Workflows

hierarchical microarray clustering (1)

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To illustrate our caGrid plug-in’s application, we tested it with a microarray hierarchical clustering workflow that involves services hosted at multiple institutions. Microarrays are a high-throughput technology used to measure the expression of tens of thousands of genes in different tissues or cells. Scientists represent the data from each microarray via a vector (profile) in which each element represents a gene’s expression level. They use clustering analysis to identify sim...

Created: 2008-12-05 | Last updated: 2008-12-05

Credits: Wei Tan

Clustering of Molecular Compounds with Bio... (4)

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This workflow downloads an input set of molecular compounds in SMILES format, using Chemspider service. The most frequent molecular fragments are extracted by means of MoSS tool (see http://www.borgelt.net/moss.html) , in order to obtain a set of features for each compound. Then a clustering and a visual exploration of the input dataset is performed by BioDICE service (see http://biolab.pa.icar.cnr.it/biodice.html), implementing Fast Learning Self-Organized Map (FLSOM) algorithm. Finally the ...

Created: 2013-05-29 | Last updated: 2014-01-09

Credits: Antonino Fiannaca Massimo La Rosa

Attributions: Get compound information Simple search

SNP identification and evaluation for Diab... (1)

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This workflow gathers SNP information for a gene set of Diabetes Type II phenotype using BioMart queries. Furthermore, GO Terms and functional annotation clustering are defined for this gene set using FunctionalClusterDavid workflow. 

Created: 2015-06-23

Credits: Nikolaos Bismpikos Katy Wolstencroft

Attributions: FunctionalClusterDavid

FunctionalClusterDavid (1)

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This workflow takes a list of Entrez Gene IDs as input and submits them to the DAVID REST API for functional clustering using OG annotaiton, biological pathways and disease associations. Used for analysing a set of genes (i.e. those differentially expressed for a particular disease condition).

Created: 2014-09-05

Credits: Katy Wolstencroft

Population genomics : Structure and CLUMPP (1)

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Population genomics analysis using Structure and Clumpp to cluster data

Created: 2014-02-27 | Last updated: 2014-06-10

Credits: Ylebras

document clustering (1)

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Tesla Experiment Clustering wikipedia articles of different topics Evaluation of the results with the purity measure and rand index

Created: 2012-02-15 | Last updated: 2012-02-17

Credits: AGeduldig

Loading OWL files (RDF version of videolec... (1)

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The workflow uses RapidMiner extension named RMonto (http://semantic.cs.put.poznan.pl/RMonto/). Operator "Build knowledge base" is responsible for collecting data either from OWL files or SPARQL endpoints or RDF repositories and provide it to the subsequent operators in a workflow. In this workflow it is parametrized in this way, that is builds a Sesame/OWLIM repository from the files specified in "Load file" operators. Paths to OWL files are specified as parameter va...

Created: 2012-01-29 | Last updated: 2012-01-29

Semantic clustering (with alpha-clustering... (1)

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The workflow uses RapidMiner extension named RMonto (http://semantic.cs.put.poznan.pl/RMonto/) to perform clustering of SPARQL query results based on chosen semantic similarity measure. The measure used in this particualr workflow is a kernel that exploits membership of clustered individuals to OWL classes from a background ontology ("Epistemic" kernel from [1]). Since the semantics of the backgound ontology is used in this way, we use the name "semantic clustering". This ...

Created: 2012-01-29 | Last updated: 2012-01-30

Semantic clustering (with AHC) of SPARQL q... (1)

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The workflow uses RapidMiner extension named RMonto (http://semantic.cs.put.poznan.pl/RMonto/) to perform clustering of SPARQL query results based on chosen semantic similarity measure. The measure used in this particualr workflow is a kernel that exploits membership of clustered individuals to OWL classes from a background ontology ("Common classes" kernel from [1]). Since the semantics of the backgound ontology is used in this way, we use the name "semantic clustering". ...

Created: 2012-01-29 | Last updated: 2012-01-29

Semantic clustering (with k-medoids) of SP... (1)

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The workflow uses RapidMiner extension named RMonto (http://semantic.cs.put.poznan.pl/RMonto/) to perform clustering of SPARQL query results based on chosen semantic similarity measure. Since the semantics of the backgound ontology is used in this way, we use the name "semantic clustering". The SPARQL query is entered in a parameter of "SPARQL selector" operator. The clustering operator (k-medoids) allows to specify which of the query variables are to be used as clustering criteria. If more ...

Created: 2012-01-29