The Experts below are selected from a list of 144 Experts worldwide ranked by ideXlab platform
Sang Won Lee - One of the best experts on this subject based on the ideXlab platform.
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Multiplexed Post-Experimental Monoisotopic Mass Refinement (mPE-MMR) to Increase Sensitivity and Accuracy in Peptide Identifications from Tandem Mass Spectra of Cofragmentation
Analytical chemistry, 2016Co-Authors: Inamul Hasan Madar, Richard D Smith, Hokeun Kim, Dong Gi Mun, Sangtae Kim, Sang Won LeeAbstract:Mass spectrometry (MS)-based proteomics, which uses high-resolution hybrid Mass spectrometers such as the quadrupole-orbitrap Mass spectrometer, can yield tens of thousands of tandem Mass (MS/MS) spectra of high resolution during a routine bottom-up experiment. Despite being a fundamental and key step in MS-based proteomics, the accurate determination and assignment of precursor Monoisotopic Masses to the MS/MS spectra remains difficult. The difficulties stem from imperfect isotopic envelopes of precursor ions, inaccurate charge states for precursor ions, and cofragmentation. We describe a composite method of utilizing MS data to assign accurate Monoisotopic Masses to MS/MS spectra, including those subject to cofragmentation. The method, “multiplexed post-experiment Monoisotopic Mass refinement” (mPE-MMR), consists of the following: multiplexing of precursor Masses to assign multiple Monoisotopic Masses of cofragmented peptides to the corresponding multiplexed MS/MS spectra, multiplexing of charge states ...
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postexperiment Monoisotopic Mass filtering and refinement pe mmr of tandem Mass spectrometric data increases accuracy of peptide identification in lc ms ms
Molecular & Cellular Proteomics, 2008Co-Authors: Byunghee Shin, Hee Jung Jung, Hokeun Kim, Seok Won Hyung, Dongkyu Lee, Cheolju Lee, Sang Won LeeAbstract:Methods for treating MS/MS data to achieve accurate peptide identification are currently the subject of much research activity. In this study we describe a new method for filtering MS/MS data and refining precursor Masses that provides highly accurate analyses of Massive sets of proteomics data. This method, coined "postexperiment Monoisotopic Mass filtering and refinement" (PE-MMR), consists of several data processing steps: 1) generation of lists of all Monoisotopic Masses observed in a whole LC/MS experiment, 2) clusterization of Monoisotopic Masses of a peptide into unique Mass classes (UMCs) based on their Masses and LC elution times, 3) matching the precursor Masses of the MS/MS data to a representative Mass of a UMC, and 4) filtration of the MS/MS data based on the presence of corresponding Monoisotopic Masses and refinement of the precursor ion Masses by the UMC Mass. PE-MMR increases the throughput of proteomics data analysis, by efficiently removing "garbage" MS/MS data prior to database searching, and improves the Mass measurement accuracies (i.e. 0.05 +/- 1.49 ppm for yeast data (from 4.46 +/- 2.81 ppm) and 0.03 +/- 3.41 ppm for glycopeptide data (from 4.8 +/- 7.4 ppm)) for an increased number of identified peptides. In proteomics analyses of glycopeptide-enriched samples, PE-MMR processing greatly reduces the degree of false glycopeptide identification by correctly assigning the Monoisotopic Masses for the precursor ions prior to database searching. By applying this technique to analyses of proteome samples of varying complexities, we demonstrate herein that PE-MMR is an effective and accurate method for treating Massive sets of proteomics data.
Hokeun Kim - One of the best experts on this subject based on the ideXlab platform.
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Multiplexed Post-Experimental Monoisotopic Mass Refinement (mPE-MMR) to Increase Sensitivity and Accuracy in Peptide Identifications from Tandem Mass Spectra of Cofragmentation
Analytical chemistry, 2016Co-Authors: Inamul Hasan Madar, Richard D Smith, Hokeun Kim, Dong Gi Mun, Sangtae Kim, Sang Won LeeAbstract:Mass spectrometry (MS)-based proteomics, which uses high-resolution hybrid Mass spectrometers such as the quadrupole-orbitrap Mass spectrometer, can yield tens of thousands of tandem Mass (MS/MS) spectra of high resolution during a routine bottom-up experiment. Despite being a fundamental and key step in MS-based proteomics, the accurate determination and assignment of precursor Monoisotopic Masses to the MS/MS spectra remains difficult. The difficulties stem from imperfect isotopic envelopes of precursor ions, inaccurate charge states for precursor ions, and cofragmentation. We describe a composite method of utilizing MS data to assign accurate Monoisotopic Masses to MS/MS spectra, including those subject to cofragmentation. The method, “multiplexed post-experiment Monoisotopic Mass refinement” (mPE-MMR), consists of the following: multiplexing of precursor Masses to assign multiple Monoisotopic Masses of cofragmented peptides to the corresponding multiplexed MS/MS spectra, multiplexing of charge states ...
