Literature DB >> 18351753

Two-dimensional correlation optimized warping algorithm for aligning GC x GC-MS data.

Dabao Zhang1, Xiaodong Huang, Fred E Regnier, Min Zhang.   

Abstract

A two-dimensional (2-D) correlation optimized warping (COW) algorithm has been developed to align 2-D gas chromatography coupled with time-of-flight mass spectrometry (GC x GC/TOF-MS) data. By partitioning raw chromatographic profiles and warping the grid points simultaneously along the first and second dimensions on the basis of applying a one-dimensional COW algorithm to characteristic vectors, nongrid points can be interpolatively warped. This 2-D algorithm was directly applied to total ion counts (TIC) chromatographic profiles of homogeneous chemical samples, i.e., samples including mostly identical compounds. For heterogeneous chemical samples, the 2-D algorithm is first applied to certain selected ion counts chromatographic profiles, and the resultant warping parameters are then used to warp the corresponding TIC chromatographic profiles. The developed 2-D COW algorithm can also be applied to align other 2-D separation images, e.g., LC x LC data, LC x GC data, GC x GC data, LC x CE data, and CE x CE data.

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Year:  2008        PMID: 18351753     DOI: 10.1021/ac7024317

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  13 in total

1.  DISCO: distance and spectrum correlation optimization alignment for two-dimensional gas chromatography time-of-flight mass spectrometry-based metabolomics.

Authors:  Bing Wang; Aiqin Fang; John Heim; Bogdan Bogdanov; Scott Pugh; Mark Libardoni; Xiang Zhang
Journal:  Anal Chem       Date:  2010-06-15       Impact factor: 6.986

2.  An optimal peak alignment for comprehensive two-dimensional gas chromatography mass spectrometry using mixture similarity measure.

Authors:  Seongho Kim; Aiqin Fang; Bing Wang; Jaesik Jeong; Xiang Zhang
Journal:  Bioinformatics       Date:  2011-04-14       Impact factor: 6.937

3.  Semi-automated alignment and quantification of peaks using parallel factor analysis for comprehensive two-dimensional liquid chromatography-diode array detector data sets.

Authors:  Robert C Allen; Sarah C Rutan
Journal:  Anal Chim Acta       Date:  2012-02-19       Impact factor: 6.558

4.  MetPP: a computational platform for comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry-based metabolomics.

Authors:  Xiaoli Wei; Xue Shi; Imhoi Koo; Seongho Kim; Robin H Schmidt; Gavin E Arteel; Walter H Watson; Craig McClain; Xiang Zhang
Journal:  Bioinformatics       Date:  2013-05-11       Impact factor: 6.937

Review 5.  Recent applications of chemometrics in one- and two-dimensional chromatography.

Authors:  Tijmen S Bos; Wouter C Knol; Stef R A Molenaar; Leon E Niezen; Peter J Schoenmakers; Govert W Somsen; Bob W J Pirok
Journal:  J Sep Sci       Date:  2020-03-19       Impact factor: 3.645

6.  Coherent Point Drift Peak Alignment Algorithms Using Distance and Similarity Measures for Two-Dimensional Gas Chromatography Mass Spectrometry Data.

Authors:  Zeyu Li; Seongho Kim; Sikai Zhong; Zichun Zhong; Ikuko Kato; Xiang Zhang
Journal:  J Chemom       Date:  2020-03-28       Impact factor: 2.467

7.  Comprehensive Two-Dimensional Gas Chromatography Mass Spectrometry-Based Metabolomics.

Authors:  Md Aminul Islam Prodhan; Craig McClain; Xiang Zhang
Journal:  Adv Exp Med Biol       Date:  2021       Impact factor: 2.622

8.  Global peak alignment for comprehensive two-dimensional gas chromatography mass spectrometry using point matching algorithms.

Authors:  Beichuan Deng; Seongho Kim; Hengguang Li; Elisabeth Heath; Xiang Zhang
Journal:  J Bioinform Comput Biol       Date:  2016-09-09       Impact factor: 1.122

9.  Smith-Waterman peak alignment for comprehensive two-dimensional gas chromatography-mass spectrometry.

Authors:  Seongho Kim; Imhoi Koo; Aiqin Fang; Xiang Zhang
Journal:  BMC Bioinformatics       Date:  2011-06-15       Impact factor: 3.169

10.  An efficient post-hoc integration method improving peak alignment of metabolomics data from GCxGC/TOF-MS.

Authors:  Jaesik Jeong; Xiang Zhang; Xue Shi; Seongho Kim; Changyu Shen
Journal:  BMC Bioinformatics       Date:  2013-04-10       Impact factor: 3.169

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