Difference between revisions of "Trykipedia"
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+ | |title= Collaborating Institutions | ||
+ | |title_background=#cef2e0 | ||
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+ | * [http://knoesis.wright.edu Kno.e.sis Center, Wright State University] | ||
+ | * [http://www.ctegd.uga.edu Tarleton Research Group, Center for Tropical and Emerging Global Diseases(CTEGD), University of Georgia] | ||
+ | * [http://lsdis.cs.uga.edu Large Scale Distributed Information Systems, LSDIS Lab, University of Georgia] | ||
+ | * [http://bioontology.org National Center for Biological Ontologies, NCBO, Stanford University] | ||
+ | * [http://www.sanger.ac.uk The Wellcome Trust Sanger Institute, Cambridge, UK] | ||
+ | * [http://www.fiocruz.br/ioc/cgi/cgilua.exe/sys/start.htm?tpl=home The Oswaldo Cruz Institute (Fiocruz), Brazil] | ||
+ | We invite new members to collaborate with us in extending Parasite Life cycle Ontology (PLO) and/or Parasite Experiment Ontology (PEO). | ||
+ | }} | ||
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Research in many biological systems, particularly those involving infectious agents, continues to experience an enormous increase in information with the sequencing of genomes, the use of expression profiling, and the completion of proteomic analyses. For example, annotated genomes and comparative analyses of two ''T. cruzi'' related kinetoplastids, ''Trypanosoma brucei'' [1] and ''Leishmania major'' [2] , and a whole organism (all life-cycle stages) proteome analysis of ''T. cruzi'' have been published [3] . Data from other sequencing projects in ''T. cruzi'', including ESTs [4] , preexisting and ongoing expression profiling (DNA microarray [5] ) and proteome analyses are also available. These dynamic datasets, addressing different but logically related aspects, are distributed over multiple databases that undergo frequent additions and curation. It is difficult to integrate these datasets manually from muliple sources. Therefore, we propose to use ontology-driven technology to integrate local and external datasets to answer biological questions at mulitple level of granularity. [http://www.knoesis.org/research/semsci/application_domain/sem_life_sci/tcruzi_pse/ Project Page] | Research in many biological systems, particularly those involving infectious agents, continues to experience an enormous increase in information with the sequencing of genomes, the use of expression profiling, and the completion of proteomic analyses. For example, annotated genomes and comparative analyses of two ''T. cruzi'' related kinetoplastids, ''Trypanosoma brucei'' [1] and ''Leishmania major'' [2] , and a whole organism (all life-cycle stages) proteome analysis of ''T. cruzi'' have been published [3] . Data from other sequencing projects in ''T. cruzi'', including ESTs [4] , preexisting and ongoing expression profiling (DNA microarray [5] ) and proteome analyses are also available. These dynamic datasets, addressing different but logically related aspects, are distributed over multiple databases that undergo frequent additions and curation. It is difficult to integrate these datasets manually from muliple sources. Therefore, we propose to use ontology-driven technology to integrate local and external datasets to answer biological questions at mulitple level of granularity. [http://www.knoesis.org/research/semsci/application_domain/sem_life_sci/tcruzi_pse/ Project Page] | ||
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Revision as of 18:43, 12 January 2010
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