|Evaluation of Different Interpretation Strategies to Discover PTM in MS/MS Peptide Fragmentation Data|
Daniel Chamrad, Gerhard Korting, Ken Fantom, Andy West, Klaus Schneider, Ulrike Schweiger-Hufagel, Herbert Thiele and Martin Bluggel
The phenomenon of acquired high quality MS/MS spectra that can not be explained within typical sequence database searches is well known. Although protein identification was successful it is manually very laborious and in most cases even impossible to match these spectra with any suggested protein sequence. The procedure of second pass searches has been developed to overcome this problem. Here we report from our in house developed tool PTM-Explorer.
|Towards Understanding of Ryegrass-Endophyte Symbiosis through Data Integration of Transcriptome and Metabolome|
Mingshu Cao, Linda Johnson, Albert Koulman, Geoff Lane and Susanne Rasmussen
Combined with extensive bioinformatics analyses, our joint analysis of transcriptomics and metabolomics data has generated interesting findings which led to further laboratory verification, such as potential genes associated with alkaloid production.
|Herbal Metabolic Profiling of Raw and Steamed Panax notoginseng|
Eric C.Y. Chan, Swee-Lee Yap, Aik-Jiang Lau, Pay-Chin Leow, Ding-Fung Toh, and Hwee-Ling Koh
At present, metabolite profiling is of growing importance in herbal medicine fields such as breeding, formulation, quality control and clinical trials. Herbal metabolic profiling allows direct detection of down-stream derivatives of metabolites, arising from herbal formulation process, using metabolite profiling ultra performance liquid chromatography time-of-flight mass spectrometry.
|Metabolic Profiling of Human Blood Plasma by Combined Ultra Performance Liquid Chromatography / Mass Spectrometry|
Steve Bruce, Pär Jonsson, Henrik Antti, Olivier Cloarec, Stefan Marklund and Thomas Moritz
Metabolic profiling is concerned with the analysis of low molecular weight compounds present in complex samples such as plasma. Analytical techniques such as UPLC/MS are proving to be powerful tools for metabolic profiling on complex samples such as plasma. Here we describe a protocol of metabolic profiling analysis on plasma by UPLC/MS.
|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.
|Automated Profiling and Identification of Endogenous Peptidomic Markers in Human Plasma|
T. Richmond, M. Askenazi, J. Sutton and L. Bonilla
Development of robust methods that include the accurate identification of the relevant components of the peptidome is critical not only to our understanding of the biology of disease states, but also to our ability to discover markers for these states.
|Differential Expression Analysis using an Unlabelled Approach and a New Software for Relative Quantification of LC-MS Data|
John Flensburg, Carolina Johansson and Lars Sundstrom
DeCyder™ MS Differential Analysis Software (DeCyder MS) is a new tool for visualization, detection, identification and label-free relative quantification of LC-MS and LC-MS/MS data.
|KingFisher - A Multifunctional Tool for Proteomics|
Mehto, M., Walker, E., Maggott, K., Richmond, T., Partanen, M., Kymalainen, V., Lamberg, A.
In the proteomics area with the increasing capacity of the mass spectrometers, sample preparation is becoming a limiting step for protein identification. Magnetic particle based technology provides a rapid and easy solution for automation of the sample preparation step.
|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).