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

Download Structures from PubChem given che... (1)

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This workflow takes the input file containing chemical names and returns a single SDF file of structures. The names are searched against pubchem compounds via e-search. If the compound name is found an XML file containing PubChem ID is returned.The max return compound_ID is set to 1 which could be increased. If the compound name is not found then no ID is returned.  The pubchem compound_ID is then used to download structures from PubChem.  

Created: 2011-05-24 | Last updated: 2011-05-24

Credits: Kalai Michael Gerlich

Attributions: Download Entries from PubChem

Frequent Itemset and association rules ana... (1)

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Generates frequent itemsets and association rules from the gene data. Frequent itemsets correspond to different gene characteristics (locations and functions) that frequently occur together across different genes. The quality of a frequent itemset is given by its support which is the fraction of genes for which a given combination of gene characteristics hold; the longer the itemset the lower its support. Based on the frequent itemset this WF also generates association rules which have some...

Created: 2011-05-23 | Last updated: 2011-05-24

Prepares data for gene correlation analysis (1)

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Prepares data for gene correlation analysis.

Created: 2011-05-23 | Last updated: 2011-05-23

Prepares data for the analysis of fibrosis... (1)

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Prepares gene data for fibrosis by joining datasets from different studies on fibrosis across various organs including the kidney.

Created: 2011-05-23 | Last updated: 2011-05-25

Get names of proteins similar to RNA bindi... (1)

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A very simple demo workflow using some existing SADI services. It finds UniProt proteins of GO function "RNA Binding", it then runs a BLAST service to find similar UniProt proteins and then outputs their names.

Created: 2011-05-18 | Last updated: 2011-05-18

Credits: hindlem

EBI PICR, find cross-references for protei... (2)

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Find cross-references (based on 100% sequence identity) for protein accessions from more than 95 distinct databases. For instance input a list of IPI accessions and find cross-references for Swissprot and Ensembl. Mappings can be limited by source database, taxonomic ID and activity status.

Created: 2011-05-18 | Last updated: 2011-05-29

Credits: Rafael C. Jimenez

Example for external tools with gzip and g... (1)

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This workflow is self-contained. It has a fixed URL from which a text file is downloaded (output as Original_file). That file is gzipped (output as Compressed_File) and then gunzipped again (output as Decompressed_File). The workflow wraps external tools from taverna.nordugrid.org and needs a beta version of Taverna 2.3 or later.

Created: 2011-05-18 | Last updated: 2011-05-18

Credits: Steffen Möller Alan Williams

Molecular Interactions from IntAct PSICQUI... (2)

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Get molecular interaction data in psi-mitab25 from IntAct through its PSICQUIC service. As input you can use an Uniprot Acc like "P99999" or a MIQL query like "alias:(KHDRBS1 OR HCK)". This workflow finds by itself how many queries needs to make (SOAP service limited to 200 binary interactions per call) to be able to return all the results in one file.

Created: 2011-05-17 | Last updated: 2011-07-20

Credits: Rafael C. Jimenez

Plotting distribution of natural product l... (1)

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 Prerequisite:  CDK -Taverna Plugin 0.5.1 http://www.ts-concepts.de/cdk-taverna2/plugin/ - To run this workflow you need a Score file which is written to text file.  - This could be generated from ScorerActivity.t2flow http://www.myexperiment.org/workflows/2121/download?version=1   Description of input ports : score_file: Path to file name that has pre computed scores. Note: While passing file as input it could be passed as list of many files or single fi...

Created: 2011-05-13 | Last updated: 2011-05-13

Credits: Kalai

Generate Atom Signatures of molecules give... (1)

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Reference: Natural Product-likeness Score and Its Application for Prioritization of Compound Libraries Peter Ertl,* Silvio Roggo, and Ansgar Schuffenhauer Novartis Institutes for BioMedical Research, CH-4002 Basel, Switzerland http://peter-ertl.com/reprints/Ertl-JCIM-48-68-2008.pdf    The natural product likeness scorer implemented by Peter Ertl was originally devised to screen large compound libraries for natural product likeness in drug designing studies. His work is re...

Created: 2011-05-13 | Last updated: 2011-05-13

Credits: Kalai

Extract chemical structures from a Beilste... (1)

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 Uses the Oscar4 text mining tool to extract chemical structures from a Beilstein Journal of Organic Chemistry paper and visualizes them in the molecules table. Jericho is used to extract text from the paper's HTML page.

