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Mass spectrometry-based proteomics

Author

Listed:
  • Ruedi Aebersold

    (Institute for Systems Biology)

  • Matthias Mann

    (Center for Experimental BioInformatics(CEBI), University of Southern Denmark)

Abstract

Recent successes illustrate the role of mass spectrometry-based proteomics as an indispensable tool for molecular and cellular biology and for the emerging field of systems biology. These include the study of protein–protein interactions via affinity-based isolations on a small and proteome-wide scale, the mapping of numerous organelles, the concurrent description of the malaria parasite genome and proteome, and the generation of quantitative protein profiles from diverse species. The ability of mass spectrometry to identify and, increasingly, to precisely quantify thousands of proteins from complex samples can be expected to impact broadly on biology and medicine.

Suggested Citation

  • Ruedi Aebersold & Matthias Mann, 2003. "Mass spectrometry-based proteomics," Nature, Nature, vol. 422(6928), pages 198-207, March.
    • Handle: RePEc:nat:nature:v:422:y:2003:i:6928:d:10.1038_nature01511
    DOI: 10.1038/nature01511
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    1. Kertcher, Zack & Venkatraman, Rohan & Coslor, Erica, 2020. "Pleasingly parallel: Early cross-disciplinary work for innovation diffusion across boundaries in grid computing," Journal of Business Research, Elsevier, vol. 116(C), pages 581-594.
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    3. Karsten Suhre & Guhan Ram Venkataraman & Harendra Guturu & Anna Halama & Nisha Stephan & Gaurav Thareja & Hina Sarwath & Khatereh Motamedchaboki & Margaret K. R. Donovan & Asim Siddiqui & Serafim Batz, 2024. "Nanoparticle enrichment mass-spectrometry proteomics identifies protein-altering variants for precise pQTL mapping," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
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    11. Wei Feng & Joanne C. Beer & Qinyu Hao & Ishara S. Ariyapala & Aparna Sahajan & Andrei Komarov & Katie Cha & Mason Moua & Xiaolei Qiu & Xiaomei Xu & Shweta Iyengar & Thu Yoshimura & Rajini Nagaraj & Li, 2023. "NULISA: a proteomic liquid biopsy platform with attomolar sensitivity and high multiplexing," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    12. ?uksza Marta & Kluge Bogus?aw & Ostrowski Jerzy & Karczmarski Jakub & Gambin Anna, 2009. "Two-Stage Model-Based Clustering for Liquid Chromatography Mass Spectrometry Data Analysis," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-36, February.
    13. Kong Ao & Azencott Robert, 2017. "Binary Markov Random Fields and interpretable mass spectra discrimination," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 16(1), pages 13-30, March.
    14. Tianhai Tian & Jiangning Song, 2012. "Mathematical Modelling of the MAP Kinase Pathway Using Proteomic Datasets," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-12, August.
    15. Benjamin A Shoemaker & Anna R Panchenko, 2007. "Deciphering Protein–Protein Interactions. Part II. Computational Methods to Predict Protein and Domain Interaction Partners," PLOS Computational Biology, Public Library of Science, vol. 3(4), pages 1-7, April.
    16. Mertens, B.J.A. & van der Burgt, Y.E.M. & Velstra, B. & Mesker, W.E. & Tollenaar, R.A.E.M. & Deelder, A.M., 2011. "On the use of double cross-validation for the combination of proteomic mass spectral data for enhanced diagnosis and prediction," Statistics & Probability Letters, Elsevier, vol. 81(7), pages 759-766, July.
    17. Alexander Kaever & Manuel Landesfeind & Kirstin Feussner & Burkhard Morgenstern & Ivo Feussner & Peter Meinicke, 2014. "Meta-Analysis of Pathway Enrichment: Combining Independent and Dependent Omics Data Sets," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-12, February.
    18. Dayle L Sampson & Tony J Parker & Zee Upton & Cameron P Hurst, 2011. "A Comparison of Methods for Classifying Clinical Samples Based on Proteomics Data: A Case Study for Statistical and Machine Learning Approaches," PLOS ONE, Public Library of Science, vol. 6(9), pages 1-11, September.
    19. Guler, Arzu Tugce & Waaijer, Cathelijn J.F. & Mohammed, Yassene & Palmblad, Magnus, 2016. "Automating bibliometric analyses using Taverna scientific workflows: A tutorial on integrating Web Services," Journal of Informetrics, Elsevier, vol. 10(3), pages 830-841.
    20. Lei Xin & Rui Qiao & Xin Chen & Hieu Tran & Shengying Pan & Sahar Rabinoviz & Haibo Bian & Xianliang He & Brenton Morse & Baozhen Shan & Ming Li, 2022. "A streamlined platform for analyzing tera-scale DDA and DIA mass spectrometry data enables highly sensitive immunopeptidomics," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    21. Jiang Tan & Hui-Zhen Fu & Yuh-Shan Ho, 2014. "A bibliometric analysis of research on proteomics in Science Citation Index Expanded," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 1473-1490, February.
    22. Stephan Krueger & Patrick Giavalisco & Leonard Krall & Marie-Caroline Steinhauser & Dirk Büssis & Bjoern Usadel & Ulf-Ingo Flügge & Alisdair R Fernie & Lothar Willmitzer & Dirk Steinhauser, 2011. "A Topological Map of the Compartmentalized Arabidopsis thaliana Leaf Metabolome," PLOS ONE, Public Library of Science, vol. 6(3), pages 1-16, March.
    23. Yun Xu & Wolfgang Schrader, 2021. "Studying the Complexity of Biomass Derived Biofuels," Energies, MDPI, vol. 14(8), pages 1-13, April.

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