Overview of software options for processing, analysis and interpretation of mass spectrometric proteomic data

被引:5
|
作者
Haga, Steve. W. [1 ]
Wu, Hui-Fen [2 ,3 ,4 ,5 ,6 ,7 ]
机构
[1] Natl Sun Yat Sen Univ, Dept Comp Sci & Engn, Kaohsiung 804, Taiwan
[2] Natl Sun Yat Sen Univ, Dept Chem, Kaohsiung 804, Taiwan
[3] Kaohsiung Med Univ, Sch Pharm, Coll Pharm, Kaohsiung 807, Taiwan
[4] Natl Sun Yat Sen Univ, Ctr Nanosci & Nanotechnol, Kaohsiung 804, Taiwan
[5] Natl Sun Yat Sen Univ, Doctoral Degree Program Marine Biotechnol, Kaohsiung 804, Taiwan
[6] Acad Sinica, Kaohsiung 804, Taiwan
[7] Natl Sun Yat Sen Univ, Inst Med Sci & Technol, Kaohsiung 804, Taiwan
来源
JOURNAL OF MASS SPECTROMETRY | 2014年 / 49卷 / 10期
关键词
proteins; MS; biocomputation; high throughput analysis; software programs; PROTEIN-PROTEIN INTERACTIONS; AMINO-ACID-SEQUENCES; COMPREHENSIVE ANALYSIS; COMPUTATIONAL METHODS; IDENTIFICATION; PEPTIDES; INFORMATION; DATABASES; SPECTRA; TOOLS;
D O I
10.1002/jms.3414
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Recently, the interests in proteomics have been intensively increased, and the proteomic methods have been widely applied to many problems in cell biology. If the age of 1990s is considered to be a decade of genomics, we can claim that the following years of the new century is a decade of proteomics. The rapid evolution of proteomics has continued through these years, with a series of innovations in separation techniques and the core technologies of two-dimensional gel electrophoresis and MS. Both technologies are fueled by automation and high throughput computation for profiling of proteins from biological systems. As Patterson ever mentioned, data analysis is the Achilles heel of proteomics and our ability to generate data now outstrips our ability to analyze it'. The development of automatic and high throughput technologies for rapid identification of proteins is essential for large-scale proteome projects and automatic protein identification and characterization is essential for high throughput proteomics. This review provides a snap shot of the tools and applications that are available for mass spectrometric high throughput biocomputation. The review starts with a brief introduction of proteomics and MS. Computational tools that can be employed at various stages of analysis are presented, including that for data processing, identification, quantification, and the understanding of the biological functions of individual proteins and their dynamic interactions. The challenges of computation software development and its future trends in MS-based proteomics have also been speculated. Copyright (c) 2014 John Wiley & Sons, Ltd.
引用
收藏
页码:959 / 969
页数:11
相关论文
共 50 条
  • [1] UTILITY OF A COMPUTER IN ACQUISITION, PROCESSING AND INTERPRETATION OF MASS SPECTROMETRIC DATA
    BIEMANN, K
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 1971, (NSEP): : 4 - &
  • [2] Software tools for analysis of mass spectrometric lipidome data
    Haimi, Perttu
    Uphoff, Andreas
    Hermansson, Martin
    Somerharju, Pentti
    ANALYTICAL CHEMISTRY, 2006, 78 (24) : 8324 - 8331
  • [3] Software utilities for the interpretation of mass spectrometric data of glycoconjugates: application to glycosphingolipids of human serum
    Souady, Jamal
    Dadimov, Denis
    Kirsch, Stephan
    Bindila, Laura
    Peter-Katalinic, Jasna
    Vakhrushev, Sergey Y.
    RAPID COMMUNICATIONS IN MASS SPECTROMETRY, 2010, 24 (07) : 1039 - 1048
  • [4] Desktop prediction/analysis of mass spectrometric data in proteomic projects by using massXpert
    Rusconi, F
    Belghazi, M
    BIOINFORMATICS, 2002, 18 (04) : 644 - 645
  • [5] PythoMS: A Python']Python Framework To Simplify and Assist in the Processing and Interpretation of Mass Spectrometric Data
    Yunker, Lars P. E.
    Donnecke, Sofia
    Ting, Michelle
    Yeung, Darien
    McIndoe, J. Scott
    JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2019, 59 (04) : 1295 - 1300
  • [6] Software innovations in four-dimensional mass spectrometric data analysis
    Cox, Jürgen
    Kruppa, Gary
    Spectroscopy Europe, 2020, 32 (06): : 14 - 17
  • [7] Software development for mass spectrometric analysis
    Hart, KJ
    RAPID COMMUNICATIONS IN MASS SPECTROMETRY, 1996, 10 (03) : 393 - 398
  • [8] Mass Spectrometric Proteomic Analysis of Human Glaucomatous Retinae
    Funke, Sebastian
    Perumal, Natarajan
    Beck, Sabine
    Gabel-Scheurich, Silke
    Schmelter, Carsten
    Gerbig, Claudia
    Gramlich, Oliver
    Pfeiffer, Norbert
    Grus, Franz H.
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2015, 56 (07)
  • [9] Bioinformatic methods to exploit mass spectrometric data for proteomic applications
    Chalkley, RJ
    Hansen, KC
    Baldwin, MA
    BIOLOGICAL MASS SPECTROMETRY, 2005, 402 : 289 - 312
  • [10] Software tool for automated processing of 13C labeling data from mass spectrometric spectra
    Talwar, P
    Wittmann, C
    Lengauer, T
    Heinzle, E
    BIOTECHNIQUES, 2003, 35 (06) : 1214 - 1215