Created: 2011-05-12 | Last updated: 2011-05-12

Credits: Egon Willighagen

SVD user-based collaborative filtering rec... (1)

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This workflow takes user-item matrix A as a input. Then it calculates reduced SVD decomposition A_k by taking only k greatest singular values and corresponding singular vectors. This worfkflow calculates recommendations and predictions for particular user %{id} from matrix A. Particular row %{id} is taken from original matrix A and replaced with %{id} row in A_k matrix. Predictions are made for %{id} user based on another users A_k. Note: This workflow uses R-script operator with R library ...

Created: 2011-05-09 | Last updated: 2011-05-09

Credits: Ninoaf Matko Bošnjak

Attributions: User-based collaborative filtering recommender system template Datasets for the pack: RCOMM2011 recommender systems workflow templates

LSI content based recommender system template (1)

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This workflow performs LSI text-mining content based recommendation. We use SVD to capture latent semantics between items and words and to obtain low-dimensional representation of items. Latent Semantic Indexing (LSI) takes k greatest singular values and left and right singular vectors to obtain matrix  A_k=U_k * S_k * V_k^T. Items are represented as word-vectors in the original space, where each row in matrix A represents word-vector of particular item. Matrix U_k, on the other hand ...

Created: 2011-05-06 | Last updated: 2011-05-09

Credits: Ninoaf Matko Bošnjak

Attributions: Content based recommender system template Datasets for the pack: RCOMM2011 recommender systems workflow templates

External Tool: Numerically adding two valu... (1)

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The workflow is an examples for the External Tools / UseCase plugin to integrate external tools. It wraps the "bc" command line calculator. Internally, it executes the following script: if [ ! -r "$1" ]; then echo "Cannot read file indicated by first argument '$1'." ; exit -1 ; fi ; if [ ! -r "$2" ];then echo "Cannot read file indicated by second argument '$1'." ; exit -1 ; fi if [ -x /usr/bin/bc ]; then ...

Created: 2011-05-06 | Last updated: 2011-05-06

Credits: Steffen Möller

Item-based collaborative filtering recomme... (1)

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The workflow for item-based collaborative filtering receives a user-item matrix for its input, and the same context defined macros as the user-based recommender template, namely %{id}, %{recommendation_no}, and %{number_of_neighbors}. Although this process is in theory very similar to user-based technique, it differs in several processing steps since we are dealing with an item-user matrix, the transposed user-item example set. The first step of the workflow, after declaring zero values miss...

Created: 2011-05-05 | Last updated: 2011-05-09

Credits: Matko Bošnjak Ninoaf

Attributions: Datasets for the pack: RCOMM2011 recommender systems workflow templates

User-based collaborative filtering recomme... (1)

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The workflow for user-based collaborative filtering, takes only one example set as an input: a user-item matrix, where the attributes denote item IDs, and rows denote users. If a user i has rated an item j with a score s, the matrix will have the value s written in i-th row and j-th column. In the context of the process we define the ID of the user %{id}, desired number of recommendations %{recommendation_no}, and the number of neighbors used in ca...

Created: 2011-05-05 | Last updated: 2011-05-09

Credits: Matko Bošnjak Ninoaf

Attributions: Datasets for the pack: RCOMM2011 recommender systems workflow templates

Content based recommender system template (1)

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As an input, this workflow takes two distinct example sets: a complete set of items with IDs and appropriate textual attributes (item example set) and a set of IDs of items our user had interaction with (user example set). Also, a macro %{recommendation_no} is defined in the process context, as a required number of outputted recommendations. The first steps of the workflow are to preprocess those example sets; select only textual attributes of item example set, and set ID roles on both of th...

Created: 2011-05-05 | Last updated: 2011-05-09

Credits: Matko Bošnjak Ninoaf

Attributions: Datasets for the pack: RCOMM2011 recommender systems workflow templates

CGR from multiple fasta files (1)

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 The workflow generates Chaos Game Represenations (CGR) image from multiple fasta files. See http://www.g-language.org/wiki/cgr for more information about the Chaos Game Representations.

