ArticleScientific reports2015
Quantitative assessment of gene expression network module-validation methods.
Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Co-expression Gene Networks and Machine-learning Algorithms Unveil a Core Genetic Toolkit for Reproductive Division of Labour in Rudimentary Insect Societies.Genome biology and evolution · 2023Pooled it
- Multi-scale geometric network analysis identifies melanoma immunotherapy response gene modules.Scientific reports · 2024Article
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- C3NA: correlation and consensus-based cross-taxonomy network analysis for compositional microbial data.BMC bioinformatics · 2022Article
- GWENA: gene co-expression networks analysis and extended modules characterization in a single Bioconductor package.BMC bioinformatics · 2021Article
- A framework for stability-based module detection in correlation graphs.Statistical analysis and data mining · 2021Article
- Bioinformatics analysis of common key genes and pathways of intracranial, abdominal, and thoracic aneurysms.BMC cardiovascular disorders · 2021Article
- Transcriptional Analysis of Nuclear-Encoded Mitochondrial Genes in Eight Neurodegenerative Disorders: The Analysis of Seven Diseases in Reference to Friedreich's Ataxia.Frontiers in genetics · 2021Article
- Essential Oil Phytocomplex Activity, a Review with a Focus on Multivariate Analysis for a Network Pharmacology-Informed Phytogenomic Approach.Molecules (Basel, Switzerland) · 2020Review
- Erosion of Gene Co-expression Networks Reveal Deregulation of Immune System Processes in Late-Onset Alzheimer's Disease.Frontiers in neuroscience · 2020Article
- Functional homogeneity and specificity of topological modules in human proteome.BMC bioinformatics · 2019Article
- Network-Wide Screen Identifies Variation of Novel Precise On-Module Targets Using Conformational Modudaoism.CPT: pharmacometrics & systems pharmacology · 2018Article
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Authors and funding
7 authors.
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Abstract
Validation of pluripotent modules in diverse networks holds enormous potential for systems biology and network pharmacology. An arising challenge is how to assess the accuracy of discovering all potential modules from multi-omic networks and validating their architectural characteristics based on innovative computational methods beyond function enrichment and biological validation. To display the framework progress in this domain, we systematically divided the existing Computational Validation Approaches based on Modular Architecture (CVAMA) into topology-based approaches (TBA) and statistics-based approaches (SBA). We compared the available module validation methods based on 11 gene expression datasets, and partially consistent results in the form of homogeneous models were obtained with each individual approach, whereas discrepant contradictory results were found between TBA and SBA. The TBA of the Zsummary value had a higher Validation Success Ratio (VSR) (51%) and a higher Fluctuation Ratio (FR) (80.92%), whereas the SBA of the approximately unbiased (AU) p-value had a lower VSR (12.3%) and a lower FR (45.84%). The Gray area simulated study revealed a consistent result for these two models and indicated a lower Variation Ratio (VR) (8.10%) of TBA at 6 simulated levels. Despite facing many novel challenges and evidence limitations, CVAMA may offer novel insights into modular networks.
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