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integrated post experiment Monoisotopic Mass refinement an integrated approach to accurately assign Monoisotopic precursor Masses to tandem Mass spectrometric data
Analytical Chemistry, 2010Co-Authors: Hee Jung Jung, Samuel O Purvine, Matthew E Monroe, Hokeun Kim, Vladislav A Petyuk, Seok Won Hyung, Dong Gi Mun, Kyong Chul Kim, Jongmoon Park, Sujin KimAbstract:Accurate assignment of Monoisotopic precursor Masses to tandem Mass spectrometric (MS/MS) data is a fundamental and critically important step for successful peptide identifications in Mass spectrometry based proteomics. Here we describe an integrated approach that combines three previously reported methods of treating MS/MS data for precursor Mass refinement. This combined method, “integrated post-experiment Monoisotopic Mass refinement” (iPE-MMR), integrates steps (1) generation of refined MS/MS data by DeconMSn; (2) additional refinement of the resultant MS/MS data by a modified version of PE-MMR; and (3) elimination of systematic errors of precursor Masses using DtaRefinery. iPE-MMR is the first method that utilizes all MS information from multiple MS scans of a precursor ion including multiple charge states, in an MS scan, to determine precursor Mass. With the combination of these methods, iPE-MMR increases sensitivity in peptide identification and provides increased accuracy when applied to complex h...
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postexperiment Monoisotopic Mass filtering and refinement pe mmr of tandem Mass spectrometric data increases accuracy of peptide identification in lc ms ms
Molecular & Cellular Proteomics, 2008Co-Authors: Byunghee Shin, Hee Jung Jung, Hokeun Kim, Seok Won Hyung, Dongkyu Lee, Cheolju Lee, Sang Won LeeAbstract:Methods for treating MS/MS data to achieve accurate peptide identification are currently the subject of much research activity. In this study we describe a new method for filtering MS/MS data and refining precursor Masses that provides highly accurate analyses of Massive sets of proteomics data. This method, coined "postexperiment Monoisotopic Mass filtering and refinement" (PE-MMR), consists of several data processing steps: 1) generation of lists of all Monoisotopic Masses observed in a whole LC/MS experiment, 2) clusterization of Monoisotopic Masses of a peptide into unique Mass classes (UMCs) based on their Masses and LC elution times, 3) matching the precursor Masses of the MS/MS data to a representative Mass of a UMC, and 4) filtration of the MS/MS data based on the presence of corresponding Monoisotopic Masses and refinement of the precursor ion Masses by the UMC Mass. PE-MMR increases the throughput of proteomics data analysis, by efficiently removing "garbage" MS/MS data prior to database searching, and improves the Mass measurement accuracies (i.e. 0.05 +/- 1.49 ppm for yeast data (from 4.46 +/- 2.81 ppm) and 0.03 +/- 3.41 ppm for glycopeptide data (from 4.8 +/- 7.4 ppm)) for an increased number of identified peptides. In proteomics analyses of glycopeptide-enriched samples, PE-MMR processing greatly reduces the degree of false glycopeptide identification by correctly assigning the Monoisotopic Masses for the precursor ions prior to database searching. By applying this technique to analyses of proteome samples of varying complexities, we demonstrate herein that PE-MMR is an effective and accurate method for treating Massive sets of proteomics data.
Alan G Marshall - One of the best experts on this subject based on the ideXlab platform.