Created: 2011-04-29 | Last updated: 2011-04-29

Credits: cory (Kazuki Oshita)

Voronoi polygon generation using GRASS-GIS... (1)

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Generic example on how to deal with vectorial data. Major pitfall is the need to process ProcessOutputs using Xpath plugin. A random point file in GML 2.1.2 is sent to the v.voronoi service and after it is sent to a service that runs v.out.svg generating a SVG image that can be rendered in Taverna (need to set output to SVG image)

Created: 2011-04-27 | Last updated: 2011-04-27

Credits: Jorgejesus

[untitled] (1)

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This workflow allows the user to search for processes that are involved with a certain gene. Using microarray-files (CEL-files), consisting of wild type and KO mice to which a stimulant is induced, the user can get an idea of the processes involved. (This is done using the global test and the literature weighted global test.) The results are then given as a text-file. Warning: workflow is not working (needs some revisions), all input is currently hardcoded! (You will have to change the file...

Created: 2011-04-26 | Last updated: 2011-04-26

Credits: Dennis Leenheer

Gene expression interpretation by the Glob... (1)

This workflow adds meaning to gene expresion values by performing a standard and a literature weighted Global Test. Gene expression is expected to be from Affymetrix microarrays, for which an RMA normalization and entrez Gene ID mapping/summation is performed. Original workflow is by Dennis Leenheer, edits by Marco Roos. Scripts by Kristina Hettne, acknowledging Rob Jellier, Jelle Goeman, and Peter-Bram 't Hoen. The workflow was created for the LUMC BioSemantics group, part of the Human Gen...

Created: 2011-04-26 | Last updated: 2011-04-26

Credits: Marco Roos

Remove_Duplicates (1)

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This workflow removes any duplicates from a list of inputs, merges the unique values, and then removes any null values.

Created: 2011-04-21 | Last updated: 2011-04-21

Credits: Paul Fisher

Magnetic Resonance Image simulation with S... (1)

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Created: 2011-04-18 | Last updated: 2011-04-18

Credits: Glatard

Positron Emission Tomography simulation wi... (1)

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This workflow implements Positron Emission Tomography simulation with PET-Sorteo http://sorteo.cermep.fr/. It is developped by the Virtual Imaging Platform (http://www.creatis.insa-lyon.fr/vip).

Created: 2011-04-18 | Last updated: 2011-04-18

Credits: Glatard

Computed Tomography with Sindbad (1)

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This workflow implements computed tomography (CT) simulation with the Sindbad software. It is developped by the Virtual Imaging Platform (http://www.creatis.insa-lyon.fr/vip).

Created: 2011-04-18 | Last updated: 2011-04-18

Credits: Glatard

FIELD-II ultrasound simulation (1)

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Workflow implementing ultrasound simulation using FIELD-II http://server.electro.dtu.dk/personal/jaj/field/. Developped by the Virtual Imaging Platform (http://www.creatis.insa-lyon.fr/vip).

Created: 2011-04-18

Credits: Glatard

M_Super_aln_boot_phylo_New (1)

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This workflow performs a generic protein sequence analysis. A multiple sequence alignment and finally a phylogenetic analysis.This workflow performs a generic protein sequence analysis. In order to do that a novel protein sequence enters into the software along with a list of known protein identifiers chosen by the biologist to perform a homology search, followed by a multiple sequence alignment and finally a phylogenetic analysis.This workflow performs "parallel" generic protein sequence ana...

Created: 2011-04-18 | Last updated: 2011-04-18

Credits: Achille Zappa

Attributions: EMBL-EBI ClustalW2 (SOAP)

GRASS-GIS orchestration using pyWPS (2)

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Generic workflow that run r.watershed, with auxiliary services: r.math and geotiff2png. Watershed accumulation is calculated from DEM using r.watershed, the accumulation result is then filtered using r.math with equation:output=(if(a>10,a,null())) Generic workflow that run r.watershed, with auxiliary services: r.math and geotiff2png. Watershed accumulation is calculated from DEM using r.watershed, the accumulation result is then filtered using r.math with equation: output=(if(a>10,...

Created: 2011-04-18 | Last updated: 2011-04-25

Credits: Jorgejesus

Create Linear Combinations (1)

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This process creates new attributes based on all combinations of coefficients for two attributes, i.e. it produces all linear combinations c1 * att1 + c2 * att2 by looping through a set of possible values for c1 and c2 and all their different combinations.

