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Proteomics. 2018 Jul;18(14):e1700454. doi: 10.1002/pmic.201700454.

Future Prospects of Spectral Clustering Approaches in Proteomics.

Author information

1
European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
2
Division of Immunology, Allergy and Infectious Diseases, Department of Dermatology, Medical University of Vienna, 1090, Vienna, Austria.

Abstract

In this article, current and future applications of spectral clustering are discussed in the context of mass spectrometry-based proteomics approaches. First of all, the main algorithms and tools that can currently be used to perform spectral clustering are introduced. In addition, its main applications and their use in current computational proteomics workflows are explained, including the generation of spectral libraries and spectral archives. Finally, possible future directions for spectral clustering, including its potential use to achieve a deeper coverage of the proteome and the discovery of novel post-translational modifications and single amino acid variants.

KEYWORDS:

algorithms; computational proteomics; mass spectrometry; spectral clustering

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