Calls for papers

The broad focus of this systems immunology collection is on computational and experimenal approaches that can be used to generate and interrogate combinations of these datasets in a principled fashion to uncover phenotypes and mechanisms underlying immunological states and disorders, and predictive dynamical models that can connect such high-throughput data to phenotypic/cell-state aspects.

This Collection focuses on methodological advances and novel applications of systems modeling frameworks that incorporate virtual trials and digital twins.

This collection aims to bring together researchers from diverse backgrounds—including mathematics, computer science, engineering, and biology—to showcase how data-driven modeling can advance our understanding of biomedical processes and improve patient outcomes.

This Collection invites research using discrete dynamical models to study biological systems across scales, from gene regulation to ecosystems.

This collection invites research on a systems perspective on phenotypic plasticity to better understand cancer and evolution and reconcile the genetic/non-genetic duality.

This Collection invites submissions on interplay of mechanical and molecular cues using diverse experimental tools and computational and theoretical approaches.

This collection invites research on empirical, theoretical, or computational studies advancing our understanding of predicting evolution.

This Collection will highlight studies that employ multi-omics techniques such as genomic, epigenomic, transcriptomic, proteomic and metabolomic profiling or utilize first principles based mathematical modelling and AI/ML approaches to explore the genetic, regulatory, and metabolic networks in mammalian cells and their cultures.