ArticleBioData mining2011
Using graph theory to analyze biological networks.
Article in BioData mining, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 242 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
242 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- 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
- Integrative bioinformatics frameworks for abdominal aortic aneurysm using GWAS meta-analysis, biological network construction, and structural modeling.Scientific reports · 2025Pooled it
- Analysis of the Whole CDR3 T Cell Receptor Repertoire after Hematopoietic Stem Cell Transplantation in 2 Clinical Cohorts.Biology of blood and marrow transplantation : journal of the American Society for Blood and Marrow Transplantation · 2020Trial
- Evolutionary Reorganization of Transcriptomic Architecture Across a UVB Tolerance Gradient in Fish.Ecology and evolution · 2026Article
- The Effect of Mycorrhization with Fungi of Different Efficiency on the Root Metabolome ofInternational journal of molecular sciences · 2026Article
- Machine Learning and Deep Learning Frameworks for Human-Virus Protein-Protein Interaction Prediction: Emerging Architectures, Methods, Benchmarks, and Challenges.International journal of molecular sciences · 2026Review
- Data-intensive immune network modelling for One Health.Briefings in bioinformatics · 2026Review
- Network-Based, Cross-Sectional Analysis of Drug-Related Problems Reveals a Strong Association of Possible Inappropriate Medication and Clinical Outcomes in Romanian Elderly Nursing Home Residents.Medical sciences (Basel, Switzerland) · 2026Article
- Indices of trophic and competitive relationships in a planktonic meta-network of carp ponds.Scientific reports · 2026Article
- Artificial intelligence in drug research and development: a review of methods and applications in drug repurposing.Briefings in bioinformatics · 2026Review
- A manually curated gene-phenotype catalogue for progeroid syndromes and premature aging.Aging · 2026Article
- Evaluating network-based algorithms for protein function prediction using plant protein-protein interaction networks.BMC plant biology · 2026Article
- In silico interactome analysis reveals distinct and complementary metabolic roles of bacteria in stingless bee larval food.Computational and structural biotechnology journal · 2026Article
- Integrative gene co-expression network analysis reveals protein-coding and LncRNA genes associated with Alzheimer's disease pathology.Scientific reports · 2025Article
- Identifying key regulators in neuronal transdifferentiation by gene regulatory network analysis.PNAS nexus · 2025Article
- A graph-theoretic framework for quantitative analysis of angiogenic networks.BioData mining · 2025Article
- Metabolic profiles of squamous cell lung carcinoma and diagnostic model construction.Scientific reports · 2025Article
- Sex and age-specific multimorbidity profiles among working-age inpatients in China: a comparative network analysis.BMC public health · 2025Article
- A systems approach for elucidating the role of the microbiome in epigenetic cellular memory.mSystems · 2025Review
- Exploring population and sex-specific disease trajectories for multimorbidities among individuals with overweight or obesity: A retrospective cohort study in UK biobank.Diabetes, obesity & metabolism · 2025Article
182 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Understanding complex systems often requires a bottom-up analysis towards a systems biology approach. The need to investigate a system, not only as individual components but as a whole, emerges. This can be done by examining the elementary constituents individually and then how these are connected. The myriad components of a system and their interactions are best characterized as networks and they are mainly represented as graphs where thousands of nodes are connected with thousands of vertices. In this article we demonstrate approaches, models and methods from the graph theory universe and we discuss ways in which they can be used to reveal hidden properties and features of a network. This network profiling combined with knowledge extraction will help us to better understand the biological significance of the system.
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.