The increase in biological data and the formation of various biomolecule interaction
databases enable us to obtain diverse biological networks. These biological networks …

In the recent years, the vast amount of genetic information generated by new-generation
approaches, have led to the need of new data handling methods. The integrative analysis of …

Coexpression networks and gene regulatory networks (GRNs) are emerging as important
tools for predicting functional roles of individual genes at a system-wide scale. To enable …

Objectives To assess a new application of artificial intelligence for real‐time detection of
laryngeal squamous cell carcinoma (LSCC) in both white light (WL) and narrow‐band …

Gene regulatory networks lie at the core of cell function control. In E. coli and S. cerevisiae,
the study of gene regulatory networks has led to the discovery of regulatory mechanisms …

One of the most interesting, difficult, and potentially useful topics in computational biology is
the inference of gene regulatory networks (GRNs) from expression data. Although …

This article presents a review of computational methods for connectivity inference from
neural activity data derived from multi-electrode recordings or fluorescence imaging. We first …

Cellular gene expression changes throughout a dynamic biological process, such as
differentiation. Pseudotimes estimate cells' progress along a dynamic process based on …

Co-expression networks are essential tools to infer biological associations between gene
products and predict gene annotation. Global networks can be analyzed at the transcriptome …

The human gut microbiome, composed of trillions of microorganisms, plays an essential role
in human health. Many factors shape gut microbiome composition over the life span …