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Frontiers in Systems Biology is a peer-reviewed journal published by Frontiers, covering Gene Regulatory Network Analysis, Bioinformatics and Genomic Networks, Computational Drug Discovery Methods. Over its lifetime it has published 199 papers, which have received 1,225 citations.
| Publisher | Frontiers |
|---|---|
| Reference style | Author–year (Harvard) Author–year — (Smith, 2023) in the text Smith, A., Jones, B. and Lee, C. (2023) 'A representative article title', Frontiers in Systems Biology, 12(3), pp. 45–58.
Formats any DOI in Frontiers in Systems Biology style. No sign-up. |
| Publishes research in | Gene Regulatory Network Analysis Bioinformatics and Genomic Networks Computational Drug Discovery Methods Microbial Metabolic Engineering and Bioproduction Gut microbiota and health |
| ISSN | 2674-0702 |
| Citation impact (2-yr) | 3.28 |
| h-index | 17 |
| i10-index | 34 |
| Open access | Yes — indexed in DOAJ |
| Top institutions publishing here | University of Pittsburgh |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Humans are supra-organisms co-evolved with microbial communities (Prokaryotic and Eukaryotic), named the microbiome. These microbiomes supply essential ecosystem services that play critical roles in human health. A loss of indigenous microbes through modern lifestyles leads to microbial extinctions, associated with many diseases and epidemics. This narrative review conforms a complete guide to the human holobiont-comprising…
Large scale -omics datasets can provide new insights into normal and disease-related biology when analyzed through a systems biology framework. However, technical artefacts present in most -omics datasets due to variations in sample preparation, batching, platform settings, personnel, and other experimental procedures prevent useful analyses of such data without prior adjustment for these technical factors.…
There has been a great deal of interest in the concept, development and implementation of medical digital twins. This interest has led to wide ranging perceptions of what constitutes a medical digital twin. This Perspectives article will provide 1) a description of fundamental features of industrial digital twins, the source of the digital twin concept,…
Both machine learning and mechanistic modelling approaches have been used independently with great success in systems biology. Machine learning excels in deriving statistical relationships and quantitative prediction from data, while mechanistic modelling is a powerful approach to capture knowledge and infer causal mechanisms underpinning biological phenomena. Importantly, the strengths of one are the weaknesses of…
Mathematical modeling has made significant contributions to drug design, development, and optimization. Virtual clinical trials that integrate mathematical models to explore patient heterogeneity and its impact on a variety of therapeutic questions have recently risen in popularity. Here, we outline best practices for creating virtual patients from mathematical models to ultimately implement and execute a…
