An orchestra of machine learning methods reveals landmarks in single-cell data exemplified with aging fibroblasts

• Lauritz Rasbach ,

  Contributed equally to this work with: Lauritz Rasbach, Aylin Caliskan

  Roles Methodology, Software, Visualization, Writing – review & editing

  Affiliation Department of Bioinformatics, Biocenter, University of Würzburg, Würzburg, Germany

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• Aylin Caliskan ,

  Contributed equally to this work with: Lauritz Rasbach, Aylin Caliskan

  Roles Data curation, Formal analysis, Investigation, Validation, Visualization, Writing – review & editing

  Affiliation Department of Bioinformatics, Biocenter, University of Würzburg, Würzburg, Germany

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• Fatemeh Saderi,

  Roles Visualization

  Affiliation Department of Bioinformatics, Biocenter, University of Würzburg, Würzburg, Germany

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• Thomas Dandekar ,

  Roles Funding acquisition, Supervision, Writing – review & editing

  * E-mail: dandekar@biozentrum.uni-wuerzburg.de (TD); tim.breitenbach@mathematik.uni-wuerzburg.de (TB)

  Affiliation Department of Bioinformatics, Biocenter, University of Würzburg, Würzburg, Germany

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• Tim Breitenbach

  Roles Conceptualization, Methodology, Project administration, Software, Supervision, Writing – original draft, Writing – review & editing

  * E-mail: dandekar@biozentrum.uni-wuerzburg.de (TD); tim.breitenbach@mathematik.uni-wuerzburg.de (TB)

  Affiliation Department of Bioinformatics, Biocenter, University of Würzburg, Würzburg, Germany

  https://orcid.org/0000-0003-4615-1915

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