Magnus Palmblad's Workflows

connect to WoS Web services lite concept (1)

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This workflow is a concept for how Taverna could connect to the Thomson Reuters Web of Science (WoS) Web services lite. However, at this moment (2015-01-20), the authentication generate a session ID, but the other services (here search and closeSession) do not have an input port for this session ID. According to the documentation, this is required. The error message from the Web service also show this is missing. This workflow is "work in progress", but may nevertheless be of interest to an...

Created: 2015-01-20 | Last updated: 2015-08-19

Credits: Magnus Palmblad Arzu Tugce Guler Cathelijn Waaijer

Make Groups for Tutorial (2)

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The workflow pairs people from two groups of equal size into the same number of pairs with one member from each group. This is done randomly, using the random.org randomization engine, which in turn is based on atmospheric radio noise.

Created: 2014-04-16 | Last updated: 2015-10-12

Credits: Magnus Palmblad

Tutorial 1 Workflow (2)

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Fetch and combine transcriptomics and proteomics data from NSC11 cells in GEO and PRIDE respectively. Apply spectral counting on the proteomics data. The workflow demonstrates how to combine data from different domains (here microarray- based transcriptomics and mass spectrometry-based proteomics) and do something useful with the data. The workflow also demonstrates spreadsheet import and XPath parsing of XML data. This workflow is for tutorial/educational use only. The cells were not grown...

Created: 2014-04-16 | Last updated: 2014-04-16

Credits: Magnus Palmblad

Tutorial_1_start (1)

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This partial workflow is the starting point for Taverna tutorial held at the Leiden University Medical Center on April 17, 2014.

Created: 2014-04-16

Credits: Magnus Palmblad

RTCalc Retention Time Prediction and Outli... (1)

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This workflow takes as input a pepXML file from PeptideProphet, applied RTCalc and outputs a filtered list of peptides based on the retention time Z-scores.

Created: 2014-02-06 | Last updated: 2014-02-06

Credits: Magnus Palmblad Sonja Holl

Simulate_Mass_Spectrum (1)

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This workflow takes as input a peptide sequence and calculates the elemental composition of the peptide (Calculate_Elemental_Composition). This is then transferred as a numerical vector to the Rshell Simulate_Mass_Spectrum, that calculates the isotopic distribution using the FFT method and convolutes the theoretical (infinite resolution) distribution with a Gaussian peak shape. The building blocks can be used in any other workflows using the isotopic distribution of peptides or other molecul...

Created: 2013-03-12

Credits: Magnus Palmblad

Calculate_Isotopic_Distribution (1)

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This small workflow takes as input a peptide sequence and calculates the elemental composition of the peptide (Calculate_Elemental_Composition). This is then transferred as a numerical vector to the Rshell Calculate_Isotopic_Distribution, that calculates the (integer mass) isotopic distribution using the FFT method. To shift to approximate real masses (or m/z values), transpose the distribution with the difference between the integer and real monoisotopic masses (both easily calculated using ...

Created: 2013-03-05

Credits: Magnus Palmblad

ROC_AUC_Workflow (1)

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This small workflow extracts the area under the curve (AUC) from the receiver operating characteristic (ROC) curve for all charge states analyzed by PeptideProphet. This measure can be used to compare the sensitivity and specificity of different search engines for matching tandem mass spectra to peptides.

Created: 2013-01-28

Credits: Magnus Palmblad

Retention Time Prediction with X!Tandem (1)

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This workflow identifies peptides from tandem mass spectra using X!Tandem as in a standard installation of the Trans-Proteomic Pipeline (TPP, version 4.6, but earlier versions should also work). The peptide-spectrum matches are validates using PeptideProphet (also from a standard installation of TPP) and peptides with at least a probability 0.95 are used to train a linear retention time predictor (Palmblad et al., 2002), whereby retention coefficients are also derived. These indirectly provid...

Created: 2012-09-03 | Last updated: 2012-09-03

Credits: Magnus Palmblad Yassene Eleni

Attributions: rt3.c

de Bruin et al. Workflow 4 (1)

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This is "Workflow 4" from de Bruin et al., Mol. Cell. Proteomics 2012.

Created: 2012-08-01 | Last updated: 2012-08-01

Credits: Magnus Palmblad

de Bruin et al. Workflow 3 (1)

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This is "Workflow 3" from de Bruin et al., Mol. Cell. Proteomics 2012.

Created: 2012-08-01 | Last updated: 2012-08-01

Credits: Magnus Palmblad

de Bruin et al. Workflow 2 (1)

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This is "Workflow 2" from de Bruin et al., Mol. Cell. Proteomics 2012.

Created: 2012-08-01 | Last updated: 2012-08-01

Credits: Magnus Palmblad

de Bruin et al. Workflow 1 (1)

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This is "Workflow 1" from de Bruin et al., Mol. Cell. Proteomics 2012.

Created: 2012-08-01 | Last updated: 2012-08-01

Credits: Magnus Palmblad

Plasma Precipitation Analysis (1)

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ABOUT THE WORKFLOW This workflow was used to analyze the data in a manuscript by Mostovenko et al. (2012, submitted), comparing proteins in the precipitate with those left in solution after organic solvent precipitation. However, the workflow is generally applicable in comparisons of any binary fractionation method in proteomics, where the fractions are analyzed by liquid chromatography-tandem mass spectrometry. The workflow identifies proteins by SpectraST spectral library search and X!Ta...

Created: 2012-07-31 | Last updated: 2012-07-31

Credits: Magnus Palmblad Kate Mostovenko Yassene