Difference between revisions of "SemEP"

 
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semEP: The research will explore a new area of multidisciplinary research that
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semEP: A new area of multidisciplinary research that is at the intersection of bioinformatics, algorithmics and semantic Web research. We exploit Linked Data resources on genes, pathways, drugs, ontologies and injury phenotypes. We develop new methodologies based upon semantics based community detection and tensor methods. We will construct complex phenotype profiles and show their application in diverse clinical applications, e.g., all drug adverse reactions associated with seed drug induced liver injury (DILI) drugs. Lung cancer and Alzheimer's disease are being explored as part of the EU H2020 iASiS project: [http://project-iasis.eu]
is at the intersection of bioinformatics, algorithmics and semantic Web research.
 
We exploit Linked Data resources on genes, pathways, drugs, ontologies and injury phenotypes. We will construct complex phenotype profiles and show their application in diverse clinical applications, e.g., all drug adverse reactions associated with seed drug induced liver injury -- DILI drugs.
 
 
 
  
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Recent papers:
 
[https://link.springer.com/chapter/10.1007%2F978-3-319-11964-9_9] [http://ieeexplore.ieee.org/document/6817596/?reload=true]
 
[https://link.springer.com/chapter/10.1007%2F978-3-319-11964-9_9] [http://ieeexplore.ieee.org/document/6817596/?reload=true]

Latest revision as of 21:58, 16 November 2017

semEP: A new area of multidisciplinary research that is at the intersection of bioinformatics, algorithmics and semantic Web research. We exploit Linked Data resources on genes, pathways, drugs, ontologies and injury phenotypes. We develop new methodologies based upon semantics based community detection and tensor methods. We will construct complex phenotype profiles and show their application in diverse clinical applications, e.g., all drug adverse reactions associated with seed drug induced liver injury (DILI) drugs. Lung cancer and Alzheimer's disease are being explored as part of the EU H2020 iASiS project: [1]

Recent papers: [2] [3]