Future Prospects of Spectral Clustering Approaches in Proteomics. Issue 14 (30th July 2018)

• Record Type: Journal Article
• Authors: Perez‐Riverol, Yasset; Vizcaíno, Juan Antonio; Griss, Johannes
• Is Part Of: Proteomics. Volume 18:Issue 14(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-07-30
• Subjects: algorithms -- computational proteomics -- mass spectrometry -- spectral clustering; Proteins -- Separation -- Periodicals; Bioinformatics -- Periodicals; Proteomics -- Periodicals; Genomes -- Periodicals; Molecular genetics -- Periodicals; 572.605
• DOI: 10.1002/pmic.201700454
• Languages: English
• ISSNs: 1615-9853

Abstract

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.