ArticleScientific reports2021
Deciphering the generating rules and functionalities of complex networks.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed.
- Article
- Graph-Theory Approach to Element Miscibility and Alloy Design.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Topological Environment in Genetic and Metabolic Networks.bioRxiv : the preprint server for biology · 2026Article
- Hallmarks of disease: how tuned hierarchies of intelligent molecular neural networks (MNNs) may matter.Endocrine-related cancer · 2026Review
- CENTRA: knowledge-based gene contextuality graphs reveal functional master regulators by centrality and fractality.NAR genomics and bioinformatics · 2025Article
- Spiking dynamics of individual neurons reflect changes in the structure and function of neuronal networks.Nature communications · 2025Article
- Polygenic prediction and gene regulation networks.Royal Society open science · 2025Article
- Autocatalytic Nucleation and Self-Assembly of Inorganic Nanoparticles into Complex Biosimilar Networks.Angewandte Chemie (International ed. in English) · 2025Article
- The impact of physical activity and dietary behavior on depression in college students: a study on mediation effects and network analysis.Frontiers in public health · 2025Article
- Effective methods and framework for energy-based local learning of deep neural networks.Frontiers in artificial intelligence · 2025Article
- Graph Theoretical Description of Phase Transitions in Complex Multiscale Phases with Supramolecular Assemblies.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- From pixels to connections: exploring in vitro neuron reconstruction software for network graph generation.Communications biology · 2024Review
- Postural control in gymnasts: anisotropic fractal scaling reveals proprioceptive reintegration in vestibular perturbation.Frontiers in network physiology · 2024Article
- Complexity synchronization in living matter: a mini review.Frontiers in network physiology · 2024Review
- GAHLS: an optimized graph analytics based high level synthesis framework.Scientific reports · 2023Article
- The role of long-term power-law memory in controlling large-scale dynamical networks.Scientific reports · 2023Article
- A unified approach of detecting phase transition in time-varying complex networks.Scientific reports · 2023Article
- Network bypasses sustain complexity.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Hierarchical growth in neural networks structure: Organizing inputs by Order of Hierarchical Complexity.PloS one · 2023Article
- Case report: Cortico-ocular interaction networks in NBA2K.Frontiers in network physiology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Network theory helps us understand, analyze, model, and design various complex systems. Complex networks encode the complex topology and structural interactions of various systems in nature. To mine the multiscale coupling, heterogeneity, and complexity of natural and technological systems, we need expressive and rigorous mathematical tools that can help us understand the growth, topology, dynamics, multiscale structures, and functionalities of complex networks and their interrelationships. Towards this end, we construct the node-based fractal dimension (NFD) and the node-based multifractal analysis (NMFA) framework to reveal the generating rules and quantify the scale-dependent topology and multifractal features of a dynamic complex network. We propose novel indicators for measuring the degree of complexity, heterogeneity, and asymmetry of network structures, as well as the structure distance between networks. This formalism provides new insights on learning the energy and phase transitions in the networked systems and can help us understand the multiple generating mechanisms governing the network evolution.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.