersfield

September 2000 - July 2001(10 months)

BA Chemistry

Department of Chemistry, University of Oxford

October 1985 - June 1989(4 years)