|Effective Fishing of Characteristic Proteome Fractions and Identification of Biomarkers Therein: Application of VisualCockpit to Multidimensional Chromatogram and MS Data|
S. Kreusch, M. Nagel, R. Janetzko, G. A. Cumme, A. Winter, M. Pohl, A. Meier-Hellmann and H. Rhode
Characteristic 2D fractions are rapidly identified among thousands using interactive visualization, filtering and data mining with VisualCockpit. Biomarker candidates are found therein after identifying proteins from sequence tags. VisualCockpit correlates their concentrations, reflected by normalized MS peptide peak height sum, enzyme activity and immunoreactivity, to donor conditions.
|Simplifying the Flow of Drug Discovery Data|
Dr. Jonathan M.R. Davies
Regardless of research disciplines, scientists need to easily reach the information pertinent to their research. Ideally this data access is easy. Researchers also need the ability to ‘move the data around’ to gain a better view or different perspective. This data manipulation needs to be straightforward. Incorporating the varying views and information required by different scientific disciplines is a considerable challenge.
|A 1H-NMR Based Metabonomics Study of Urine and Plasma Obtained from Healthy Human Subjects|
E.M. Lenz, J. Bright, I.D. Wilson, S.A. Morgan and A.F.P.Nash
An investigation on the plasma and urine samples of healthy male volunteers designed to evaluate the variability in metabonomic data, when severe life-style and dietary restrictions are imposed.
|Metabonomics, Dietary Influences and Cultural Differences: A 1H NMR-Based Study of Urine Samples Obtained From Healthy British and Swedish Subjects|
E.M. Lenz, J. Bright, I.D. Wilson1, A. Hughes, J. Morrisson, H. Lindberg and A. Lockton
Here, we describe two investigations on healthy subjects designed to evaluate the variability in metabonomic data, in view of dietary influences and cultural trends.
|Metabonomics for MolPAGE Discovering Diabetes Biomarkers|
K. Magnus Åberg, Mark Jairaj, Henrik Toft Pedersen, Dorrit Baunsgaard
MolPAGE (Molecular Phenotyping to Accelerate Genomic Epidemiology) is an EU consortium with almost twenty collaborating universities and companies throughout Europe. One of the aims of MolPAGE is to find early onset biomarkersfor type 2 diabetes (T2DM) and cardio-vascular diseases(CVD).
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