Version 2 (latest)
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Version created on:
26/10/08 @ 21:16:10
by:
Hamish McWilliam
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Title: Protein_transmembrane_prediction
Type: Taverna 1
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Description
Transmembrane and signal peptide prediction using three methods: 1. EMBOSS tmap with a single sequence. Uses Soaplab tmap. 2. Phobius. Uses EBI’s WSPhobius web service. 3. TMHMM and SignalP. Uses the TMHMM and SignalP methods of InterProScan via the EBI’s WSInterProScan service.
The results of the three methods are converted into GFF format and collated.
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Option 1:
Note: you need to have both the WHIP Launcher and the Taverna myExperiment/WHIP plugin installed on your machine for this to work. See here for information.
Option 2:
Copy and paste this link into File > 'Open workflow location...'
http://www.myexperiment.org/workflows/216/download?version=2
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All versions of this Workflow are licensed under the Creative Commons Attribution 3.0 License.
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Earliest Version:
[1] - Protein_transmembrane_prediction
Latest Version:
[2] - Protein_transmembrane_prediction
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Copyright (c) 2007 - 2008 The University of Manchester and University of Southampton
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Any chance of getting the subworkflows for this as well. Couldn't find them online and I want the polling part. i.e. For loads of the EBI jobs, you have to write beanshells to check if the job is done. It would nice to see a write up on how to create workflows for this.
Thanks,
Niall
Hi Niall. The subworkflows are included. If you download this workflow, load it into Taverna and navigate to the nexted workflows you can save them indpendantly using the normal save functionality.
The general process required to poll for service results is explained on the EBI website (see http://www.ebi.ac.uk/Tools/webservices/tutorials/workflow/taverna). In brief it uses Taverna's retry mechanism and a nested workflow which fails if the job has not completed.
Great!
With which proteins have you tried this workflow? Do you have an estimate for its precision/accuracy?
There are other protein structure preditors that merge results from various sources, and combine them, to obtain a better prediction.
Is this the same approach you are using in this protocol?
e.g. I know of this predictor (http://pongo.biocomp.unibo.it/), but it is only for membrane proteins structure. Is it something similar?
How are the gff results merged at the end of the workflow? What does Gff_output contains, exactly?