Abstract Purpose of Review This article gives a broad overview of quantitative modelling
approaches in biology and provides guidance on how to employ them to boost stem cell …

Boolean networks (BNs) have been extensively used to model gene regulatory networks
(GRNs). The dynamics of BNs depend on the network architecture and regulatory logic rules …

Today, a wide range of technologies and data types are available when studying disease-
relevant processes. Therefore, a major challenge is integrating data from different …

Sterols are secondary metabolites commonly found in rapeseed that play crucial
physiological roles in plants and also benefit human health. Consequently, unraveling the …

Biological systems exhibit complex dynamics that differential equations can often adeptly
represent. Ordinary differential equation models are widespread; until recently their …

Time-series experiments are crucial for understanding the transient and dynamic nature of
biological phenomena. These experiments, leveraging advanced classification and …

Single-cell transcriptome data can provide insights into how genetic variation influences
biological processes involved in human biology and disease. However, the identification of …

One of the most robust approaches to the prediction of causal driver genes of complex
diseases is to apply reverse engineering methods to infer a gene regulatory network (GRN) …

Cancer research has been significantly advanced by the integration of transcriptomic data
through high-throughput sequencing technologies like RNA sequencing (RNA-seq). This …

Insulin synthesis is a complex and essential biological process involving a series of
interconnected subprocesses. We present a model of the translational process and post …