Created: 2011-04-08

Blast Report from ID (1)

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This workflow retrieves a fasta sequence or blast report from an id. Firstly, given some inputs (e.g. ids:EDL10223.1, format:fasta, style:default and db:emblcds), it returns the sequence in fasta format associated to those inputs using the EBI's WSDbfetch web service (see http://www.ebi.ac.uk/Tools/webservices/services/dbfetch). Next, we obtain a Blast report from this fasta sequence and some others parameters. The final result in that case corresponds with the same fasta sequence introduced...

Created: 2011-04-07 | Last updated: 2011-04-07

Credits: Hectorj2f

Quality control processing of GEO datasets (2)

The workflow performs a quality control process on gene expression data sets stored in the Gene Expression Omnibus database. The QC process is performed using Bioconductor R packages. A variety of statistics are produced by the workflow including a diagnostic plot from snm normalisation and nucleotide composition bias.

Created: 2011-04-06 | Last updated: 2011-04-11

Credits: Peter Li Bhmecham

Mouse Brain Image Analysis: General Linear... (1)

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Overview - General Linear Model The workflow runs voxelwise statistics on two populations of mice. Each of the populations has been scanned prior to injection of a label and at four subsequent timepoints.   Problem addressed by this workflow The workflow addresses several problems. First of all, it performs co-registration between the subjects from the two populations and at different timepoints. It then scales all images. Finally, it runs a multiple linear regression module t...

Created: 2011-04-06 | Last updated: 2011-04-06

Credits: Pipeline

Automated BrainSuite Cortical Surface Extr... (1)

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Overview - BrainSuite Cortical Surface Extraction The workflow takes a skull stripped volume as input and runs a multi-stage process, extracting the cortical surface and splitting it into hemispheres.   Problem addressed by this workflow Generating a shape model of the cortical surface from a 3D volume.   Detailed Workflow Usage & Specifications Tissue Classification The next step in the Brainsuite09 cortical surface identification sequence is tissue classificatio...

Created: 2011-04-06 | Last updated: 2011-04-06

Credits: Pipeline

First Level within subject fMRI processing (1)

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Overview - fMRI-FEAT workflow This is a simple with-in subject fMRI analysis workflow. It takes 3D fMRI images and structural images of a subject and performs FSLmerge, BET (if the data is not already skull stripped) and first level FEAT processing.   Problem addressed by this workflow FSLMerge, BET and FEAT first level analysis can be performed using this workflow on one or more subjects that require the same processing. The design FSF file is generate using the FSL FEAT inte...

Created: 2011-04-06 | Last updated: 2011-07-14

Credits: Pipeline

Image Registration Meta Algorithm (IRMA) (1)

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Overview - Workflow-Title In this workflow different registration algorithms are applied to the same image and the image that is best registered to the template is chosen as the output top candidate.   Problem addressed by this workflow In this workflow various registration algorithm is performed on the same subject. The algorithm that gives the best result is chosen. This might be different for different input images. This workflow is robust and picks the best-registered imag...

Created: 2011-04-06 | Last updated: 2011-07-14

Credits: Pipeline

Direct Hippocampal Mapping (1)

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Overview - Direct Hippo Mapping The workflow takes volumetric masks of hippocampi from two groups, generates surfaces from each mask, and maps these surfaces to a hippocampal atlas. It also computes thickness and displacement feature on the surfaces and evaluates the statistical significance of the differences between the two groups with respect to these measurements.   Problem addressed by this workflow Automatically establishing correspondences between points on hippocampal ...

Created: 2011-04-06 | Last updated: 2011-04-06

Credits: Pipeline

BrainParser: Automated Volume Calculation ... (1)

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This workflow takes raw un-skull-stripped volumes and generates tables of the volumes for all 56 ROIs currently automatically extracted using LONI BrainParser.   Problem addressed by this workflow Computing and tabulating the Brain Volumes of 56 cortical and sub-cortical ROIs. This workflow also generates DX models of all 56 ROIs which can be viewed as a scene in ShapeViewer.   Detailed Workflow Usage & Specifications Input: Any volumetric file format can be use...

Created: 2011-04-06 | Last updated: 2011-04-06

Credits: Pipeline

Automated Brain Tissue Extraction and Volu... (1)

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This workflow takes raw un-skull-stripped volumes and generates tables of the volumes for all 56 ROIs currently automatically extracted using LONI BrainParser.   Problem addressed by this workflow Computing and tabulating the Brain Volumes of 56 cortical and sub-cortical ROIs. This workflow also generates DX models of all 56 ROIs which can be viewed as a scene in ShapeViewer.   Detailed Workflow Usage & Specifications Input: Any volumetric file format can be use...

