Generating synthetic multidimensional molecular time series data for machine learning: considerations.
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| Title: | Generating synthetic multidimensional molecular time series data for machine learning: considerations. |
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| Authors: | An, Gary1 gan@med.uvm.edu, Cockrell, Chase1 |
| Source: | Frontiers in Systems Biology. 8/8/2023, Vol. 3, p1-13. 13p. |
| Database: | Academic Search Ultimate |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: asn DbLabel: Academic Search Ultimate An: 174397743 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=asn&AN=174397743 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3389/fsysb.2023.1188009 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 13 StartPage: 1 Titles: – TitleFull: Generating synthetic multidimensional molecular time series data for machine learning: considerations. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: An, Gary – PersonEntity: Name: NameFull: Cockrell, Chase IsPartOfRelationships: – BibEntity: Dates: – D: 08 M: 08 Text: 8/8/2023 Type: published Y: 2023 Identifiers: – Type: issn-print Value: 26740702 Numbering: – Type: volume Value: 3 Titles: – TitleFull: Frontiers in Systems Biology Type: main |
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