We analyze weighted networks as randomly reinforced urn processes, in which the edge-total weights are determined by a reinforcement mechanism. We develop a statistical test and a procedure based on it to study the evolution of networks over time, detecting the "dominance" of some edges with respect to the others and then assessing if a given instance of the network is taken at its steady state or not. Distance from the steady state can be considered as a measure of the relevance of the observed properties of the network. Our results are quite general, in the sense that they are not based on a particular probability distribution or functional form of the random weights. Moreover, the proposed tool can be applied also to dense networks, which have received little attention by the network community so far, since they are often problematic. We apply our procedure in the context of the International Trade Network, determining a core of "dominant edges."
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1103/PhysRevE.87.020106 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Identification of critical biomarkers and immune landscape patterns in glioma based on multi-database.
Discov Oncol
January 2025
Department of Neurosurgery, Changde Hospital, Xiangya School of Medicine, Central South University (The First People's Hospital of Changde City), Changde, 415003, Hunan, China.
Purpose: Glioma is the most prevalent tumor of the central nervous system. The poor clinical outcomes and limited therapeutic efficacy underscore the urgent need for early diagnosis and an optimized prognostic approach for glioma. Therefore, the aim of this study was to identify sensitive biomarkers for glioma.
View Article and Find Full Text PDFPredictors of Potentially Inappropriate Stimulant Prescribing Among Adults.
Pharmacoepidemiol Drug Saf
January 2025
Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, USA.
Purpose: Increases in adult stimulant prescribing pose a potential risk due to the higher prevalence of contraindicated conditions among this population. We sought to identify patient, provider, and visit characteristics predictive of potentially inappropriate adult stimulant prescriptions.
Methods: We conducted a repeated cross-sectional study using the National Ambulatory Medical Care Survey, a nationally representative weighted sample of 5 453 702 723 ambulatory care visits from 2012 to 2019.
End-to-end deep-learning model for the detection of coronary artery stenosis on coronary CT images.
Open Heart
January 2025
Department of Molecular and Clinical Medicine, University of Gothenburg Institute of Medicine, Gothenburg, Sweden.
Purpose: We examined whether end-to-end deep-learning models could detect moderate (≥50%) or severe (≥70%) stenosis in the left anterior descending artery (LAD), right coronary artery (RCA) or left circumflex artery (LCX) in iodine contrast-enhanced ECG-gated coronary CT angiography (CCTA) scans.
Methods: From a database of 6293 CCTA scans, we used pre-existing curved multiplanar reformations (CMR) images of the LAD, RCA and LCX arteries to create end-to-end deep-learning models for the detection of moderate or severe stenoses. We preprocessed the images by exploiting domain knowledge and employed a transfer learning approach using EfficientNet, ResNet, DenseNet and Inception-ResNet, with a class-weighted strategy optimised through cross-validation.
Analysis of key lncRNA related to Parkinson's disease based on gene co-expression weight networks.
Neurosciences (Riyadh)
January 2025
From the School of Clinical Medicine (Liang, Luo, Jia), Shandong Second Medical University, Weifang, from the Department of Neurology (Liang, Zhao, Lin, Li, Luo, Jia) , Beijing Shijingshan Hospital, Shijingshan Teaching Hospital of Capital Medical University, Beijing, and from the Department of Neurology (Li), Affiliated Hospital of Weifang Medical University, Weifang, China.
Objectives: To identify a key Long chain non-coding RNAs (lncRNAs) related to PD and provide a new perspective on the role of LncRNAs in Parkinson's disease (PD) pathophysiology.
Methods: Our study involved analyzing gene chips from the substantia nigra and white blood cells, both normal and PD-inclusive, in the Gene Expression Omnibus (GEO) database, utilizing a weighted gene co-expression network analysis (WGCNA). The technique of WGCNA facilitated the examination of differentially expressed genes (DEGs) in the substantia nigra and the white blood cells of individuals with PD.
Genipin-crosslinked double PLL membranes overcome the strength-diffusion trade-off in cell encapsulation without compromising biocompatibility.
Int J Pharm
January 2025
NanoBioCel Research Group, Laboratory of Pharmaceutics, School of Pharmacy, University of the Basque Country (UPV-EHU), 01006 Vitoria-Gasteiz, Spain; Biomedical Research Networking Centre in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Institute of Health Carlos III, 28029 Madrid, Spain; Bioaraba, NanoBioCel Research Group, 01006 Vitoria-Gasteiz, Spain. Electronic address:
Cell microencapsulation technologies allow non-autologous implantation of therapeutic cells for sustained drug delivery purposes. The perm-selective membrane of these systems provides resistance to rupture, stablishes the upper molecular weight limit in bidirectional diffusion of molecules, and affects biocompatibility. Thus, despite being a decisive factor to succeed in terms of biosafety and therapeutic efficacy, little progress has been made in its optimization so far.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!