MOTIVATION: The proteomics field requires the production and publication of reliable mass spectrometry-based identification and quantification results. Although many tools or algorithms exist, very few consider the importance of combining, in a unique software environment, efficient processing algorithms and a data management system to process and curate hundreds of datasets associated with a single proteomics study. RESULTS: Here, we present Proline, a robust software suite for analysis of MS-based proteomics data, which collects, processes and allows visualization and publication of proteomics datasets. We illustrate its ease of use for various steps in the validation and quantification workflow, its data curation capabilities and its computational efficiency. The DDA label-free quantification workflow efficiency was assessed by comparing results obtained with Proline to those obtained with a widely used software using a spiked-in sample. This assessment demonstrated Proline's ability to provide high quantification accuracy in a user-friendly interface for datasets of any size. AVAILABILITY AND IMPLEMENTATION: Proline is available for Windows and Linux under CECILL open-source license. It can be deployed in client-server mode or in standalone mode at http://proline.profiproteomics.fr/#downloads. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

This paper presents Schlouder, a broker of IaaS cloud resources which helps users to take advantage of IaaS elasticity. The main advantages of Schlouder are its simplicity, its extensibility, and its capability to provide the user with a prediction of the make span and cost, given the chosen provisioning strategy and before any actual execution. This paper illustrates how Schlouder enables, with a very limited engineering effort, the port of a bag-of-tasks scientific application which was originally developed for the European Grid Infrastructure. Experiments in real environment support assessments on Schlouder efficiency and comparison between grids and clouds for scientific computations. We conclude that porting grid applications to the cloud represents a shift in the associated problematics: from tailoring the application to the platform, to tailoring the platform to the application.