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mathPlot Web service (1)

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Plotting operation which uses Mathematica (http://www.wolfram.com/mathematica/) software.

Created: 2011-01-26 | Last updated: 2011-01-26

Credits: trybik

odeSolver Web service (1)

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SBML ODE Solver Library (http://www.tbi.univie.ac.at/~raim/odeSolver/) Web service.

Created: 2011-01-26 | Last updated: 2011-01-26

Credits: trybik

sbml2Prism Web service (1)

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For example of the SBML to PRISM translation and the description of its details see http://www.prismmodelchecker.org/manual/RunningPRISM/SupportForSBML .

Created: 2011-01-26 | Last updated: 2011-01-26

Credits: trybik

asynchronous prism Web service (1)

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Asynchronous version of the Prism Web service. Results XML list is sent via email.

Created: 2011-01-26 | Last updated: 2011-01-26

Credits: trybik

prism Web service (1)

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PRISM model checking (http://www.prismmodelchecker.org/manual/RunningPRISM/ModelChecking). The '-fixdl' switch is used, which means that all deadlock states in model are fixed by addition of self-loops.

Created: 2011-01-26 | Last updated: 2011-01-26

Credits: trybik

SELECT3 (2)

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Select3 decides if a particular transition matches the selection criteria based on the line strength and line opacity in a given medium. To do that select3 requires a model of the medium (temperature, pressure, node spacing), chemical composition and boundary conditions. Only 1D models are supported at the moment. Select3 processes one transition at a time working in two modes: opacity and synthesis. In the first mode it computes line opacity, compares it to the reference (e.g. bf and ff opa...

Created: 2011-01-22 | Last updated: 2011-02-27

Pathways and Gene annotations forQTL region (1)

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This workflow searches for genes which reside in a QTL (Quantitative Trait Loci) region in Cow, Bos taurus. 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 UniProt 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 data...

Created: 2011-01-21 | Last updated: 2011-01-21

Credits: Paul Fisher

Change Class Distribution of Your Training... (1)

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This example process shows how to change the class distribution of your training data set (in this case the training data is what ever comes out of the "myData reader"). The given training set has a distribution of 10 "Iris-setosa" examples, 40 "Iris-versicolor" examples and 50 "Iris-virginica" examples. The aim is to get a data set which has the class distribution for the label, lets say 10 "Iris-setosa", 20 "Iris-versicolor" and 20 "Iris-virginica. Beware that this may change some propert...

Created: 2011-01-21 | Last updated: 2011-01-21

PRM With External Data (1)

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IN PROGRESS! Runs the PRM using data from an external on-line source.

Created: 2011-01-19 | Last updated: 2011-01-19

Credits: Nick Malleson

QSPR Model Discovery -- workflow structure... (2)

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replicates the structure of the QSPR model discovery workflow. Ref.: replicates the structure of the QSPR model discovery workflow. Ref.: http://www.openqsar.com/

Created: 2011-01-18 | Last updated: 2011-01-18

EBI_InterproScan_NewServices (2)

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This workflow performs an interproscan on provided sequencesThis workflow performs an interproscan at the EBI on sequences provided as input. The output is provided as text, xml or png. This workflow uses the new EBI services, which are asynchronous and require looping over the nested workflow (Status) until the workflow has finished. Many of the EBI services now work in this way, so you can use this workflow as an example of the invocation pattern and looping configuration.

Created: 2011-01-17 | Last updated: 2011-01-17

Credits: Katy Wolstencroft Hamish McWilliam Stian Soiland-Reyes

Attributions: EBI_InterProScan for Taverna 2 EBI_InterProScan for Taverna 2 EBI_InterProScan

Split Molecules Into Clusters (1)

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This workflow splits given molecules into their cluster memberships. The molecules are loaded from a SD file and the relationship data from a CSV file. The results are saved into N different SD files, where N is the number of clusters.

Created: 2011-01-17 | Last updated: 2011-07-21

2. Getting Started: Retrieve and Apply a M... (1)

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This getting started process demonstrates how to load (retrieve) a model from the repository and apply it to a data set. The result is a data set (at the lab output for "labeled data" ) with has a new "prediction" attribute which indicated the prediction for each example (ie. row/record). You will need to adjust the path of the retrieve data operator to the actual location where the model is stored by a previews execution of the "1. Getting Started: Learn and Store a...

