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Sample Dataset

Created: 2012-06-17 14:45:21

Credits: Eoghan Barry

License: Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 Unported License

File type: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet

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Presentation - The Reality of Reproducibility of in ...

Created: 2012-06-16 13:34:35 | Last updated: 2012-06-28 09:43:48

4 items in this pack

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Gene enhancer region analysis (1)

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 This Galaxy pipeline searches for transciption factor binding sites which are conserved through to Fugu. It then finds genes associated with these enhancer binding sites. See http://screencast.g2.bx.psu.edu/MAF_manipulation for the screencast that describes how this workflow is developed.

Created: 2012-06-14 | Last updated: 2012-07-06

Advanced FastQ manipulation (1)

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 This Galaxy workflow performs advanced FastQ manipulation as demonstrated by the screencast at http://screencast.g2.bx.psu.edu/quickie_14_fastq_adv/flow.html. Given a FastQ set of data, it will be transformed using the tools, Groomer, Filter FastQ, FastQ Trimmer, Manipulate FastQ before it is finally converted into FASTA format.

Created: 2012-06-14 | Last updated: 2012-06-14

Perform QC on FastQ data (1)

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 This Galaxy pipeline performs quality control analyses on FastQ data. A report is generated which provides various measures of the quality of the sequence reads.

Created: 2012-06-14 | Last updated: 2012-06-14

Gaussian Blur (1)

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Convolves the image with a Gaussian kernel wherein the Gaussian has a standard deviation specified by the user ("sigma") and the kernel width in each dimension is 6 times the standard deviation of the Gaussian. You can find more details here

Created: 2012-06-13 | Last updated: 2012-06-13

galaxy_101 (2)

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  This is a Galaxy pipeline written using the Galaxy 101 tutorial (https://main.g2.bx.psu.edu/galaxy101). The pipeline involves retrieving genome and SNP data from UCSC for a particular chromosome. These data are integrated in order to find exons with the highest number of SNPs.

Created: 2012-06-13 | Last updated: 2012-06-14

Credits: Peter Li

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Trial Pack for UT UCD

Created: 2012-06-11 12:06:57 | Last updated: 2012-06-17 14:46:28

2 items in this pack

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ir

Created: 2012-06-08 03:28:32

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Image Characterisation - Fits (Extended) (1)

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Extracts metadata from images.

Created: 2012-06-06 | Last updated: 2012-06-06

Credits: Markus Plangg

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Dataset for workflow: "TextualAttributeExtraction fo...

Created: 2012-06-03 19:47:32 | Last updated: 2012-06-04 08:37:05

Credits: Ninoaf

License: Creative Commons Attribution-Share Alike 3.0 Unported License

File type: application/x-zip-compressed

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TextualAttributeExtraction for Recommender... (1)

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This workflow takes conent data from VideoLectures.Net Recommender System Challenge and extractes word-vectors for each lecture. Latent semantic analysis with Singular Value Decomposition is done on item-word binary matrix. The last step is the binomializaiton of dataset.

Created: 2012-06-03

Evaluating semantic kernel with k-NN class... (1)

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This workflow uses k-NN classifier to evaluate quality of EL++ Convolution Kernel [1]. As a dataset one of the examples from DL-Learner project [2] is used. After preparing knowledge base with "Build Knowledge Base", the item to item distance matrix is computed with "Calculate Gram/Distance Matrix". Such a matrix is then used as an input to 10-fold cross-validation with k-NN as an classifier and average result is delivered. [1] L. Józefowski, A. Lawrynowicz, J...