Created: 2011-04-06 | Last updated: 2011-07-14

Credits: Pipeline

Minimum Deformation Template (MDT) Atlasin... (1)

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This pipeline present the redesigned automated workflow for constructing the Minimum Distance Template (MDT) atlas for a given population, based on one specific image modality (e.g., sMRI). There will be two specific validation examples based on 100+ ICBM subjects: Quantitative: The ICBM data will be registered to the MDT, NRU and ICBM 462 atlases and mean displacement stats across all subjects will be reported for each voxel. The distributions of these mean displacement magnitud...

Created: 2011-04-06 | Last updated: 2011-07-14

Credits: Pipeline

Automated Cortical Surface Extraction Work... (1)

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This workflow takes raw un-skull-stripped volumes and generates a cortical surface model using FreeSurfer? and CCB tools. Problem addressed by this workflow There are many ways to generate cortical surface models based on MRI data. Here is one of them. Eventually, there will be a new Learning-based Cortical Surface Modeling Pipeline, as well.   Input is Raw MRI T1-weighted volume CCB/FreeSurfer Cortical Surface extractor that the SIG-Shape team developed and we validated ...

Created: 2011-04-06 | Last updated: 2011-07-14

Credits: Pipeline

Local Shape Analysis (LSA) Workflow (1)

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This workflow takes raw un-skull-stripped volumes in 2 groups/populations and an ROI index to generate a color-coded shape object using the per-vertex local p-values of some local shape-measure (e.g., displacement, atrophy, Jacobian, curvature, etc). It also outputs the p-values color-map superimposed on the mean shape. Problem addressed by this workflow   Identifying local group differences between 2 populations in one specific ROI. This workflow also generates mean-shape DX mo...

Created: 2011-04-06 | Last updated: 2011-04-06

Credits: Pipeline

Automated Image Registration (1)

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This is a simple registration workflow. The structural MRI images are aligned to a standard brain image by using AIR registration tools. To build this workflow follow the steps mentioned on the following pages. URL: http://www.loni.ucla.edu/Software/AIR Try this Pipeline Workflow Now!

Created: 2011-04-06 | Last updated: 2011-04-06

Credits: Pipeline

Sub-Volume Probabilistic Atlas Segmentaito... (1)

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This workflow takes a raw unskull-stripped volume and a brain mask of the volume to create a tissue segmented image.This workflow is based on a novel genetic algorithm based finite mixture model and a local 3D Markov random field segmentation algorithm based on iterative conditional modes algorithm. Problem addressed by this workflow   This workflow performs tissue segmentation on the brain volumes using genetic algorithm based finite mixture model (GAMIXTURE), local 3D Markov ...

Created: 2011-04-06 | Last updated: 2011-04-06

Credits: Pipeline

Global Shape Analysis Workflow (1)

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This workflow takes raw un-skull-stripped volumes in multiple groups/populations, or a Study-Design, and generates a scene file containing the models of the ROIs where the groups are different. It also reports the global 56 regional p-values. Problem addressed by this workflow   Identifying the group differences between 2 populations in the global shapes of 56 cortical and sub-cortical ROIs. This workflow also generates DX models of all 56 ROIs which can be viewed as a scene in Sh...

Created: 2011-04-06 | Last updated: 2011-04-06

Credits: Pipeline

Microsatellite-based Ancestry and Parentag... (1)

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GENEPOP is genetics software package that does the following types of analyses: Hardy Weinberg Exact Tests Linkage Disequilibrium Population Differentiation Nm estimates Basic Information, Fis and gene diversities Fst & other correlations File Conversion Additional Miscellaneous Utilities     Problems addressed by this GENEPOP workflow This specific GENEPOP workflow computes the following: Testing : Hardy-W...

Created: 2011-04-05 | Last updated: 2011-07-14

Credits: Pipeline

Integrated Mapping and Assembly with Quali... (1)

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This workflow contains the first step of a genomics data analysis protocol designed and implemented by Federica Torri, Fabio Macciardi and Ivo Dinov to process large number of sequence data outputted by the Illumina sequencing pipeline. See Step II analysis (GATK/QC/Cleaning) here. This protocol is implemented using the LONI Pipeline environment and includes the following types of computational resources: Mapping and Assembly with Qualities (MAQ) Sequence Alignment and Mapping t...

