Special Issue: Computational Proteomics
This special issue of Briefings in Bioinformatics was guest edited by Mario Cannataro. It focuses on the overall knowledge discovery process behind computational proteomics, with special emphasis on machine learning methods, spectra data handling, biomarker discovery, standard-based and quality-aware management of proteomics experiments. This special issue will be of interest to bioinformaticians, mass spectrometrists working on proteomics, clinical proteomic researchers, and machine learning researchers.
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Table of Contents
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Computational proteomics: management and analysis of proteomics data
Mario Cannataro
Approaches to dimensionality reduction in proteomic biomarker studies
Melanie Hilario and Alexandros Kalousis
Machine learning methods for predictive proteomics
Annalisa Barla, Giuseppe Jurman, Samantha Riccadonna, Stefano Merler, Marco Chierici, and Cesare Furlanello
Classification of mass-spectrometric data in clinical proteomics using learning vector quantization methods
Thomas Villmann, Frank-Michael Schleif, Markus Kostrzewa, Axel Walch, and Barbara Hammer
Algorithms and tools for analysis and management of mass spectrometry data
Pierangelo Veltri
Computational methods for the comparative quantification of proteins in label-free LCn-MS experiments
Jason W. H. Wong, Matthew J. Sullivan, and Gerard Cagney
The HUPO proteomics standards initiative—easing communication and minimizing data loss in a changing world
Sandra Orchard and Henning Hermjakob
Information quality in proteomics
David A. Stead, Norman W. Paton, Paolo Missier, Suzanne M. Embury, Cornelia Hedeler, Binling Jin, Alistair J. P. Brown, and Alun Preece