Topic Editors

Department of Science and High Technology, Università degli Studi dell’Insubria, Via Valleggio, 9, 22100 Como, CO, Italy
Department of Science and High Technology, University of Insubria, 22100 Como, Italy

Systems Biology and Network Medicine: From Bench to Bedside

Abstract submission deadline
closed (30 April 2023)
Manuscript submission deadline
closed (31 July 2023)
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5560

Topic Information

Dear Colleagues,

From single cells to the whole human body, every biological entity must be considered as a complex system where single components interact and influence each other. In this view, both internal and external perturbations, such as disease states or environmental factors, produce effects that can be predicted and interpreted only in the context of a systems biology perspective. This approach entails the use and development of mathematical tools that allow the representation and analysis of biological systems at different levels of complexity; in this context, networks are widely used to represent biological entities (e.g., genes, proteins, metabolites) with their physical and/or functional interactions. The possibility to link the topology and dynamics of such molecular networks to a specific disease state is the basis for the concept of network medicine, which also represents the most important step towards personalized medicine. The aim of the present topic is to publish original articles and reviews where the use of systems biology and network medicine is highlighted as a tool to identify disease mechanisms and to prevent and to treat complex diseases, suggesting novel approaches and strategies to direct clinical practice.

Prof. Dr. Mauro Fasano
Dr. Marta Lualdi
Topic Editors

Keywords

  • systems biology
  • network medicine
  • personalized medicine
  • network topology
  • complex systems
  • artificial intelligence

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Biomolecules
biomolecules
4.8 9.4 2011 16.3 Days CHF 2700
Cells
cells
5.1 9.9 2012 17.5 Days CHF 2700
Genes
genes
2.8 5.2 2010 16.3 Days CHF 2600
International Journal of Molecular Sciences
ijms
4.9 8.1 2000 18.1 Days CHF 2900
AI
ai
3.1 7.2 2020 17.6 Days CHF 1600

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Published Papers (2 papers)

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13 pages, 3345 KiB  
Article
Visual Detection of Stem-Loop Primer Amplification (SPA) Products without Denaturation Using Peroxidase-like DNA Machines (PxDM)
by Yulia I. Maltzeva, Daria A. Gorbenko, Ekaterina V. Nikitina, Maria S. Rubel and Dmitry M. Kolpashchikov
Int. J. Mol. Sci. 2023, 24(9), 7812; https://doi.org/10.3390/ijms24097812 - 25 Apr 2023
Cited by 3 | Viewed by 1518
Abstract
Rapid, inexpensive, and accurate determination of nucleic acids is a decisive factor in evaluating population’s health and monitoring treatment at point-of-care (POC) settings. Testing systems with visual outputs can provide instrument-free signal detection. Isothermal amplification technologies can substitute conventional polymerase chain reaction (PCR) [...] Read more.
Rapid, inexpensive, and accurate determination of nucleic acids is a decisive factor in evaluating population’s health and monitoring treatment at point-of-care (POC) settings. Testing systems with visual outputs can provide instrument-free signal detection. Isothermal amplification technologies can substitute conventional polymerase chain reaction (PCR) testing due to compatibility with the POC diagnostic. Here, we have visually detected DNA fragments obtained by stem-loop-primer-assisted isothermal amplification (SPA), but not those obtained by PCR or LAMP amplification using DNA nanomachines with peroxidase-like activity (PxDM) with sensitivity to a single nucleotide substitution. Compared to the diagnostics with conventional loop-mediated isothermal amplification (LAMP), the PxDM method produces no false positive signals with the non-specific amplification products. The study suggests that PxDM, in conjunction with SPA isothermal amplification, can become a valid platform for POC testing systems. Full article
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21 pages, 779 KiB  
Article
Differentially Expressed Cell Cycle Genes and STAT1/3-Driven Multiple Cancer Entanglement in Psoriasis, Coupled with Other Comorbidities
by Subhashini Dorai and Daniel Alex Anand
Cells 2022, 11(23), 3867; https://doi.org/10.3390/cells11233867 - 30 Nov 2022
Cited by 4 | Viewed by 2679
Abstract
Psoriasis is a persistent T-cell-supported inflammatory cutaneous disorder, which is defined by a significant expansion of basal cells in the epidermis. Cell cycle and STAT genes that control cell cycle progression and viral infection have been revealed to be comorbid with the development [...] Read more.
Psoriasis is a persistent T-cell-supported inflammatory cutaneous disorder, which is defined by a significant expansion of basal cells in the epidermis. Cell cycle and STAT genes that control cell cycle progression and viral infection have been revealed to be comorbid with the development of certain cancers and other disorders, due to their abnormal or scanty expression. The purpose of this study is to evaluate the expression of certain cell cycle and STAT1/3 genes in psoriasis patients and to determine the types of comorbidities associated with these genes. To do so, we opted to adopt the in silico methodology, since it is a quick and easy way to discover any potential comorbidity risks that may exist in psoriasis patients. With the genes collected from early research groups, protein networks were created in this work using the NetworkAnalyst program. The crucial hub genes were identified by setting the degree parameter, and they were then used in gene ontology and pathway assessments. The transcription factors that control the hub genes were detected by exploring TRRUST, and DGIdb was probed for remedies that target transcription factors and hubs. Using the degree filter, the first protein subnetwork produced seven hub genes, including STAT3, CCNB1, STAT1, CCND1, CDC20, HSPA4, and MAD2L1. The hub genes were shown to be implicated in cell cycle pathways by the gene ontology and Reactome annotations. The former four hubs were found in signaling pathways, including prolactin, FoxO, JAK/STAT, and p53, according to the KEGG annotation. Furthermore, they enhanced several malignancies, including pancreatic cancer, Kaposi’s sarcoma, non-small cell lung cancer, and acute myeloid leukemia. Viral infections, including measles, hepatitis C, Epstein–Barr virus, and HTLV-1 and viral carcinogenesis were among the other susceptible diseases. Diabetes and inflammatory bowel disease were conjointly annotated. In total, 129 medicines were discovered in DGIdb to be effective against the transcription factors BRCA1, RELA, TP53, and MYC, as opposed to 10 medications against the hubs, STAT3 and CCND1, in tandem with 8 common medicines. The study suggests that the annotated medications should be tested in suitable psoriatic cell lines and animal models to optimize the drugs used based on the kind, severity, and related comorbidities of psoriasis. Furthermore, a personalized medicine protocol must be designed for each psoriasis patient that displays different comorbidities. Full article
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