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dc.contributor.authorLussier, Yves A.
dc.contributor.authorButte, Atul J.
dc.contributor.authorLi, Haiquan
dc.contributor.authorChen, Rong
dc.contributor.authorMoore, Jason H.
dc.date.accessioned2019-08-06T23:48:22Z
dc.date.available2019-08-06T23:48:22Z
dc.date.issued2019
dc.identifier.citationLussier, Y. A., Butte, A. J., Li, H., Chen, R., & Moore, J. H. (2019, January). Translational informatics of population health: How large biomolecular and clinical datasets unite. In PSB (p. 455).en_US
dc.identifier.issn2335-6936
dc.identifier.doi10.1142/9789813279827_0043
dc.identifier.urihttp://hdl.handle.net/10150/633736
dc.description.abstractThis paper summarizes the workshop content on how the integration of large biomolecular and clinical datasets can enhance the field of population health via translational informatics. Large volumes of data present diverse challenges for existing informatics technology, in terms of computational efficiency, modeling effectiveness, statistical computing, discovery algorithms, and heterogeneous data integration. While accumulating large 'omics measurements on subjects linked with their electronic record remains a challenge, this workshop focuses on non-trivial linkages between large clinical and biomolecular datasets. For example, exposures and clinical datasets can relate through zip codes, while comorbidities and shared molecular mechanisms can relate diseases. Workshop presenters will discuss various methods developed in their respective labs/organizations to overcome the difficulties of combining together such large complex datasets and knowledge to enable the translation to clinical practice for improving health outcomes.en_US
dc.language.isoenen_US
dc.publisherWORLD SCIENTIFIC PUBL CO PTE LTDen_US
dc.rights© 2018 The Authors. Open Access chapter published by World Scientific Publishing Company and distributed under the terms of the Creative Commons Attribution Non-Commercial (CC BY-NC) 4.0 License.en_US
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.subjectTranslational informaticsen_US
dc.subjectbiomolecularen_US
dc.subjectclinicalen_US
dc.subjectpopulation healthen_US
dc.subjectbig dataen_US
dc.subjectworkshopen_US
dc.titleTranslational informatics of population health: How large biomolecular and clinical datasets uniteen_US
dc.typeArticleen_US
dc.contributor.departmentUniv Arizona, Ctr Biomed Informat & Biostat, Dept Med, BIO5 Inst,Canc Ctren_US
dc.contributor.departmentUniv Arizona, Coll Agr & Life Scien_US
dc.identifier.journalPACIFIC SYMPOSIUM ON BIOCOMPUTING 2019en_US
dc.description.noteOpen access journalen_US
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en_US
dc.eprint.versionFinal published versionen_US
refterms.dateFOA2019-08-06T23:48:22Z


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© 2018 The Authors. Open Access chapter published by World Scientific Publishing Company and distributed under the terms of the Creative Commons Attribution Non-Commercial (CC BY-NC) 4.0 License.
Except where otherwise noted, this item's license is described as © 2018 The Authors. Open Access chapter published by World Scientific Publishing Company and distributed under the terms of the Creative Commons Attribution Non-Commercial (CC BY-NC) 4.0 License.