Transcriptional insights into pathogenesis of cutaneous systemic sclerosis using pathway driven meta-analysis assisted by machine learning methods.

Transcriptional insights into pathogenesis of cutaneous systemic sclerosis using pathway driven meta-analysis assisted by machine learning methods.

Pathophysiology of systemic sclerosis (SSc, Scleroderma), an autoimmune rheumatic disease, comprises of mechanisms that drive vasculopathy, inflammation and fibrosis. Understanding of the disease and associated clinical heterogeneity has advanced considerably in the past decade, highlighting the nec...

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Bibliographic Details
Main Authors: Xiao Xu, Meera Ramanujam, Sudha Visvanathan, Shervin Assassi, Zheng Liu, Li Li
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0242863

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https://doi.org/10.1371/journal.pone.0242863

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