Created: 2011-04-05 | Last updated: 2011-04-05

Credits: Pipeline

PLINK Association workflow (1)

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PLINK is an open-source genome association analysis (GWAS) suite of tools providing a range of basic, large-scale computationally-efficient analyses. PLINK may be used for analysis of genotype/phenotype data, but requires some outside data-preprocessing (e.g., study design and planning, generating genotype or CNV calls from raw data). Support for visualization, annotation and storage of results is provided via gPLINK and Haploview.   The PLINK Association workflow provides testi...

Created: 2011-04-05 | Last updated: 2011-07-14

Credits: Pipeline

GWASS Impute (1)

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Genome-wide Association Study Software (GWASS) package provides genomics tools facilitating the analysis of genome-wide association studies. These tools were used in the design and analysis of the 7 genome-wide association studies carried out by the Wellcome Trust Case-Control Consortium (WTCCC)   IMPUTE2 is a GWASS program for phasing observed genotypes and imputing missing genotypes. It includes basic and advanced functions. URL: http://www.loni.ucla.edu/twiki/bin/view/CCB/Pipe...

Created: 2011-04-05 | Last updated: 2011-04-05

Credits: Pipeline

mrFAST Indexing and Mapping (1)

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This page contains a number of bioinformatics workflows based on the mrFAST sequence analysis package. This page describes Pipeline bioinformatics modules from the mrFAST suite.   mrFAST (micro-read Fast Alignment Search Tool) is mapper designed to map short reads to reference genome with a special emphasis on the discovery of structural variation and segmental duplications. mrFAST maps short reads with respect to user defined error threshold, including indels up to 6 bp. This manu...

Created: 2011-04-05 | Last updated: 2011-04-05

Credits: Pipeline

EMBOSS-Matcher Pipeline Workflow (1)

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This page contains a number of bioinformatics workflows based on the advanced EMBOSS informatics package. This page describes as Pipeline modules several bioinformatics tools from the EMBOSS suite and demonstrates the construction of a couple of integrated pipeline workflows (end-to-end bioinformatics solutions via the LONI Pipeline). Matcher finds the best local alignments between two sequences. It can be used to compare two sequences looking for local sequence similarities using a ri...

Created: 2011-04-05 | Last updated: 2011-07-14

Credits: Pipeline

Bioinformatics BLAST processing Workflow (1)

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This is a simple workflow demonstrating a sequence Basic Local Alignment Search Tool (BLAST). This workflow shows an example of a common bioinformatics pipeline workflow using tools from several different institutions. This workflow starts by formatting the NCIBI/NCBI Escherichia coli (E. coli) database, creating a database-index table, using a FASTA query instructions to create a filtering file, and finally running miBLAST, an efficient Basic Local Alignment Search Tool (BLAST) for batc...

Created: 2011-04-05 | Last updated: 2011-04-05

Credits: Pipeline

Parsed UniProt to PubMed (1)

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Uses the parsed Uniprot results (see workflow http://www.myexperiment.org/workflows/26.html) to retrieve information from PubMed.

Created: 2011-04-01 | Last updated: 2011-04-01

Credits: Morgan Taschuk

Use UniProt to retrieve InterPro data (1)

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Used parsed Uniprot results (see workflowUsed parsed Uniprot results (see workflow http://www.myexperiment.org/workflows/26.html) to retrieve results about the protein from InterPro.

Created: 2011-04-01

Credits: Morgan Taschuk

UniProt to Gene Ontology (1)

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Used parsed Uniprot results (see workflow http://www.myexperiment.org/workflows/26.html) to retrieve results about the protein from Gene Ontology and outputs it in text format.

Created: 2011-04-01 | Last updated: 2011-04-01

Credits: Morgan Taschuk

Print Protein Information to HTML (1)

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Takes in a lot of parameters in order to construct an HTML table to display the information.

Created: 2011-04-01

Credits: Morgan Taschuk

Odkrywanie reguł asocjacyjnych za pomocą... (1)

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Proces pokazuje wykorzystanie algorytmu FP-Growth do odkrywania reguÅ‚ asocjacyjnych. Należy zwrócić uwagÄ™ na to, że implementacja algorytmu FP-Growth akceptuje jedynie atrybuty binominalne, zatem zachodzi konieczność zamiany wszystkich atrybutów numerycznych i nominalnych na binominalne.

