Format

Send to

Choose Destination
J Proteomics. 2015 Nov 3;129:78-82. doi: 10.1016/j.jprot.2015.05.029. Epub 2015 Jun 3.

Distributed and interactive visual analysis of omics data.

Author information

1
Proteomics Unit, Department of Biomedicine, University of Bergen, Bergen, Norway; Department of Informatics, University of Bergen, Norway; KG Jebsen Centre for Multiple Sclerosis Research, Department of Clinical Medicine, University of Bergen, Bergen, Norway.
2
Proteomics Unit, Department of Biomedicine, University of Bergen, Bergen, Norway; KG Jebsen Centre for Multiple Sclerosis Research, Department of Clinical Medicine, University of Bergen, Bergen, Norway; Norwegian Multiple Sclerosis Competence Centre, Department of Neurology, Haukeland University Hospital, Bergen, Norway.
3
Computational Biology Unit, Department of Informatics, University of Bergen, Norway.
4
Proteomics Unit, Department of Biomedicine, University of Bergen, Bergen, Norway; Department of Clinical Medicine, University of Bergen, Bergen, Norway. Electronic address: harald.barsnes@uib.no.

Abstract

The amount of publicly shared proteomics data has grown exponentially over the last decade as the solutions for sharing and storing the data have improved. However, the use of the data is often limited by the manner of which it is made available. There are two main approaches: download and inspect the proteomics data locally, or interact with the data via one or more web pages. The first is limited by having to download the data and thus requires local computational skills and resources, while the latter most often is limited in terms of interactivity and the analysis options available. A solution is to develop web-based systems supporting distributed and fully interactive visual analysis of proteomics data. The use of a distributed architecture makes it possible to perform the computational analysis at the server, while the results of the analysis can be displayed via a web browser without the need to download the whole dataset. Here the challenges related to developing such systems for omics data will be discussed. Especially how this allows for multiple connected interactive visual displays of omics dataset in a web-based setting, and the benefits this provide for computational analysis of proteomics data.This article is part of a Special Issue entitled: Computational Proteomics.

KEYWORDS:

Bioinformatics; Computational analysis; Visual analysis

PMID:
26047716
DOI:
10.1016/j.jprot.2015.05.029
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Elsevier Science
Loading ...
Support Center