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:
22888
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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.
由 Dou Sun 最后更新于

Special Issues

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.
由 Dou Sun 最后更新于

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