Created: 2011-03-30 | Last updated: 2011-03-30

Vaccine Targets Workflow (3)

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Comparison of the genome of Bacillus anthracis to closely related strains will allow the discovery of proteins which may be involved in pathogenicity. Based on the biochemical pathways where the protein interacts, vaccines can be designed for these unique proteins. By gaining insight into the biochemical pathways that the unique proteins are involved in, the proteins can also be assessed for potential quality as vaccines. The key components of the vaccine finding system are the following: T...

Created: 2011-03-30 | Last updated: 2011-04-01

Credits: Morgan Taschuk A Team

Compile Protein FASTA from Target to Drug ... (1)

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Uses a tab-delimited file with protein target and drug information (created in Ondex) to compile a protein FASTA file including each target.

Created: 2011-03-30 | Last updated: 2011-03-30

Credits: Morgan Taschuk Andrewsmeaton

Print Analysis Information to HTML (2)

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Takes in a lot of parameters in order to construct an HTML header to display the information.

Created: 2011-03-29 | Last updated: 2011-04-01

Credits: Morgan Taschuk

gene subset extract (1)

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This workflow functions for matching a set of genes as a part of whole gene data set and aim to extract the subset as a separate list.

Created: 2011-03-29 | Last updated: 2011-03-29

Credits: Naser Paul Fisher

KEGG Pathways and Additional Information f... (2)

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Takes in a tab-delimited BLAST file and finds additional information about the target proteins from KEGG, Gene Ontology, Interpro and PubMed.

Created: 2011-03-29 | Last updated: 2011-03-30

Credits: Morgan Taschuk

Attributions: extract_uniprot_embl_gi.xml

NCBI Gi to Kegg Pathways (1)

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"This workflow gets a series of information relating to a list of KEGG genes supplied to it. It also removes any null values from a list of strings."This workflow gets a series of information relating to a list of KEGG genes supplied to it. It also removes any null values from a list of strings.

Created: 2011-03-28 | Last updated: 2011-03-28

Credits: Alibukhari

Threshold BLAST results (2)

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Thresholds tab-delimited BLAST results to a certain percent identity.

Created: 2011-03-28 | Last updated: 2011-04-01

Credits: Morgan Taschuk A Team

ADR-S (2)

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  The ADR-S pathway seeks to establish a connection between the clinical event and the drug through different paths: (i) through proteins in common among the proteins that are drug targets or metabolite targets and proteins associated to the clinical event (ii) through proteins that are drug targets or metabolite targets and proteins associated to the clinical event that participate in a common biological pathway. The workflow proceeds as follows: First, it checks if there are pr...

Created: 2011-03-28 | Last updated: 2011-08-09

Credits: Anna Bauer-Mehren

Gene function prediction in Macaca Fasciculus (1)

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This workflow searches for ORF regions in a specific gene (TOM1L1 in Macaca fasciculus testis) to predict candidate protein coding regions. Results from blastp are used to find which frames are closest to existing proteins in other species. rpsblast is used to predict the domains and the protein families that these sequences may belong to. This is used to predict the function of the protein.

Created: 2011-03-27 | Last updated: 2011-03-27

Credits: Kalpana

Drug Re-Purposing Workflow (6)

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The drug repurposing workflow system screens at least 20 bacterial proteomes against this set of proteins that are already being treated against using established drugs. By screening the bacterial proteomes it will be possible to find proteins of highly similar structure to those that are existing drug protein targets and so this will infer that it is highly likely that the drugs can be used as antimicrobials against these proteins of highly similar structure. Proteomes that will be screene...

Created: 2011-03-25 | Last updated: 2011-04-01

Credits: Morgan Taschuk A Team

Extract unique proteins from blast results (4)

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The workflow parses uses the tab-delimited BLAST results to determine the unique proteins found in the target genome that have no similarity to the source genome.The workflow parses uses the blast results to determine the unique proteins found in the target genome that have no similairty to the source genome. Using these unique protein ids, and the original target protein fasta file, a fasta file of unique proteins is created.This workflow allows you to configure a BioMart query to fetch sequ...

Created: 2011-03-24 | Last updated: 2011-04-01

Credits: Morgan Taschuk A Team

Attributions: Parse unique proteins from Blast file

Pathways and Gene annotations forQTL region (1)

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This workflow searches for genes found from a set of differentially expressed probestes, in Human, Homo sapiens. The workflow requires an input human affymetrix probeset identifiers. 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 database.

