ATAQS: A computational software tool for high throughput transition optimization and validation for selected reaction monitoring

Background: Since its inception, proteomics has essentially operated in a discovery mode with the goal of identifying and quantifying the maximal number of proteins in a sample. Increasingly, proteomic measurements are also supporting hypothesis-driven studies, in which a predetermined set of proteins is consistently detected and quantified in multiple samples. Selected reaction monitoring (SRM) is a targeted mass spectrometric technique that supports the detection and quantification of specific proteins in complex samples at high sensitivity and reproducibility. Here, we describe ATAQS, an integrated software platform that supports all stages of targeted, SRMbased proteomics experiments including target selection, transition optimization and post acquisition data analysis. This software will significantly facilitate the use of targeted proteomic techniques and contribute to the generation of highly sensitive, reproducible and complete datasets that are particularly critical for the d...

• Type: Journal
• Year: 2011
• Where: BMCBI
• Authors: Mi-Youn K. Brusniak, Sung-Tat Kwok, Mark Christiansen, David Campbell, Lukas Reiter, Paola Picotti, Ulrike Kusebauch, Hector Ramos, Eric W. Deutsch, Jingchun Chen, Robert L. Moritz, Ruedi Aebersold
• Keywords: Artificial Intelligence, BMCBI 2011, Hypothesis-driven Studies, Protein, Proteomics