Academic Journal
Προβολή σε EDS

Exploring potential gene signatures in dengue through machine learning and deep learning approaches

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Exploring potential gene signatures in dengue through machine learning and deep learning approaches
Συγγραφείς: Josyula, Jhansi Venkata NagamaniAff1, Aff2, Jangili, ShraddhaAff1, Aff2, Yaladanda, NikhilaAff1, Aff2, Pillai, Agiesh Kumar BalakrishnaAff3, Mutheneni, Srinivasa RaoAff1, Aff2, IDs11262025022049_cor1
Πηγή: Virus Genes. 62(1):51-66
Βάση Δεδομένων: Springer Nature Journals
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://dx.doi.org/doi:10.1007/s11262-025-02204-9
    Name: EDS - Springer Nature Journals (s7799221)
    Category: fullText
    Text: View record at Springer
  – Url: https://resolver.ebsco.com/c/fiv2js/result?sid=EBSCO:edssjs&genre=article&issn=09208569&ISBN=&volume=62&issue=1&date=20260201&spage=51&pages=51-66&title=Virus Genes&atitle=Exploring%20potential%20gene%20signatures%20in%20dengue%20through%20machine%20learning%20and%20deep%20learning%20approaches&aulast=Josyula%2C%20Jhansi%20Venkata%20Nagamani&id=DOI:10.1007/s11262-025-02204-9
    Name: Full Text Finder (for New FTF UI) (ns324271)
    Category: fullText
    Text: Full Text Finder
    MouseOverText: Full Text Finder
Header DbId: edssjs
DbLabel: Springer Nature Journals
An: edssjs.C2C73C2C
RelevancyScore: 1009
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 1008.57232666016
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Exploring potential gene signatures in dengue through machine learning and deep learning approaches
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Josyula%2C+Jhansi+Venkata+Nagamani%22">Josyula, Jhansi Venkata Nagamani</searchLink><relatesTo>Aff1, Aff2</relatesTo><br /><searchLink fieldCode="AR" term="%22Jangili%2C+Shraddha%22">Jangili, Shraddha</searchLink><relatesTo>Aff1, Aff2</relatesTo><br /><searchLink fieldCode="AR" term="%22Yaladanda%2C+Nikhila%22">Yaladanda, Nikhila</searchLink><relatesTo>Aff1, Aff2</relatesTo><br /><searchLink fieldCode="AR" term="%22Pillai%2C+Agiesh+Kumar+Balakrishna%22">Pillai, Agiesh Kumar Balakrishna</searchLink><relatesTo>Aff3</relatesTo><br /><searchLink fieldCode="AR" term="%22Mutheneni%2C+Srinivasa+Rao%22">Mutheneni, Srinivasa Rao</searchLink><relatesTo>Aff1, Aff2, IDs11262025022049_cor1</relatesTo>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <i>Virus Genes</i>. 62(1):51-66
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edssjs&AN=edssjs.C2C73C2C
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s11262-025-02204-9
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 16
        StartPage: 51
    Titles:
      – TitleFull: Exploring potential gene signatures in dengue through machine learning and deep learning approaches
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Josyula, Jhansi Venkata Nagamani
      – PersonEntity:
          Name:
            NameFull: Jangili, Shraddha
      – PersonEntity:
          Name:
            NameFull: Yaladanda, Nikhila
      – PersonEntity:
          Name:
            NameFull: Pillai, Agiesh Kumar Balakrishna
      – PersonEntity:
          Name:
            NameFull: Mutheneni, Srinivasa Rao
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 02
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 09208569
            – Type: issn-print
              Value: 1572994X
          Numbering:
            – Type: volume
              Value: 62
            – Type: issue
              Value: 1
          Titles:
            – TitleFull: Virus Genes
              Type: main
ResultId 1