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dc.contributor.authorLussier, Yves A
dc.contributor.authorBerghout, Joanne
dc.contributor.authorVitali, Francesca
dc.contributor.authorRamos, Kenneth S
dc.contributor.authorKann, Maricel
dc.contributor.authorMoore, Jason H
dc.date.accessioned2019-07-18T17:57:13Z
dc.date.available2019-07-18T17:57:13Z
dc.date.issued2018
dc.identifier.citationLussier, Y. A., Berghout, J., Vitali, F., Ramos, K. S., Kann, M., & Moore, J. H. (2017). Reading Between the Genes: Computational Models to Discover Function from Noncoding DNA.en_US
dc.identifier.issn2335-6936
dc.identifier.pmid29218909
dc.identifier.doi10.1142/9789813235533_0046
dc.identifier.urihttp://hdl.handle.net/10150/633387
dc.description.abstractNoncoding DNA - once called "junk" has revealed itself to be full of function. Technology development has allowed researchers to gather genome-scale data pointing towards complex regulatory regions, expression and function of noncoding RNA genes, and conserved elements. Variation in these regions has been tied to variation in biological function and human disease. This PSB session tackles the problem of handling, analyzing and interpreting the data relating to variation in and interactions between noncoding regions through computational biology. We feature an invited speaker to how variation in transcription factor coding sequences impacts on sequence preference, along with submitted papers that span graph based methods, integrative analyses, machine learning, and dimension reduction to explore questions of basic biology, cancer, diabetes, and clinical relevance.en_US
dc.description.sponsorshipUniversity of Arizona Health Sciences CB2, the BIO5 Institute; NIH [U01AI122275, HL132532, CA023074, 1UG3OD023171, 1R01AG053589-01A1, 1S10RR029030]en_US
dc.language.isoenen_US
dc.publisherWORLD SCIENTIFIC PUBL CO PTE LTDen_US
dc.relation.urlhttps://www.worldscientific.com/doi/abs/10.1142/9789813235533_0046en_US
dc.rights© 2017 The Authors. Open Access chapter published by World Scientific Publishing Company and distributed under the terms of the Creative Commons Attribution Non-Commercial (CC BYNC) 4.0 License.en_US
dc.subjectnon-coding DNAen_US
dc.subjectintergenicen_US
dc.subjectLncRNAen_US
dc.subjectmicroRNAen_US
dc.subjectsncRNAen_US
dc.subjectmiRNAen_US
dc.subjectpiRNAen_US
dc.subjectLINEsen_US
dc.subjectLINE1en_US
dc.subjectrepetitive elementsen_US
dc.titleReading Between the Genes: Computational Models to Discover Function from Noncoding DNAen_US
dc.typeArticleen_US
dc.contributor.departmentUniv Arizona, UA Canc Ctr, Ctr Biomed Informat & Biostat, BIO5 Inst,Ctr Appl Genet & Genom Meden_US
dc.contributor.departmentUniv Arizona, Dept Meden_US
dc.identifier.journalPACIFIC SYMPOSIUM ON BIOCOMPUTING 2018 (PSB)en_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
dc.source.journaltitlePacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
refterms.dateFOA2019-07-18T17:57:14Z


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