Identifying and predicting Parkinson’s disease subtypes through trajectory clustering via bipartite networks

Chronic medical conditions show substantial heterogeneity in their clinical features and progression. We develop the novel data-driven, network-based Trajectory Profile Clustering (TPC) algorithm for 1) identification of disease subtypes and 2) early prediction of subtype/disease progression pattern...

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Detalles Bibliográficos
Autores principales: Krishnagopal, Sanjukta, von Coelln, Rainer, Shulman, Lisa M., Girvan, Michelle
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7299311/
https://www.ncbi.nlm.nih.gov/pubmed/32555729
http://dx.doi.org/10.1371/journal.pone.0233296

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7299311/
https://www.ncbi.nlm.nih.gov/pubmed/32555729
http://dx.doi.org/10.1371/journal.pone.0233296

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