Literature DB >> 18297649

Alignment of LC-MS images, with applications to biomarker discovery and protein identification.

Mathias Vandenbogaert1, Sébastien Li-Thiao-Té, Hans-Michael Kaltenbach, Runxuan Zhang, Tero Aittokallio, Benno Schwikowski.   

Abstract

LC-MS-based approaches have gained considerable interest for the analysis of complex peptide or protein mixtures, due to their potential for full automation and high sampling rates. Advances in resolution and accuracy of modern mass spectrometers allow new analytical LC-MS-based applications, such as biomarker discovery and cross-sample protein identification. Many of these applications compare multiple LC-MS experiments, each of which can be represented as a 2-D image. In this article, we survey current approaches to LC-MS image alignment. LC-MS image alignment corrects for experimental variations in the chromatography and represents a computational key technology for the comparison of LC-MS experiments. It is a required processing step for its two major applications: biomarker discovery and protein identification. Along with descriptions of the computational analysis approaches, we discuss their relative merits and potential pitfalls.

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Year:  2008        PMID: 18297649     DOI: 10.1002/pmic.200700791

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  19 in total

1.  Retention time alignment of LC/MS data by a divide-and-conquer algorithm.

Authors:  Zhongqi Zhang
Journal:  J Am Soc Mass Spectrom       Date:  2012-04       Impact factor: 3.109

2.  Warpgroup: increased precision of metabolomic data processing by consensus integration bound analysis.

Authors:  Nathaniel G Mahieu; Jonathan L Spalding; Gary J Patti
Journal:  Bioinformatics       Date:  2015-09-30       Impact factor: 6.937

Review 3.  Quantitative strategies to fuel the merger of discovery and hypothesis-driven shotgun proteomics.

Authors:  Kelli G Kline; Greg L Finney; Christine C Wu
Journal:  Brief Funct Genomic Proteomic       Date:  2009-03

4.  Profile-Based LC-MS data alignment--a Bayesian approach.

Authors:  Tsung-Heng Tsai; Mahlet G Tadesse; Yue Wang; Habtom W Ressom
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2013 Mar-Apr       Impact factor: 3.710

5.  Multi-profile Bayesian alignment model for LC-MS data analysis with integration of internal standards.

Authors:  Tsung-Heng Tsai; Mahlet G Tadesse; Cristina Di Poto; Lewis K Pannell; Yehia Mechref; Yue Wang; Habtom W Ressom
Journal:  Bioinformatics       Date:  2013-09-06       Impact factor: 6.937

Review 6.  Image analysis tools and emerging algorithms for expression proteomics.

Authors:  Andrew W Dowsey; Jane A English; Frederique Lisacek; Jeffrey S Morris; Guang-Zhong Yang; Michael J Dunn
Journal:  Proteomics       Date:  2010-12       Impact factor: 3.984

7.  A Bayesian approach to the alignment of mass spectra.

Authors:  Xiaoxiao Kong; Cavan Reilly
Journal:  Bioinformatics       Date:  2009-10-09       Impact factor: 6.937

Review 8.  Mass Spectrometry-based Metabolomics in Translational Research.

Authors:  Su Jung Kim; Ha Eun Song; Hyo Yeong Lee; Hyun Ju Yoo
Journal:  Adv Exp Med Biol       Date:  2021       Impact factor: 2.622

Review 9.  Tools for label-free peptide quantification.

Authors:  Sven Nahnsen; Chris Bielow; Knut Reinert; Oliver Kohlbacher
Journal:  Mol Cell Proteomics       Date:  2012-12-17       Impact factor: 5.911

10.  An adaptive alignment algorithm for quality-controlled label-free LC-MS.

Authors:  Marianne Sandin; Ashfaq Ali; Karin Hansson; Olle Månsson; Erik Andreasson; Svante Resjö; Fredrik Levander
Journal:  Mol Cell Proteomics       Date:  2013-01-09       Impact factor: 5.911

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