ReviewGenetics, selection, evolution : GSE2016
Using biological networks to integrate, visualize and analyze genomics data.
Review in Genetics, selection, evolution : GSE, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 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
59 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Genome-Wide Gene-Set Analysis Identifies Molecular Mechanisms Associated with ALS.International journal of molecular sciences · 2023Pooled it
- Meta-analysis of Transcriptomic Data Reveals Pathophysiological Modules Involved with Atrial Fibrillation.Molecular diagnosis & therapy · 2020Pooled it
- Testican-1-MMP axis in tumour extracellular matrix (ECM) remodelling: interaction dynamics analysis and an in silico perspective.The Journal of pathology · 2026Article
- NOVAGene: a nonlinear approach to improve biological resolution in weighted gene co-expression networks for low-variability datasets.Frontiers in bioinformatics · 2026Article
- From network biology to immunity: potential longitudinal biomarkers for targeting the network topology of the HIV reservoir.Journal of translational medicine · 2025Review
- Computational pharmacology-based molecular mechanism investigation of cinnamaldehyde intervention in nephrotic syndrome.Naunyn-Schmiedeberg's archives of pharmacology · 2025Article
- Network insights into childhood obesity: unveiling methylated-differentially expressed genes and pathways through integrative bioinformatics analysis.Endocrine connections · 2025Article
- Operating principles of interconnected feedback loops driving cell fate transitions.NPJ systems biology and applications · 2025Article
- Bioinformatics-Driven Investigations of Signature Biomarkers for Triple-Negative Breast Cancer.Bioinformatics and biology insights · 2025Article
- Drug Repurposing: Insights into Current Advances and Future Applications.Current medicinal chemistry · 2025Review
- Article
- List2Net: Linking multiple lists of biological data in a network context.Computational and structural biotechnology journal · 2024Article
- From Genomics to Metabolomics: Molecular Insights into Osteoporosis for Enhanced Diagnostic and Therapeutic Approaches.Biomedicines · 2024Review
- Network Pharmacology Approaches Used to Identify Therapeutic Molecules for Chronic Venous Disease Based on Potential miRNA Biomarkers.Journal of xenobiotics · 2024Article
- A Tiny Viral Protein, SARS-CoV-2-ORF7b: Functional Molecular Mechanisms.Biomolecules · 2024Article
- Article
- Overlapping action of TFrontiers in endocrinology · 2024Article
- Construction of an Exudative Age-Related Macular Degeneration Diagnostic and Therapeutic Molecular Network Using Multi-Layer Network Analysis, a Fuzzy Logic Model, and Deep Learning Techniques: Are Retinal and Brain Neurodegenerative Disorders Related?Pharmaceuticals (Basel, Switzerland) · 2023Article
- Exploring pathway interactions to detect molecular mechanisms of disease: 22q11.2 deletion syndrome.Orphanet journal of rare diseases · 2023Article
- Systems Biology and Cytokines Potential Role in Lung Cancer Immunotherapy Targeting Autophagic Axis.Biomedicines · 2023Review
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
No grant is acknowledged in the PubMed record.
Abstract
Network biology is a rapidly developing area of biomedical research and reflects the current view that complex phenotypes, such as disease susceptibility, are not the result of single gene mutations that act in isolation but are rather due to the perturbation of a gene's network context. Understanding the topology of these molecular interaction networks and identifying the molecules that play central roles in their structure and regulation is a key to understanding complex systems. The falling cost of next-generation sequencing is now enabling researchers to routinely catalogue the molecular components of these networks at a genome-wide scale and over a large number of different conditions. In this review, we describe how to use publicly available bioinformatics tools to integrate genome-wide 'omics' data into a network of experimentally-supported molecular interactions. In addition, we describe how to visualize and analyze these networks to identify topological features of likely functional relevance, including network hubs, bottlenecks and modules. We show that network biology provides a powerful conceptual approach to integrate and find patterns in genome-wide genomic data but we also discuss the limitations and caveats of these methods, of which researchers adopting these methods must remain aware.
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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.