Extracting Insights From Temporal Data by Integrating Dynamic Modeling and Machine Learning.

Biological processes are dynamic. As a result, temporal analyses are necessary to fully understand the complex interactions that occurs within these systems. One example of a multifaceted biological process is restitution: the initial step in complex wound repair.

Correction to: A quantitative systems pharmacology (QSP) model for Pneumocystis treatment in mice.

It was highlighted that the original article [1] contained errors in the figures and their legends and by extension the in-text figure citations. This Corrections article shows the correct figures and correct figure legends.

Unraveling the Control of Cell Cycle Periods during Intestinal Stem Cell Differentiation.

During differentiation, intestinal stem cells (ISCs), a prototypical adult stem cell pool, become either secretory transit-amplifying cells, which give rise to all secretory cell types, or absorptive transit-amplifying cells, which give rise to enterocytes. These cells exhibit distinct cell cycle dynamics: ISCs cycle with a period of 24 h and absorptive transit-amplifying cells cycle with a period of ∼12 h, whereas secretory transit-amplifying cells arrest their cycle. The cell cycle dynamics of ISCs and their progeny are a systems-level property that emerges from interactions between the cell cycle control machinery and multiple regulatory pathways.