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SUMMARY:BSU Seminar: “Biomarker discovery through statistical signal pro
 cessing and Bayesian modelling on large-scale quantitative proteomics data
 ” - Prof. Andrew Dowsey\, University of Bristol
DTSTART:20180315T143000Z
DTEND:20180315T153000Z
UID:TALK101713@talks.cam.ac.uk
CONTACT:Alison Quenault
DESCRIPTION:Abstract: Critical to the success of the stratified medicine a
 pproach is a diagnostic programme that can reliably characterise molecules
  that act as markers for early disease detection and subsequent drug selec
 tion based on safety and efficacy. A number of large-scale facilities worl
 dwide have been established to systematically discover these biomarkers\, 
 including the Stoller Biomarker Discovery Centre (SBDC) for proteomics in 
 Manchester. Despite strict operating procedures that control sample prepar
 ation and analysis\, analysis of biomedical proteomics and metabolomics da
 ta is challenged by the biological complexity\, heterogeneity and dynamic 
 range inherent in clinical samples\, requiring large sample sizes for conf
 ident discovery\, which in turn leads to issues with reproducibility. To o
 vercome the limitations of existing informatics pipelines for robust ident
 ification\, quantification and differential analysis\, we have developed a
  novel workflow for biomarker discovery that for the first time extracts p
 eaks and whole biochemical features through statistical signal processing 
 of the unprocessed raw data. Recently\, we have further extended this pipe
 line with a Bayesian modelling approach to assess peptide reproducibility 
 for robust\, reliable protein quantification and significance testing\, an
 d a new file format for scalable computation. In this talk I will discuss 
 the translation of these methods into a platform for the SBDC\, plus the p
 otential of adapting these methods for corresponding applications in metab
 olomics.
LOCATION:Large Seminar Room\, 1st Floor\, Institute of Public Health\, Uni
 versity Forvie Site\, Robinson Way\, Cambridge
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