Created: 2012-05-30 | Last updated: 2012-06-07

Semantic clustering with k-Medoids and ALC... (1)

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 This workflow loads data from a configuration file for DL-Learner (http://dl-learner.org) and uses ALCN Semantic Kernel [1] to cluster those data with k-Medoids algorithm. [1] N. Fanizzi, C. d’Amato, F. Esposito. Learning with Kernels in Description Logics. ILP 2008  

Created: 2012-05-30 | Last updated: 2012-06-07

Clustering data from DBpedia using AHC (1)

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 This workflow uses Aglomerative Hierarchical Clustering algorithm to build hierarchy of clusters on data downloaded from DBpedia, the semantic version of Wikipedia. RDF data are downloaded from SPARQL endpoint and merged with DBpedia ontology by "Build Knowledge Base". Set of items to cluster is selected with "SPARQL Selector" and later they are clustered by "Agglomerative Hierarchical Clustering" with distance measure induced by the Bloehdorn Kernel [1]. ...

Created: 2012-05-30 | Last updated: 2012-06-07

Anatomical Atlas Generation (1)

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Computes an anatomical atlas based on a set of patient images using registration methods. This workflow is automatic and does not require user interaction. The anatomical atlas is composed of a mean image and the set of transformations for each patient's between the mean image and the patient image. The atlas can be used to segment the mean image once and propagate the segmentation results to each patient image automatically. This workflow has been tested using GIMIAS-1.5 (open source) with ...

Created: 2012-05-29 | Last updated: 2012-05-29

Credits: Gimias

Convert table to CDS format (1)

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It converts a csv file (comma separated values) to the CDS format. It also provides relevant information to create the ReadMe file. The first row in the input file must be the column names. If you want to run this workflow, you have to install astrotaverna plugin. You can easyly cusomize the workflow to provide a votable or fits table as input.

Created: 2012-05-28 | Last updated: 2012-05-28

Credits: Julian Garrido

Get data and images for a date +/- 12 hour... (1)

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From the date as input date +/- 12 hours of data from the MLSO web page is collated. Images for up to three images (closest to date; -1; +1) are created via autoplot

Created: 2012-05-24 | Last updated: 2012-05-24

Credits: Anja Le Blanc

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Getting Started with Taverna - an NGS tutorial

Created: 2012-05-23 14:53:24 | Last updated: 2012-05-30 08:48:19

Credits: Katy Wolstencroft

License: Creative Commons Attribution-Share Alike 3.0 Unported License

File type: PowerPoint presentation

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Temporal Expression Extraction (1)

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This experiment evaluates a method of extracting temporal expressions from documents. It uses the WikiWars-corpus, a time-annotated corpus of descriptions of the course of wars and conflicts. An evaluation component compares the experimently identified expressions with the pre-annotated expressions of the corpus and calculates precision, recall and  f-score.

Created: 2012-05-22 | Last updated: 2012-05-22

Credits: AGeduldig

Watershed (2)

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Local machine example

Created: 2012-05-21 | Last updated: 2012-05-21

Credits: Jorgejesus

Mp3ToWav Mig+QA (2)

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Migrates Mp3 files from input List to Wav files and performs QA. The QA steps include File Format Validation, Significant Property Comparison and migrationQA file content comparison (all CLI). This workflow matches solution SO4 on the SCAPE opf wiki, see http://wiki.opf-labs.org/display/SP/SO4+Audio+mp3+to+wav+Migration+and+QA+Workflow

Created: 2012-05-21 | Last updated: 2013-04-24

Credits: Bolette Jurik

CHEMOPREVENTION WORKFLOW2 WITH DATA (1)

 CHEMOPREVENTION WORKFLOW WITH DATA

Created: 2012-05-19 | Last updated: 2012-05-19

Credits: Kleo Achilleos

CHEMOPREVENTION WORKFLOW1 (1)

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 CHEMOPREVENSION WORKFLOW NO DATA INCLUDED

Created: 2012-05-19 | Last updated: 2016-04-30

Credits: Kleo Achilleos

Hybrid recommendation system (1)

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This is one hybrid recommendation system combining linear regression recommender, created using RapidMiner core operators, and Recommender extension multiple collaborative filtering and attribute based operators.

Created: 2012-05-17

Credits: Matej Mihelčić Matko Bošnjak