期刊信息

npj Systems Biology and Applications

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影响因子:
3.5
出版商:
Springer
ISSN:
2056-7189
浏览:
19149
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0

征稿

npj Systems Biology and Applications is an academic journal published by Springer. (ISSN 2056-7189, impact factor 3.5).

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.
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Special Issues

Special Issue on Systems approaches for virtual clinical trials and digital twins 截稿日期: 2026-07-31 Virtual clinical trials and digital twins are emerging approaches to understanding mechanisms of drug responses and drug treatment heterogeneity. With the goal of providing the right drug at the right dose to the right patient, virtual clinical trials and digital twins help to identify disease and treatment biomarkers, individualize therapeutic strategies, and optimize clinical trial design, ultimately reducing the time and cost of drug development. The methodological frameworks of both virtual clinical trials and digital twins have important implications beyond drug development and therapeutic optimization, helping to establish pathophysiological processes and discern how key mechanisms drive biological heterogeneity. This thematic collection will highlight cutting-edge research into virtual clinical trials and digital twins. This includes the development of new methodological approaches and applications to a variety of diseases and drug contexts. In particular, we welcome submissions merging experimentation and/or clinical trial data with predictive mechanistic mathematical models.
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Special Issue on Systems immunology: multi-omics approaches, dynamical modeling and novel agentic AI approaches 截稿日期: 2026-09-12 Over the past decade, experimental and computational approaches for deep molecular and cellular profiling have become readily available and widely used for profiling the immune system both in human and in model organisms. 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. We are especially interested in manuscripts leveraging recent advances in AI/agentic AI approaches to study immune regulation and dysregulation. This will be a key focus of the collection. Manuscripts do not necessarily need to include both aspects; studies describing either novel computational approaches for the analyses of multi-omic datasets or creative experimental techniques for generating one or more of these datasets are welcome. However, manuscripts simply describing computational methods without demonstrating their applications on real-world datasets will not be considered a good fit for this collection.
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