Created: 2011-03-24 | Last updated: 2011-03-24

Credits: Paul Fisher

XPath Pubmed Ids (2)

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This workflow takes in a search term (as used in the normal PubMed interface) and retrieves a list of PubMed ids in xml. The xml is then parsed to retrieve a list of PubMed ids

Created: 2011-03-23 | Last updated: 2011-03-30

Credits: Paul Fisher

Attributions: XPath Pubmed Ids

XPath Pubmed Ids (1)

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This workflow takes in a search term (as used in the normal PubMed interface) and retrieves a list of PubMed ids in xml

Created: 2011-03-23 | Last updated: 2011-03-23

Credits: Paul Fisher

Wybór atrybutów na podsatwie algorytmu z... (1)

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Workflow pokazuje użycie algorytmu zachÅ‚annego do wyboru cech. Algorytm może wykonywać zarówno wyboru progresywnego (forward selection) jak i selekcji wstecznej (backward selection). Do oceny jakoÅ›ci rozwiÄ…zania algorytm wykorzystuje klasyfikator k-najbliższych sÄ…siadów i 10-krotnÄ… walidacjÄ™ krzyżowÄ….

Created: 2011-03-23 | Last updated: 2011-03-23

Wybór atrybutów na podstawie algorytmu g... (1)

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Workflow przedstawia wykorzystanie algorytmu genetycznego do znalezienia optymalnego zbioru atrybutów. Wybór atrybutów odbywa siÄ™ na podstawie sprawdzenia jakoÅ›ci klasyfikacji. Wykorzystanym klasyfikatorem jest algorytm k-najbliższych sÄ…siadów, zbiór danych jest dzielony na zbiór uczÄ…cy i zbiór testujÄ…cy w proporcji 70%-30%. WyjÅ›ciowy algorytm genetyczny wykorzystuje populacje o rozmiarze 10, ograniczajÄ…c liczbÄ™ pokoleÅ„ do 30.

Created: 2011-03-23 | Last updated: 2011-03-23

Pathways and Gene annotations forQTL region (2)

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This workflow searches for genes which reside in a QTL (Quantitative Trait Loci) region in Human, Homo sapiens. 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 ...

Created: 2011-03-17 | Last updated: 2011-08-30

Credits: Paul Fisher

Attributions: Pathways and Gene annotations for QTL region

InterproScan without Looping (1)

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This workflow performs an interproscan at the EBI on sequences provided as input. The output is provided as text 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. This workflow will not work properly until we add looping.

Created: 2011-03-16 | Last updated: 2012-08-29

Credits: Katy Wolstencroft

Collaborative filtering recommender (1)

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This process executes a collaborative filtering recommender based on user to item score matrix. This recommender predicts one user’s score on some of his non scored items based on similarity with other users. The inputs to the process are context defined macros: %{id} defines an item ID for which we would like to obtain recommendation and %{recommender_no} defines the required number of recommendations and %{number_of_neighbors} defines the number of the most similar users taken into a...

Created: 2011-03-15 | Last updated: 2012-03-06

Content based recommender (1)

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This process is a special case of the item to item similarity matrix based recommender where the item to item similarity is calculated as cosine similarity over TF-IDF word vectors obtained from the textual analysis over all the available textual data. The inputs to the process are context defined macros: %{id} defines an item ID for which we would like to obtain recommendation and %{recommender_no} defines the required number of recommendations. The process internally uses an example set of...

Created: 2011-03-15 | Last updated: 2011-03-15

Item to item similarity matrix -based reco... (1)

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This process executes the recommendation based on item to item similarity matrix. The inputs to the process are context defined macros: %{id} defines an item ID for which we would like to obtain recommendation and %{recommender_no} defines the required number of recommendations. The process internally uses an item to item similarity matrix written in pairwise form (id1, id2, similarity). The process essentially filters out appearances of the required ID in both of the columns of the pairwis...

Created: 2011-03-15 | Last updated: 2011-03-15

Random recommender (1)

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This process does a random item recommendation; for a given item ID, from the example set of items, it randomly recommends a desired number of items. The purpose of this workflow is to produce a random recommendation baseline for comparison with different recommendation solutions, on different retrieval measures. The inputs to the process are context defined macros: %{id} defines an item ID for which we would like to obtain recommendation and %{recommender_no} defines the required number of ...

Created: 2011-03-15 | Last updated: 2011-03-15