AID2011-11-22T12:34:36+00:00/groups/422009-08-24T11:07:00+00:00Jan Top joined the AID groupurn:uuid:26092fc1-5d6b-4875-9ebb-9ca423d9a447Jan Top2009-05-26T16:11:44+00:00Edgar shared Index MyExperiment WorkflowThis workflow uses AIDA components to index all of the workflows on MyExperiment. First, it lists and downloads each workflow's xml file. Then, the titles and descriptions are parsed and submitted to an Indexer webservice. After it's finished, your index will be searchable by visiting http://aida.science.uva.nl:9999/search. >urn:uuid:ca408e1e-58da-4645-9d47-4d47015a5d19Edgar2009-05-15T15:45:34+00:00Marco Roos shared Supporting material for Roos et al., BMC Bioinformatics, SWAT4LS supplement (2009)Supporting material for BMC Bioinformatics, supplement for Semantic Web Applications and Tools for Life Science (2009) Structuring and extracting knowledge for the support of hypothesis generation in molecular biology Marco Roos , M. Scott Marshall , Andrew P. Gibson , Martijn Schuemie , Edgar Meij , Sophia Katrenko , Willem Robert van Hage , Konstantinos Krommydas, Pieter W. Adriaans Acknowledgements We thank the myGrid team and OMII-UK for their support in applying their e-Science tools, and Machiel Jansen for his contribution to the early development of AIDA. This work was carried out in the context of the Virtual Laboratory for e-Science program (VL-e) and the BioRange program. These programs are supported by BSIK grants from the Dutch Ministry of Education, Culture and Science (OC&W). …urn:uuid:86a96716-7d15-4ca7-bae2-fa54ddc9ae7eMarco Roos2008-12-14T21:35:46+00:00Marco Roos shared AIDA demo pack Pack with AIDA demo materialurn:uuid:c974ba37-7d67-4f21-b59a-3f87b3b92cd4Marco Roos2008-08-22T11:00:51+00:00Marco Roos shared BioAID_EnirchBioModelWithProteinsFromTextThis workflow is for demonstration purposes only. Please contact the authors if you wish to try it. We will gladly collaborate with you. Summary This workflow extracts proteins and protein relations from Medline. Extracted protein names (symbols of at least 3 characters) are validated against mouse, rat, and human UniProt symbols, so the results are limited to these species. This workflow follows the following basic steps: it retrieves documents relevant for the query string it discovers proteins in those documents, that are considered relevant to the query string and related to the proteins mentioned in the query (colocation in text mining jargon) it stores the results in a semantic repository To support hypothesis formation, the results are added to a repository containing proto-ontologie …urn:uuid:09d33d3e-4685-492b-b789-d260e9e370baMarco Roos2008-08-01T11:33:04+00:00Marco Roos shared AIDA toolboxAdaptive Information Disclosure Application toolbox: AIDA web services for automated knowledge extraction and knowledge management Documentation urn:uuid:469e7a60-e724-41e9-800b-72bb2bb86c08Marco Roos2008-03-21T19:00:27+00:00Marco Roos shared From biologist to web service to Taverna to myExperiment to biologistA movie to show the principle of the round trip from a biology question via pieces of code wrapped as web services and combined into a workflow (computational experiment) in Taverna, via uploading to myExperiment and back to the biologist through myExperiment's run facility. NB: at the time of uploading this movie the runner-option was in test-phase. It is important to note that the workflow combines the work of various scientists with different expertise and some at remote locations around the globe. Making services and workflows is not easy, but this enhanced collaborative computation is much harder without e-science technology and tools such as Taverna and myExperiment. The movie was made for the ' NBIC on workflows ' workshop in Lunteren, The Netherlands. Many thanks to the myGrid team …urn:uuid:e731a252-ff48-4a5c-84a9-802d8393c037Marco Roos2008-02-29T01:34:48+00:00Marco Roos shared BioAID_ProteinDiscovery_filterOnHumanUniprot_perDoc_htmlThis workflow finds proteins relevant to the query string via the following steps: A user query: a single gene/protein name. E.g.: (EZH2 OR "Enhancer of Zeste"). Retrieve documents: finds 'maximumNumberOfHits' relevant documents (abstract+title) based on query (the AIDA service inside is based on Apache's Lucene) Discover proteins: extract proteins discovered in the set of relevant abstracts with a 'named entity recognizer' trained on genomic terms using a Bayesian approach; the AIDA service inside is based on LingPipe. This subworkflow also 'filters' false positives from the discovered protein by requiring a discovery has a valid UniProt ID. Martijn Schuemie's service to do that contains only human UniProt IDs, which is why this workflow only works for human proteins. Workflow by Marco Roo …urn:uuid:cdb85f41-2c43-459d-b87c-3d3ac0ae3426Marco Roos2007-12-10T22:05:27+00:00Sophia katrenko joined the AID groupurn:uuid:1dc59ae9-5353-454f-8b01-c55562014d41Sophia katrenko2007-12-10T22:05:14+00:00Willem van Hage joined the AID groupurn:uuid:98b26149-115e-402e-acf9-bc8f517b4ee8Willem van Hage2007-11-15T09:40:24+00:00Marco Roos shared BioAID_Discover_proteins_from_text_plus_synonymsThis workflow discovers proteins from plain text and adds synonyms using Martijn Schuemie's proteins synonym service. Proteins are discovered with the AIDA 'Named Entity Recognize' web service by Sophia Katrenko (service based on LingPipe), from which output it filters out proteins. The Named Recognizer services uses the pre-learned genomics model, named 'MedLine', to find genomics concepts in plain text.urn:uuid:9150cf28-f182-47d8-8408-9e4f38a77920Marco Roos2007-11-15T09:04:28+00:00Marco Roos shared Discover_proteins_from_textThis workflow discovers proteins from plain text. It is built around the AIDA 'Named Entity Recognize' web service by Sophia Katrenko (service based on LingPipe), from which output it filters out proteins. The Named Recognizer services uses the pre-learned genomics model, named 'MedLine', to find genomics concepts in plain text.urn:uuid:bd6fbcfe-133a-4d7e-ba36-b9b00afe07f8Marco Roos