ReviewFrontiers in bioengineering and biotechnology2020
A Guide to Conquer the Biological Network Era Using Graph Theory.
Review in Frontiers in bioengineering and biotechnology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 101 papers, 2 of them syntheses that pooled it.
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
101 citing papers in PubMed, 2 syntheses or guidelines pooled it, 270 citations in OpenAlex.
- A Systematic Review of the Application of Graph Neural Networks to Extract Candidate Genes and Biological Associations.American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics · 2025Pooled it
- Structural and Pharmacological Network Focused on MiRNAs Involved in Rheumatoid Arthritis: A Systematic Review.Current molecular medicine · 2024Pooled it
- Transcription clusters and developmental pathways - nature, nurture, noise.Journal of cell science · 2026Review
- DataXflowGen for GenAI-driven model generation.Scientific reports · 2026Article
- MetaNet: a scalable and integrated tool for reproducible omics network analysis.Bioinformatics (Oxford, England) · 2026Article
- Evaluating network-based algorithms for protein function prediction using plant protein-protein interaction networks.BMC plant biology · 2026Article
- Global genetic rewiring during compensatory evolution in the yeast polarity network.EMBO reports · 2026Article
- Next-Generation Biopesticides for the Control of Fungal Plant Pathogens.Plants (Basel, Switzerland) · 2026Review
- Article
- Functional Interpretation of Omics Data: From Pathways to Networks.Advances in experimental medicine and biology · 2026Review
- TempSnap-Trace: A temporal snapshot-based framework for haplotype network tracing.Biosafety and health · 2025Article
- Integrative transcriptomics and network analysis reveals core genes driving meningioma pathogenesis and clinical outcomes.Scientific reports · 2025Article
- A graph-theoretic framework for quantitative analysis of angiogenic networks.BioData mining · 2025Article
- The Evolution of Systems Biology and Systems Medicine: From Mechanistic Models to Uncertainty Quantification.Annual review of biomedical engineering · 2025Review
- Cerebral cortical functional hyperconnectivity in a mouse model of spinocerebellar ataxia type 8 (SCA8).Neurobiology of disease · 2025Article
- Lower Ricci Curvature for Efficient Community Detection.Transactions on machine learning research · 2025Article
- ACT2.6: Global Gene Coexpression Network inGenes · 2025Article
- The different impacts of functional network centrality and connectivity on the complexity of brain signals in healthy control and first-episode drug-naïve patients with major depressive disorder.Brain imaging and behavior · 2025Article
- RWRtoolkit: multi-omic network analysis using random walks on multiplex networks in any species.GigaScience · 2025Article
- Simplicity within biological complexity.Bioinformatics advances · 2025Article
41 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Networks are one of the most common ways to represent biological systems as complex sets of binary interactions or relations between different bioentities. In this article, we discuss the basic graph theory concepts and the various graph types, as well as the available data structures for storing and reading graphs. In addition, we describe several network properties and we highlight some of the widely used network topological features. We briefly mention the network patterns, motifs and models, and we further comment on the types of biological and biomedical networks along with their corresponding computer- and human-readable file formats. Finally, we discuss a variety of algorithms and metrics for network analyses regarding graph drawing, clustering, visualization, link prediction, perturbation, and network alignment as well as the current state-of-the-art tools. We expect this review to reach a very broad spectrum of readers varying from experts to beginners while encouraging them to enhance the field further.
Indexed as
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.