@article {DBLP:journals/bioinformatics/QuandtHMHMPAL08, title = {swissPIT: a novel approach for pipelined analysis of mass spectrometry data}, journal = {Bioinformatics}, volume = {24}, number = {11}, year = {2008}, pages = {1416-1417}, abstract = {The identification and characterization of peptides from tandem mass spectrometry (MS/MS) data represents a critical aspect of proteomics. Today, tandem MS analysis is often performed by only using a single identification program achieving identification rates between 10-50\% (Elias and Gygi, 2007). Beside the development of new analysis tools, recent publications describe also the pipelining of different search programs to increase the identification rate (Hartler et al., 2007; Keller et al., 2005). The Swiss Protein Identification Toolbox (swissPIT) follows this approach, but goes a step further by providing the user an expandable multi-tool platform capable of executing workflows to analyze tandem MS-based data. One of the major problems in proteomics is the absent of standardized workflows to analyze the produced data. This includes the pre-processing part as well as the final identification of peptides and proteins. The main idea of swissPIT is not only the usage of different identification tool in parallel, but also the meaningful concatenation of different identification strategies at the same time. The swissPIT is open source software but we also provide a user-friendly web platform, which demonstrates the capabilities of our software and which is available at http://swisspit.cscs.ch upon request for account.}, keywords = {bioinformatics, scientific workflow management}, doi = {10.1093/bioinformatics/btn139}, url = {http://www.ncbi.nlm.nih.gov/pubmed/18436540}, author = {Andreas Quandt and Patricia Hernandez and Alexandre Masselot and C{\'e}line Hernandez and Sergio Maffioletti and Cesare Pautasso and Ron D. Appel and Fr{\'e}d{\'e}rique Lisacek} } @conference {91, title = {Dependable computing in virtual laboratories}, booktitle = {17th IEEE International Conference on Data Engineering (ICDE 2001)}, year = {2001}, month = {April}, pages = {235 - 242}, publisher = {IEEE}, organization = {IEEE}, address = {Heidelberg, Germany}, abstract = {Many scientific disciplines are shifting from in vitro to in silico research as more physical processes and natural phenomena are examined in a computer (in silico) instead of being observed (in vitro). In many of these virtual laboratories, the computations involved are very complex and long lived. Currently, users are required to manually handle almost all aspects of such computations, including their dependability. Not surprisingly, this is a major bottleneck and a significant source of inefficiencies. To address this issue, we have developed BioOpera, an extensible process support management system for virtual laboratories. The authors briefly discuss the architecture and functionality of BioOpera and show how it can be used to efficiently manage long lived computations}, keywords = {bioinformatics, BioOpera, scientific workflow management, virtual laboratories}, doi = {10.1109/ICDE.2001.914834}, url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=914834}, author = {Gustavo Alonso and Win Bausch and Cesare Pautasso and Ari Kahn} }