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elemental composition validation from stored waveform inverse fourier transform swift isolation ft icr ms isotopic fine structure
Journal of the American Society for Mass Spectrometry, 2013Co-Authors: Brian M Ruddy, Gregory T Blakney, Ryan P Rodgers, Christopher L Hendrickson, Alan G MarshallAbstract:Elemental composition assignment confidence in Mass spectrometry is typically assessed by Monoisotopic Mass accuracy. For a given Mass accuracy, resolution and detection of other isotopologues can further narrow the number of possible elemental compositions. However, such measurements require ultrahigh resolving power and high dynamic range, particularly for compounds containing low numbers of nitrogen and oxygen (both 15N and 18O occur at less than 0.4 % natural abundance). Here, we demonstrate validation of molecular formula assignment from isotopic fine structure, based on ultrahigh resolution broadband Fourier transform ion cyclotron resonance Mass spectrometry (FT-ICR MS). Dynamic range is enhanced by external quadrupole and internal stored waveform inverse Fourier transform (SWIFT) isolation to facilitate detection of low abundance heavy atom isotopologues.
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counting individual sulfur atoms in a protein by ultrahigh resolution fourier transform ion cyclotron resonance Mass spectrometry experimental resolution of isotopic fine structure in proteins
Proceedings of the National Academy of Sciences of the United States of America, 1998Co-Authors: Stone D H Shi, Christopher L Hendrickson, Alan G MarshallAbstract:A typical molecular ion Mass spectrum consists of a sum of signals from species of various possible isotopic compositions. Only the Monoisotopic peak (e.g., all carbons are 12C; all nitrogens are 14N, etc.) has a unique elemental composition. Every other isotope peak at approximately integer multiples of ∼1 Da higher in nominal Mass represents a sum of contributions from isotope combinations differing by a few mDa (e.g., two 13C vs. two 15N vs. one 13C and one 15N vs. 34S, vs. 18O, etc., at ∼2 Da higher in Mass than the Monoisotopic Mass). At sufficiently high Mass resolving power, each of these nominal-Mass peaks resolves into its isotopic fine structure. Here, we report resolution of the isotopic fine structure of proteins up to 15.8 kDa (isotopic 13C,15N doubly depleted tumor suppressor protein, p16), made possible by electrospray ionization followed by ultrahigh-resolution Fourier transform ion cyclotron resonance Mass analysis at 9.4 tesla. Further, a resolving power of m/Δm50% ≈8,000,000 has been achieved on bovine ubiquitin (8.6 kDa). These results represent a 10-fold increase in the highest Mass at which isotopic fine structure previously had been observed. Finally, because isotopic fine structure reveals elemental composition directly, it can be used to confirm or determine molecular formula. For p16, for example, we were able to determine (5.1 ± 0.3) the correct number (five) of sulfur atoms solely from the abundance ratio of the resolved 34S peak to the Monoisotopic peak.
Hee Jung Jung - One of the best experts on this subject based on the ideXlab platform.
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integrated post experiment Monoisotopic Mass refinement an integrated approach to accurately assign Monoisotopic precursor Masses to tandem Mass spectrometric data
Analytical Chemistry, 2010Co-Authors: Hee Jung Jung, Samuel O Purvine, Matthew E Monroe, Hokeun Kim, Vladislav A Petyuk, Seok Won Hyung, Dong Gi Mun, Kyong Chul Kim, Jongmoon Park, Sujin KimAbstract:Accurate assignment of Monoisotopic precursor Masses to tandem Mass spectrometric (MS/MS) data is a fundamental and critically important step for successful peptide identifications in Mass spectrometry based proteomics. Here we describe an integrated approach that combines three previously reported methods of treating MS/MS data for precursor Mass refinement. This combined method, “integrated post-experiment Monoisotopic Mass refinement” (iPE-MMR), integrates steps (1) generation of refined MS/MS data by DeconMSn; (2) additional refinement of the resultant MS/MS data by a modified version of PE-MMR; and (3) elimination of systematic errors of precursor Masses using DtaRefinery. iPE-MMR is the first method that utilizes all MS information from multiple MS scans of a precursor ion including multiple charge states, in an MS scan, to determine precursor Mass. With the combination of these methods, iPE-MMR increases sensitivity in peptide identification and provides increased accuracy when applied to complex h...
