Mining Massive Amounts of Genomic Data: A Semiparametric Topic Modeling Approach.
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| Title: | Mining Massive Amounts of Genomic Data: A Semiparametric Topic Modeling Approach. |
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| Authors: | Fang, Ethan X.1 (AUTHOR), Li, Min-Dian2 (AUTHOR), Jordan, Michael I.3 (AUTHOR), Liu, Han4 (AUTHOR) |
| Source: | Journal of the American Statistical Association. Sep2017, Vol. 112 Issue 519, p921-932. 12p. |
| Database: | Mathematics Source |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: msf DbLabel: Mathematics Source An: 125941783 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=msf&AN=125941783 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1080/01621459.2016.1256812 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 921 Titles: – TitleFull: Mining Massive Amounts of Genomic Data: A Semiparametric Topic Modeling Approach. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Fang, Ethan X. – PersonEntity: Name: NameFull: Li, Min-Dian – PersonEntity: Name: NameFull: Jordan, Michael I. – PersonEntity: Name: NameFull: Liu, Han IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: Sep2017 Type: published Y: 2017 Identifiers: – Type: issn-print Value: 01621459 Numbering: – Type: volume Value: 112 – Type: issue Value: 519 Titles: – TitleFull: Journal of the American Statistical Association Type: main |
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