Machine learning integration of scleroderma histology and gene expression identifies fibroblast polarisation as a hallmark of clinical severity and improvement.

Abstract

Authors

• Kimberly Showalter
  Department of Medicine, Division of Rheumatology, Hospital for Special Surgery, New York, New York, USA showalterk@hss.edu.
• Robert Spiera
  Department of Medicine, Division of Rheumatology, Hospital for Special Surgery, New York, New York, USA.
• Cynthia Magro
  Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, New York, USA.
• Phaedra Agius
  New York Genome Center, New York, New York.
• Viktor Martyanov
  Geisel School of Medicine at Dartmouth, Hanover, New Hampshire.
• Jennifer M Franks
  Department of Molecular and Systems Biology.
• Roshan Sharma
  New York Genome Center, New York, New York, USA.
• Heather Geiger
  New York Genome Center, New York, New York.
• Tammara A Wood
  Geisel School of Medicine at Dartmouth, Hanover, New Hampshire.
• Yaxia Zhang
  Department of Pathology, Hospital for Special Surgery, New York, New York, USA.
• Caryn R Hale
  Laboratory of Molecular Neuro-Oncology, The Rockefeller University, New York, New York, USA.
• Jackie Finik
  Department of Medicine, Hospital for Special Surgery, New York, New York, USA.
• Michael L Whitfield
  Department of Molecular and Systems Biology.
• Dana E Orange
  Hospital for Special Surgery, The Rockefeller University, and New York Genome Center, New York, New York.
• Jessica K Gordon
  Department of Medicine, Division of Rheumatology, Hospital for Special Surgery, New York, New York, USA.

Keywords

External Resources