Gene regulation plays a fundamental role in shaping tissue identity, function, and response
to perturbation. Regulatory processes are controlled by complex networks of interacting …

Inference and analysis of gene regulatory networks (GRNs) require software that integrates
multi-omic data from various sources. The Network Zoo (netZoo; netzoo. github. io) is a …

Objectives: Graph representation learning (GRL) has emerged as a pivotal field that has
contributed significantly to breakthroughs in various fields, including biomedicine. The …

Gene regulatory networks (GRNs) are effective tools for inferring complex interactions
between molecules that regulate biological processes and hence can provide insights into …

Despite recent progress, the challenges in drug discovery for schizophrenia persist.
However, computational drug repurposing has gained popularity as it leverages the wealth …

Understanding the intricate regulatory relationships among genes is crucial for
comprehending the development, differentiation, and cellular response in living systems …

Motivation Systems biology analyses often use correlations in gene expression profiles to
infer co-expression networks that are then used as input for gene regulatory network …

Background Gene regulatory network (GRN) models that are formulated as ordinary
differential equations (ODEs) can accurately explain temporal gene expression patterns and …

Background Bipolar disorder (BD) presents significant challenges in drug discovery,
necessitating alternative approaches. Drug repurposing, leveraging computational …

The practical utility of machine learning models in the sciences often hinges on their
interpretability. It is common to assess a model's merit for scientific discovery, and thus novel …