Inference of causal transcriptional regulatory networks (TRNs) from transcriptomic data
suffers notoriously from false positives. Approaches to control the false discovery rate (FDR) …

Motivation The gene regulatory process resembles a logic system in which a target gene is
regulated by a logic gate among its regulators. While various computational techniques are …

Motivation The question of how to construct gene regulatory networks has long been a focus
of biological research. Mutual information can be used to measure nonlinear relationships …

Gene regulatory networks (GRNs) participate in many biological processes, and
reconstructing them plays an important role in systems biology. Although many advanced …

In Bioinformatics, inferring the structure of a Gene Regulatory Network (GRN) from
incomplete gene expression data is a difficult task. One popular method for inferring the …

Decomposition hybrid algorithms with the recursive framework which recursively
decompose the structural task into structural subtasks to reduce computational complexity …

Abstract Motivation Gene regulatory networks (GRNs) are vital tools for delineating
regulatory relationships between transcription factors and their target genes. The boom in …

Gene regulatory network can intuitively reflect the interaction between genes, and an in-
depth study of these relationships plays a significant role in the treatment and prevention of …

Inferring the network topology from the dynamics of interacting units constitutes a topical
challenge that drives research on its theory and applications across physics, mathematics …

The complex mechanisms of diseases involve the disturbance of the molecular network,
rather than disorder in a single gene, implying that single gene-based analysis is insufficient …