By a News Reporter-Staff News Editor at Information Technology Newsweekly -- Data detailed on Proteomics have been presented. According to news reporting out of Durham, North Carolina, by VerticalNews editors, research stated, "The goal of many proteomics experiments is to determine the abundance of proteins in biological samples, and the variation thereof in various physiological conditions. High-throughput quantitative proteomics, specifically label-free LC-MS/MS, allows rapid measurement of thousands of proteins, enabling large-scale studies of various biological systems."
Our news journalists obtained a quote from the research from Duke University Medical Center, "Prior to analyzing these information-rich datasets, raw data must undergo several computational processing steps. We present a method to address one of the essential steps in proteomics data processing -the matching of peptide measurements across samples. We describe a novel method for label-free proteomics data alignment with the ability to incorporate previously unused aspects of the data, particularly ion mobility drift times and product ion information. We compare the results of our alignment method to PEPPeR and OpenMS, and compare alignment accuracy achieved by different versions of our method utilizing various data characteristics. Our method results in increased match recall rates and similar or improved mismatch rates compared to PEPPeR and OpenMS feature-based alignment. We also show that the inclusion of drift time and product ion information results in higher recall rates and more confident matches, without increases in error rates. Based on the results presented here, we argue that the incorporation of ion mobility drift time and product ion information are worthy pursuits."
According to the news editors, the research concluded: "Alignment methods should be flexible enough to utilize all available data, particularly with recent advancements in experimental separation methods."
For more information on this research see: A flexible statistical model for alignment of label-free proteomics data--incorporating ion mobility and product ion information. Bmc Bioinformatics, 2013;14():364. (BioMed Central - www.biomedcentral.com/; Bmc Bioinformatics - www.biomedcentral.com/bmcbioinformatics/)
Our news journalists report that additional information may be obtained by contacting A.M. Benjamin, Institute for Genome Sciences and Policy, Duke University Medical Center, Durham, North Carolina, United States. Additional authors for this research include J.W. Thompson, E.J. Soderblom, S.J. Geromanos, R. Henao, V.B. Kraus, M.A. Moseley and J.E Lucas.
Keywords for this news article include: Durham, Proteomics, United States, North Carolina, North and Central America.
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