Created: 2011-01-17 | Last updated: 2011-01-19

1. Getting Started: Learn and Store a Model (1)

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This getting started process shows the first step of learning and storing a model. After a model is learned, you can load (Retrieve operator) the model and apply it to a test data set (see 2. Getting Started: Retrieve and Apply Model). The process is NOT concerned with evaluation of the model. This process will not immediately run in RapidMiner because you have to adjust the repository path in the Retrieve operator. Tags: Rapidminer, model, learn, learning, training, train, store, first step

Created: 2011-01-17 | Last updated: 2011-01-17

Count co-occurences in matrix with Aggrega... (1)

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The process counts and shows all combinations of values of two attributes and shows them in a count matrix. The process uses the operators Aggregate and Pivot for this purpose.

Created: 2011-01-15

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Fluid Dynamics Error

Created: 2011-01-14 18:26:24 | Last updated: 2011-01-14 18:26:25

Credits: Mity

License: Creative Commons Attribution-Share Alike 3.0 Unported License

File type: Word document

Comments: 0 | Viewed: 25 times | Downloaded: 90 times

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Weka Clustering Considering Different Orig... (2)

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This workflow clusters the given CSV files with the chosen Weka algorithm. The results are visualized in a PDF file. The CSV files are loaded from hard disk and merged together. Afterwards they are converted into a Weka dataset which is the suitable data type for the Weka clustering activity. The results are visualized as a PDF file showing the cluster membership of each input CSV file.

Created: 2011-01-13 | Last updated: 2011-07-21

Population reconstruction and dynamic popu... (2)

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Runs the population reconstruction model (PRM) to create a synthetic individual-level population and then projects the population through a number of years. This is still in progress, results cannot be made public yet.

Created: 2011-01-12 | Last updated: 2011-01-19

Credits: Nick Malleson

Text stemming with Porter Stemmer (1)

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This workflow does text stemming. Stemming removes the inflicted endings of words. It is often used as text preprocessing for text mining, since stemmed words can be easily matched and counted. The input to the workflow is the text to be stemmed, the output is the stemmed text.  

Created: 2011-01-11 | Last updated: 2011-01-11

Credits: Petra Kralj Novak

JSI Subgroup Discovery operators (1)

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A simple example of how to use subgroup discovery operators for learning subgroup descriptions and how to test their classification accuracy using cross-validation.

Created: 2011-01-10 | Last updated: 2011-01-10

Text preprocessing (1)

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The input to this workflow is plain text. The text is preprocessed so that non- alfanumeric symbols are removed, the text is transformed to to lower case and stop words are removed. The workflow first removes the charachters from this set: `~!@#$%^&*()_+=-{}|\][":;'?><,./. Then it transforms the text to lower case. The user will be prompted to select a dictionary for stop words from a list. The workflow will, based on the selected list, remove the stop words. Stop words are...

Created: 2011-01-07 | Last updated: 2011-01-07

Credits: Petra Kralj Novak

RBioconductor Tutorial Process (1)

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This Process illustrates how to create complex Data Analysis processes using R Scripts. In this case the Bioconductor Basic Tutorial is splitted into reusable components.

Created: 2011-01-03

Select from a list of possible web service... (1)

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The workflow for selecting from a list of possible web service parameter values has two input ports: the wsdl address of the web service and the variable name. It parses the web service wsdl description (the web service http://ropot.ijs.si/webservices/janez/getvalues.php?wsdl does that) and then it asks the user to select one value from a drop-down menu. This workflow is very useful when web services have inputs which expect as a parameter one value from a list of possible values.

Created: 2010-12-23 | Last updated: 2010-12-23

Credits: Petra Kralj Novak Janez Kranjc

Lemmatization (3)

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The workflow lemmatizes the text in the input port. Takes text as input and returns (language dependent) lemmatized text as output. All the words in the resulting text are in the same order as in the original text, but they are transformed to their dictionary form. The workflow asks for the language of lemmatization. Currently, 12 languages are supported: en,sl,ge,bg,cs,et,fr,hu,ro,sr,it,sp.

Created: 2010-12-17 | Last updated: 2010-12-23

Credits: Petra Kralj Novak

Attributions: Select from a list of possible web service parameter values

Get Molecular Weight Distribution From QSA... (2)

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This workflow calculates a molecular weight distribution from given QSAR vector. The QSAR data containing the molecular weight values is read from a CSV file and converted into a QSAR vector. Finally, the Get_molecular_Weight_Distribution_From_QSAR_vector extracts the weight data and saves it as CSV files.

Created: 2010-12-15 | Last updated: 2011-07-21