A Blueprint for Identifying Phenotypes and Drug Targets in Complex Disorders with Empirical Dynamics.

ABSTRACT: A central challenge in medicine is translating from observational understanding to mechanistic understanding, where some observations are recognized as causes for the others. This can lead not only to new treatments and understanding, but also to recognition of novel phenotypes. Here, we apply a collection of mathematical techniques (empirical dynamics), which infer mechanistic networks in a model-free manner from longitudinal data, to hematopoiesis. Our study consists of three subjects with markers for cyclic thrombocytopenia, in which multiple cells and proteins undergo abnormal oscillations. One subject has atypical markers and may represent a rare phenotype. Our analyses support this contention, and also lend new evidence to a theory for the cause of this disorder. Simulations o

SUBMITTER: Krieger MS 

PROVIDER: S-EPMC7733879 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature