Tvsfglasso: Time-varying scale-free graphical lasso for network estimation from time-series data.

ABSTRACT: In high-dimensional gene co-expression network analysis, capturing the temporal changes of gene associations is crucial for unveiling dynamic regulatory mechanisms inherent in biological systems. Examining how these interactions change over time offers valuable insights into the developmental and adaptive processes that drive an organism's lifecycle. Moreover, incorporating structural prior information can substantially enhance the accuracy and interpretability of the estimated sparse dynamic gene network. Methods previously proposed in the literature cannot simultaneously model sparse time-varying co-expression network structure and have the power-law degree distribution. Additionally, there is a demand of time-efficient, memory-light software implementations and possibility to utilize re

SUBMITTER: Kuismin M 

PROVIDER: S-EPMC12633906 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature