View in EDS HTML Full Text PDF Full Text

Identifying dynamical persistent biomarker structures for rare events using modern integrative machine learning approach.

Saved in:
Bibliographic Details
Title: Identifying dynamical persistent biomarker structures for rare events using modern integrative machine learning approach.
Authors: Dutta S; Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, Kansas, USA., Box AC; Stowers Institute for Medical Research, Kansas City, Missouri, USA., Li Y; Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, Kansas, USA.; University of Kansas Cancer Center, Kansas City, Kansas, USA., Sardiu ME; Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, Kansas, USA.; University of Kansas Cancer Center, Kansas City, Kansas, USA.; Kansas Institute for Precision Medicine, University of Kansas Medical Center, Kansas City, Kansas, USA.
Source: Proteomics [Proteomics] 2023 Nov; Vol. 23 (21-22), pp. e2200290. Date of Electronic Publication: 2023 Mar 10.
Publication Type: Journal Article; Research Support, N.I.H., Extramural
Journal Info: Publisher: Wiley-VCH Country of Publication: Germany NLM ID: 101092707 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1615-9861 (Electronic) Linking ISSN: 16159853 NLM ISO Abbreviation: Proteomics Subsets: MEDLINE
Database: MEDLINE Ultimate
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: mdl
DbLabel: MEDLINE Ultimate
An: 36852539
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Identifying dynamical persistent biomarker structures for rare events using modern integrative machine learning approach.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Dutta+S%22">Dutta S</searchLink>; Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, Kansas, USA.<br /><searchLink fieldCode="AU" term="%22Box+AC%22">Box AC</searchLink>; Stowers Institute for Medical Research, Kansas City, Missouri, USA.<br /><searchLink fieldCode="AU" term="%22Li+Y%22">Li Y</searchLink>; Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, Kansas, USA.; University of Kansas Cancer Center, Kansas City, Kansas, USA.<br /><searchLink fieldCode="AU" term="%22Sardiu+ME%22">Sardiu ME</searchLink>; Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, Kansas, USA.; University of Kansas Cancer Center, Kansas City, Kansas, USA.; Kansas Institute for Precision Medicine, University of Kansas Medical Center, Kansas City, Kansas, USA.
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22101092707%22">Proteomics</searchLink> [Proteomics] 2023 Nov; Vol. 23 (21-22), pp. e2200290. <i>Date of Electronic Publication: </i>2023 Mar 10.
– Name: TypePub
  Label: Publication Type
  Group: TypPub
  Data: Journal Article; Research Support, N.I.H., Extramural
– Name: TitleSource
  Label: Journal Info
  Group: Src
  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Wiley-VCH%22">Wiley-VCH </searchLink><i>Country of Publication: </i>Germany <i>NLM ID: </i>101092707 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1615-9861 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2216159853%22">16159853 </searchLink><i>NLM ISO Abbreviation: </i>Proteomics <i>Subsets: </i>MEDLINE
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=36852539
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1002/pmic.202200290
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        StartPage: e2200290
    Titles:
      – TitleFull: Identifying dynamical persistent biomarker structures for rare events using modern integrative machine learning approach.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Dutta S
      – PersonEntity:
          Name:
            NameFull: Box AC
      – PersonEntity:
          Name:
            NameFull: Li Y
      – PersonEntity:
          Name:
            NameFull: Sardiu ME
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 11
              Text: 2023 Nov
              Type: published
              Y: 2023
          Identifiers:
            – Type: issn-electronic
              Value: 1615-9861
          Numbering:
            – Type: volume
              Value: 23
            – Type: issue
              Value: 21-22
          Titles:
            – TitleFull: Proteomics
              Type: main
ResultId 1