Enhancing yeast cell tracking with a time-symmetric deep learning approach.
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| Title: | Enhancing yeast cell tracking with a time-symmetric deep learning approach. |
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| Authors: | Szabó, Gergely1 (AUTHOR) szabo.gergely@itk.ppke.hu, Bonaiuti, Paolo2 (AUTHOR), Ciliberto, Andrea1,2 (AUTHOR), Horváth, András1 (AUTHOR) horvath.andras@itk.ppke.hu |
| Source: | NPJ Systems Biology & Applications. 3/13/2025, Vol. 11 Issue 1, p1-14. 14p. |
| Database: | Academic Search Ultimate |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: asn DbLabel: Academic Search Ultimate An: 183751969 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=183751969 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1038/s41540-024-00466-x Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 1 Titles: – TitleFull: Enhancing yeast cell tracking with a time-symmetric deep learning approach. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Szabó, Gergely – PersonEntity: Name: NameFull: Bonaiuti, Paolo – PersonEntity: Name: NameFull: Ciliberto, Andrea – PersonEntity: Name: NameFull: Horváth, András IsPartOfRelationships: – BibEntity: Dates: – D: 13 M: 03 Text: 3/13/2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 20567189 Numbering: – Type: volume Value: 11 – Type: issue Value: 1 Titles: – TitleFull: NPJ Systems Biology & Applications Type: main |
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