Aims & Scope

npj Systems Biology and Applications considers all aspects of research covering computational and mathematical approaches to analysis and modeling of complex biological systems.

The journal covers a broad range of topics including but not limited to: 

    Computational modeling of biological systems
    Application of systems biology approaches to disease modeling, pharmacology, drug discovery, biotechnology, and industry
    Network biology and interactome analysis
    Multi-omics data integration
    Synthetic biology and metabolic engineering
    Single-cell systems biology
    Systems immunology and host-pathogen interactions
    Systems neuroscience and brain function
    Environmental systems biology
    Evolutionary systems biology

The journal offers more choice to Nature Portfolio authors who are seeking a fully open-access and more inclusive platform for publishing their work. The journal is led by systems biology experts who collaborate to cultivate high-quality research. As part of the npj Series, this journal focuses on fostering global partnerships with the research community and other Springer Nature journals.

Special Issue on Virtual human development: merging experiments and theory to understand human development
提出日: 2024-11-30

All of us began as a single cell, the fertilized egg. This cell gave rise to a group of "stem cells" that can transform into any cell type in our body to create our complex tissues consisting of trillions of cells. The development of our tissues is controlled by a complex interplay of genetics, epigenetics, gene regulatory networks, protein configurations, environmental signaling, and metabolic states. Cells use these processes to determine whether to divide, differentiate, communicate, or persist, leading to the coordination of cells to produce functional tissues and organs. To understand how information flows across biological scales and time, we need a multidisciplinary approach that combines the generation of rich molecular and cellular data with computational tools and mathematical models. Advances in single-cell genomics, lineage tracing, genetic engineering, and stem cell-derived organoid models have made it possible to study development experimentally. In addition, advances in machine learning and artificial intelligence have made it possible to predict perturbations, and physical and agent-based modeling approaches allow us to model cell behavior at tissue scales.

Consolidating our knowledge and understanding the biological rules that govern embryonic development can help us communicate better across different fields of expertise and also reveal gaps in our collective knowledge. The embryo is a complex system where molecular networks shape cellular phenotype and, ultimately, the multicellular population. This provides an opportunity for testing hypotheses to understand how changes at one level can affect the other levels. We anticipate that this combination of theory-experiment cycles will accelerate our understanding of human development while providing valuable predictions for regenerative medicine approaches.

This collection will feature original research articles, perspectives and special reviews focused on the experimental and in silico models and techniques needed to understand human development. This includes but is not limited to organoid models, single cell ‘omics’ methods and analysis, imaging techniques, lineage tracing, genetic engineering, mathematical modeling, gene regulatory network inference, and AI/machine learning-mediated prediction of cell behaviour and function.

This Collection supports and amplifies research related to SDG 3.