Workflows

blastn and blastx (1)

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This workflow accepts an url of a fasta file as input and performs an NCBI blastn at the EBI against the bacteria database and an NCBI blastx against the uniref90 database.  From the blast results of the blastx the hit with the lowest e-value is taken and the GO is returned. Output is blastx and blastn results and GO from the first hit of the blastx.   Based on Katy Wolstencroft & Hamish McWilliam EBI_NCBI_BLAST http://www.myexperiment.org/workflows/1765.html

Created: 2011-06-08 | Last updated: 2011-06-08

Credits: Niek

Bash example from the NGS community contri... (1)

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  BASH Simple workflow that executes "ls" on the command line in the directory "/".

Created: 2011-06-07

Credits: Baj

Download the ONS solubility data from Goog... (1)

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 Use the Bioclipse scripting langauge to authenticate with Google Docs, and download the Open Notebook Science solubility data into a local data structure.

Created: 2011-06-06 | Last updated: 2011-06-06

Credits: Egon Willighagen

DAS features retrieval and parsing with JDAS (2)

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Retrieve Protein or Genome features using the Distributed Annotation System (DAS) and create your own text output by modifying the JDAS component. To be able to use this workflow with JDAS copy this file … http://www.ebi.ac.uk/~maven/m2repo/uk/ac/ebi/das/jdas/1.0.3/jdas-1.0.3.jar … to the lib folder inside the Taverna application. This jar file is a dependency needed to parse DAS outputs.

Created: 2011-06-01 | Last updated: 2011-06-02

Credits: Rafael C. Jimenez

DAS features retrieval (2)

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Retrieve Protein or Genome features (annotations) using the Distributed Annotation System (DAS).

Created: 2011-06-01 | Last updated: 2011-06-01

Credits: Rafael C. Jimenez

DAS sequence retrieval and parsing with JDAS (1)

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Retrieve Protein or Genome sequences using the Distributed Annotation System (DAS) and create your own text output by modifying the JDAS component. To be able to use this workflow with JDAS, copy this file … http://www.ebi.ac.uk/~maven/m2repo/uk/ac/ebi/das/jdas/1.0.3/jdas-1.0.3.jar … to the lib folder inside the Taverna application. This jar file is a dependency needed to parse DAS outputs.

Created: 2011-05-30 | Last updated: 2011-05-30

Credits: Rafael C. Jimenez

DAS sequence retrieval (2)

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Retrieve Protein or Genome sequences using the Distributed Annotation System (DAS).

Created: 2011-05-30 | Last updated: 2011-05-30

Credits: Rafael C. Jimenez

Find Biological Models by GO. (1)

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Find Biological Models (Ids and Names) from Biomodels querying by Gene Ontology terms.

Created: 2011-05-29 | Last updated: 2011-05-29

Credits: Rafael C. Jimenez

Find Reactome pathways and reactions by GO (1)

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Find Reactome pathways and reactions (names and accessions) in Human querying by a Gene Ontology term. This is an example of how to use the Reactome Biomart service in Taverna. Many other possibilities are possible by modifying the filters and attributes options of the service.

Created: 2011-05-29 | Last updated: 2011-05-29

Credits: Rafael C. Jimenez

Find PRIDE experiments by GO (1)

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Find PRIDE experiments in Human with related information like Cell Type and Tissue location filtering results by Gene Ontology terms. This is an example of how to use the PRIDE Biomart service in Taverna. Many other options are possible by modifying the filters and attributes of this service.

Created: 2011-05-29 | Last updated: 2011-05-29

Credits: Rafael C. Jimenez

Molecular Interactions from IntAct PSICQUI... (2)

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Get molecular interaction data in psi-mitab25 from IntAct through its REST PSICQUIC service. As input you can use an Uniprot Acc like "P99999" or a MIQL query like "alias:KHDRBS1".

