Exploring potential gene signatures in dengue through machine learning and deep learning approaches.
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| Title: | Exploring potential gene signatures in dengue through machine learning and deep learning approaches. |
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| Authors: | Josyula JVN; Department of Applied Biology, CSIR-Indian Institute of Chemical Technology, Hyderabad, India.; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India., Jangili S; Department of Applied Biology, CSIR-Indian Institute of Chemical Technology, Hyderabad, India.; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India., Yaladanda N; Department of Applied Biology, CSIR-Indian Institute of Chemical Technology, Hyderabad, India.; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India., Pillai AKB; Institute of Advanced Virology, Bio 360 Life Sciences Park, Thonnakkal, Trivandrum, Kerala, 695 317, India., Mutheneni SR; Department of Applied Biology, CSIR-Indian Institute of Chemical Technology, Hyderabad, India. msrinivas@iict.res.in.; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India. msrinivas@iict.res.in. |
| Source: | Virus genes [Virus Genes] 2026 Feb; Vol. 62 (1), pp. 51-66. Date of Electronic Publication: 2025 Dec 02. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Kluwer Academic Country of Publication: United States NLM ID: 8803967 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1572-994X (Electronic) Linking ISSN: 09208569 NLM ISO Abbreviation: Virus Genes Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| FullText | Text: Availability: 0 |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 41329415 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| 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="AU" term="%22Josyula+JVN%22">Josyula JVN</searchLink>; Department of Applied Biology, CSIR-Indian Institute of Chemical Technology, Hyderabad, India.; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India.<br /><searchLink fieldCode="AU" term="%22Jangili+S%22">Jangili S</searchLink>; Department of Applied Biology, CSIR-Indian Institute of Chemical Technology, Hyderabad, India.; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India.<br /><searchLink fieldCode="AU" term="%22Yaladanda+N%22">Yaladanda N</searchLink>; Department of Applied Biology, CSIR-Indian Institute of Chemical Technology, Hyderabad, India.; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India.<br /><searchLink fieldCode="AU" term="%22Pillai+AKB%22">Pillai AKB</searchLink>; Institute of Advanced Virology, Bio 360 Life Sciences Park, Thonnakkal, Trivandrum, Kerala, 695 317, India.<br /><searchLink fieldCode="AU" term="%22Mutheneni+SR%22">Mutheneni SR</searchLink>; Department of Applied Biology, CSIR-Indian Institute of Chemical Technology, Hyderabad, India. msrinivas@iict.res.in.; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India. msrinivas@iict.res.in. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%228803967%22">Virus genes</searchLink> [Virus Genes] 2026 Feb; Vol. 62 (1), pp. 51-66. <i>Date of Electronic Publication: </i>2025 Dec 02. – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Kluwer+Academic%22">Kluwer Academic </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>8803967 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1572-994X (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2209208569%22">09208569 </searchLink><i>NLM ISO Abbreviation: </i>Virus Genes <i>Subsets: </i>MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=41329415 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11262-025-02204-9 Languages: – Code: eng Text: English PhysicalDescription: Pagination: 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 JVN – PersonEntity: Name: NameFull: Jangili S – PersonEntity: Name: NameFull: Yaladanda N – PersonEntity: Name: NameFull: Pillai AKB – PersonEntity: Name: NameFull: Mutheneni SR IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: 2026 Feb Type: published Y: 2026 Identifiers: – Type: issn-electronic Value: 1572-994X Numbering: – Type: volume Value: 62 – Type: issue Value: 1 Titles: – TitleFull: Virus genes Type: main |
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