of scientific software for biological data in general, and proteomics ... objective is to illustrate that many tools and visualization techniques are available to help ... visual analytics approaches and their concrete application in the case of ...
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Proteomics 2015, 15, 1339–1340
Editorial Proteomics Data Visualisation Recent advances in high-throughput experimental techniques have led to an exponential increase in both the size and the complexity of biological datasets. Proteomics data can be of varied origin, including datasets coming from high-throughput mass spectrometry-based approaches, large sets of molecular interaction data, and protein structures. The development of scientific software for biological data in general, and proteomics approaches in particular, has evolved enormously in recent years. Data visualisation has moved from being a secondary focus to being one of the key elements to facilitate the understanding, interpretation and validation of the data, and to improve the usability of the software. In addition, visualisation is of paramount importance as a way of communicating data to a broad audience. This Special Issue on ‘Proteomics Data Visualisation’ comprises a total of twelve valuable contributions from experts in the field. The articles of this Special Issue are organized in three sections, which serve to aggregate the contributions according to the manuscript type, namely reviews, research articles and technical briefs. The first section of the Special Issue includes five review articles, which summarize the current knowledge on different aspects of data visualization. The first review (by Oveland et al.) is aimed at a large audience and provides an overview of the different ways in which proteomics software supports the visualization and interpretation of proteomics data. The objective is to illustrate that many tools and visualization techniques are available to help scientists in their everyday challenges. The following two articles in this section are more aimed at software developers and/or bioinformaticians. First, Wang et al. give a comprehensive overview of the most popular open source and free-to-use software libraries and frameworks that can be used to develop software for data visualization purposes. Second, Gatto et al. examine the current visualisation software available developed using the R programming language and the closely related open source project Bioconductor, a topic that is on purpose not covered in the more general review mentioned before. After these two more technical focused reviews, the fourth article (by Porras et al.), devoted to data visualization of molecular interaction data, is aimed again at a broader audience. The manuscript summarizes the current knowledge of the interactome of the protein LRRK2 (Leucine-rich repeat kinase 2), which has been associated with an increased risk of Parkinson’s disease, and uses this as an example to illustrate the usefulness of targeted curation and to describe the analysis and visualisation software available for this type of data. In the final review article, Bhavnani et al. introduce visual analytics approaches and their concrete application in the case of translational teams working with patients with complex diseases. Using these approaches, researchers can address well-known challenges such as modeling and inferring heterogeneity, in the proteomic and phenotypic profiles of these patients. The second section of the Special Issue, devoted to research articles, contains one single manuscript. This contribution (by Zhang et al.) describes an interesting technique called seaMass, which represents a novel signal decomposition approach for mass spectrometry data. This open source software can be used to achieve an efficient streaming of mass spectra, enabling the development of highly interactive visualisation tools for large, remotely stored mass spectrometry runs. The third and final section of the Special Issue contains six shorter ‘Technical Brief’ articles, which describe the current status of several software applications and tools. First, the contribution of Barsnes et al. introduces a software library called JSparklines that was specifically designed to facilitate the interpretation and visualisation of tabular data. This open source Java library can be integrated in a wide variety of visualization tools. The second manuscript in this section (by Knight et al.) presents a set of web tools for enabling an effective visualization and interpretation of quantitative protein-protein interaction data. Next, Mesuere et al. describe C 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Juan Antonio Vizca´ıno
Harald Barsnes
Henning Hermjakob
www.proteomics-journal.com
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Proteomics 2015, 15, 1339–1340
recent updates to the Unipept metaproteomics analysis pipeline, and in particular new visualisation approaches. The fourth manuscript in this section (by Aiche et al.) introduces the concept of workflows, presenting the integration of tools from the open source software framework OpenMS into the workflow engine KNIME for the analysis of large datasets and generation of high quality visualizations. The following contribution (by Vermeire et al.) describes scop3D, a tool that visualises sequence conservation in the context of protein structures. Lastly, bringing closure to this Special Issue, the contribution by Tyanona et al. provides an update on the data visualization capabilities of the latest version of the popular MaxQuant analysis software. We would like to emphasize that this Special Issue owes its existence to the excellent contributions made by the different authors, and very importantly, to the efforts of the anonymous reviewers, who invested their valuable time and expertise scrutinizing the manuscripts. We also want to thank the Editor-in-Chief, Prof. Michael J. Dunn, and the Managing Editor, Dr. Hans-Joachim Kraus, for their great help in producing this Special Issue. We hope that you will not only enjoy it, but also gain novel insights for your own future work!
Juan Antonio Vizca´ıno
Harald Barsnes
C 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Henning Hermjakob
www.proteomics-journal.com