Created: 2011-05-29 | Last updated: 2011-10-05

Credits: Rafael C. Jimenez

Pathways and Gene annotations for QTL region (1)

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This workflow searches for genes which reside in a QTL (Quantitative Trait Loci) region in rice, Oryza sativa. The workflow requires an input of: a chromosome name or number; a QTL start base pair position; QTL end base pair position. Data is then extracted from BioMart to annotate each of the genes found in this region. The Entrez and UniGene identifiers are then sent to KEGG to obtain KEGG gene identifiers. The KEGG gene identifiers are then used to searcg for pathways in the KEGG pathway d...

Created: 2011-05-27 | Last updated: 2011-05-27

Credits: Paul Fisher

Feature selection with background knowledge (1)

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Sample workflow that exploits background knowledge in the form of links connecting attributes in the different measurement data. The input data is assumed to be labeled and consists of different interconnected biological levels. Additionally a number of files defining links between attributes in the different measurement data are provided. This data was used in the KUP data mining challenge (http://tunedit.org/challenge/ON). Here we focus on two biological levels: protein data measured by ...

Created: 2011-05-25 | Last updated: 2011-05-25

Authenticate with the OpenTox network (1)

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 Bioclipse script commands log authenticate with the OpenTox network.

Created: 2011-05-25 | Last updated: 2011-05-25

Credits: Egon Willighagen

Create a molecules table from a list of IU... (1)

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 Scripts that uses OPSIN to convert IUPAC names into chemical structures, which are saved as SD file and openend in the Bioclipse molecules table.

Created: 2011-05-25 | Last updated: 2011-05-25

Credits: Egon Willighagen

Wykorzystanie klasyfikatora binarnego do k... (1)

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Wiele klasyfikatorów (np. SVM) pozwala na klasyfikacjÄ™ jedynie w przypadku gdy zmienna celu jest binarna. Poniższy przepÅ‚yw pokazuje, w jaki sposób operator Polynomial By Binomial Classificaiton pozwala agregować odpowiedzi klasyfikatorów binarnych dla przypadków, w których zmienna celu zawiera wiele różnych wartoÅ›ci.

Created: 2011-05-25 | Last updated: 2011-05-25

Prosty przykład metody Voting (1)

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Ten prosty przykład ilustruje wykorzystanie operatora Voting do przeprowadzenia głosowania większościowego. W zagnieżdżonym operatorze umieszczono przykładowe trzy modele bazowe (drzewo decyzyjne, sieć neuronowa, SVN), odpowiedź z operatora Voting to zwykłe głosowanie.

Created: 2011-05-25 | Last updated: 2011-05-25

Przykład metody Stacking (1)

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Poniższy przepÅ‚yw pokazuje wykorzystanie operatora Stacking do tworzenia meta-klasyfikatorów. Operator Stacking pozwala na zagnieżdżenie dowolnej liczby modeli bazowych, które bÄ™dÄ… równolegle uczone na zbiorze uczÄ…cym. Drugim operatorem zagnieżdżonym jest model klasyfikatora, który uczy siÄ™ na odpowiedziach modeli bazowych (czyli buduje model modeli odpowiedzi). W przykÅ‚adzie jako modele bazowe wykorzystano: drzewo decyzyjne, algorytm k-NN, sieć neurono...

Created: 2011-05-25 | Last updated: 2011-05-25

Prosty przykład algorytmu AdaBoost (1)

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Przepływ obrazuje przykład wykorzystania algorytmu AdaBoost. W kolejnych teracjach metoda modyfikuje przykłady ze zbioru uczącego, przypisując większą wagę przykładom błędnie sklasyfikowanym we wcześniejszych iteracjach.

Created: 2011-05-25 | Last updated: 2011-05-25

Przyklad metody Bagging (1)

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Proces pokazuje przykÅ‚ad wykorzystania metody Bagging do tworzenia zlożonych klasyfikatorów. Metoda generuje 10 niezależnych modeli drzewa decyzyjnego (każdy na podstawie 90% próbki zbioru uczÄ…cego). Ostateczna odpowiedź jest wynikiem gÅ‚osowania.

Created: 2011-05-25 | Last updated: 2011-05-25