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postexperiment Monoisotopic Mass filtering and refinement pe mmr of tandem Mass spectrometric data increases accuracy of peptide identification in lc ms ms
Molecular & Cellular Proteomics, 2008Co-Authors: Byunghee Shin, Hee Jung Jung, Hokeun Kim, Seok Won Hyung, Dongkyu Lee, Cheolju Lee, Sang Won LeeAbstract:Methods for treating MS/MS data to achieve accurate peptide identification are currently the subject of much research activity. In this study we describe a new method for filtering MS/MS data and refining precursor Masses that provides highly accurate analyses of Massive sets of proteomics data. This method, coined "postexperiment Monoisotopic Mass filtering and refinement" (PE-MMR), consists of several data processing steps: 1) generation of lists of all Monoisotopic Masses observed in a whole LC/MS experiment, 2) clusterization of Monoisotopic Masses of a peptide into unique Mass classes (UMCs) based on their Masses and LC elution times, 3) matching the precursor Masses of the MS/MS data to a representative Mass of a UMC, and 4) filtration of the MS/MS data based on the presence of corresponding Monoisotopic Masses and refinement of the precursor ion Masses by the UMC Mass. PE-MMR increases the throughput of proteomics data analysis, by efficiently removing "garbage" MS/MS data prior to database searching, and improves the Mass measurement accuracies (i.e. 0.05 +/- 1.49 ppm for yeast data (from 4.46 +/- 2.81 ppm) and 0.03 +/- 3.41 ppm for glycopeptide data (from 4.8 +/- 7.4 ppm)) for an increased number of identified peptides. In proteomics analyses of glycopeptide-enriched samples, PE-MMR processing greatly reduces the degree of false glycopeptide identification by correctly assigning the Monoisotopic Masses for the precursor ions prior to database searching. By applying this technique to analyses of proteome samples of varying complexities, we demonstrate herein that PE-MMR is an effective and accurate method for treating Massive sets of proteomics data.
Dong Gi Mun - One of the best experts on this subject based on the ideXlab platform.
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Multiplexed Post-Experimental Monoisotopic Mass Refinement (mPE-MMR) to Increase Sensitivity and Accuracy in Peptide Identifications from Tandem Mass Spectra of Cofragmentation
Analytical chemistry, 2016Co-Authors: Inamul Hasan Madar, Richard D Smith, Hokeun Kim, Dong Gi Mun, Sangtae Kim, Sang Won LeeAbstract:Mass spectrometry (MS)-based proteomics, which uses high-resolution hybrid Mass spectrometers such as the quadrupole-orbitrap Mass spectrometer, can yield tens of thousands of tandem Mass (MS/MS) spectra of high resolution during a routine bottom-up experiment. Despite being a fundamental and key step in MS-based proteomics, the accurate determination and assignment of precursor Monoisotopic Masses to the MS/MS spectra remains difficult. The difficulties stem from imperfect isotopic envelopes of precursor ions, inaccurate charge states for precursor ions, and cofragmentation. We describe a composite method of utilizing MS data to assign accurate Monoisotopic Masses to MS/MS spectra, including those subject to cofragmentation. The method, “multiplexed post-experiment Monoisotopic Mass refinement” (mPE-MMR), consists of the following: multiplexing of precursor Masses to assign multiple Monoisotopic Masses of cofragmented peptides to the corresponding multiplexed MS/MS spectra, multiplexing of charge states ...
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integrated post experiment Monoisotopic Mass refinement an integrated approach to accurately assign Monoisotopic precursor Masses to tandem Mass spectrometric data
Analytical Chemistry, 2010Co-Authors: Hee Jung Jung, Samuel O Purvine, Matthew E Monroe, Hokeun Kim, Vladislav A Petyuk, Seok Won Hyung, Dong Gi Mun, Kyong Chul Kim, Jongmoon Park, Sujin KimAbstract:Accurate assignment of Monoisotopic precursor Masses to tandem Mass spectrometric (MS/MS) data is a fundamental and critically important step for successful peptide identifications in Mass spectrometry based proteomics. Here we describe an integrated approach that combines three previously reported methods of treating MS/MS data for precursor Mass refinement. This combined method, “integrated post-experiment Monoisotopic Mass refinement” (iPE-MMR), integrates steps (1) generation of refined MS/MS data by DeconMSn; (2) additional refinement of the resultant MS/MS data by a modified version of PE-MMR; and (3) elimination of systematic errors of precursor Masses using DtaRefinery. iPE-MMR is the first method that utilizes all MS information from multiple MS scans of a precursor ion including multiple charge states, in an MS scan, to determine precursor Mass. With the combination of these methods, iPE-MMR increases sensitivity in peptide identification and provides increased accuracy when applied to complex h...