Workflows for automated downstream data analysis and visualization in large-scale computational mass spectrometry
@inproceedings{Aiche2015WorkflowsFA, title={Workflows for automated downstream data analysis and visualization in large-scale computational mass spectrometry}, author={Stephan Aiche and Timo Sachsenberg and Erhan Kenar and Mathias Walzer and Bernd Wiswedel and Theresa Kristl and Matthew S. P. Boyles and Albert Duschl and Christian G. Huber and Michael R. Berthold and Knut Reinert and Oliver Kohlbacher}, booktitle={Proteomics}, year={2015} }
MS-based proteomics and metabolomics are rapidly evolving research fields driven by the development of novel instruments, experimental approaches, and analysis methods. Monolithic analysis tools perform well on single tasks but lack the flexibility to cope with the constantly changing requirements and experimental setups. Workflow systems, which combine small processing tools into complex analysis pipelines, allow custom-tailored and flexible data-processing workflows that can be published or… CONTINUE READING
Citations
Publications citing this paper.
SHOWING 1-10 OF 13 CITATIONS
Conquering Big Data with High Performance Computing
VIEW 10 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED
A Critical Evaluation of Wet Biomarkers for Huntington’s Disease: Current Status and Ways Forward
VIEW 1 EXCERPT
CITES METHODS
Automated SWATH Data Analysis Using Targeted Extraction of Ion Chromatograms.
VIEW 1 EXCERPT
CITES METHODS
Computational quality control tools for mass spectrometry proteomics.
VIEW 1 EXCERPT
CITES METHODS
ImmunoNodes – graphical development of complex immunoinformatics workflows
VIEW 1 EXCERPT
CITES METHODS
Explorer dispel 4 py : A Python Framework for Data-Intensive ScientificComputing
VIEW 1 EXCERPT
CITES BACKGROUND
References
Publications referenced by this paper.
SHOWING 1-10 OF 16 REFERENCES
KNIME: The Konstanz Information Miner
VIEW 3 EXCERPTS
TOPP - the OpenMS proteomics pipeline
VIEW 5 EXCERPTS