Experiments
Searchable full-text extractions: founding hypothesis, core claims, experimental setups, key results and statistics — pulled out of each paper as structure. Search a cell line, an assay or an entity (e.g. HUH7) and find every paper that worked with it. This corpus stands on its own: most entries carry no reproduction assessment (yet).
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Has reproduction · 44
Weighted gene co-expression network analysis reveals that CXCL10, IRF7, MX1, RSAD2, and STAT1 are related to the chronic stage of spinal cord injury.
PMID 34532385 · PMC8421925 · Annals of translational medicine · 2021 · 8 claims · 7 setups
The brown co-expression module (775 genes) is the module most significantly associated with the chronic stage of SCI
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Has reproduction · 97
Identification of immune-related signatures and pathogenesis differences between thoracic aortic aneurysm patients with bicuspid versus tricuspid valves via weighted gene co-expression network analysis.
PMID 37883426 · PMC10602290 · PloS one · 2023 · 6 claims · 7 setups
TAA/TAV pathogenesis is more associated with immune-related gene expression than TAA/BAV, with two WGCNA gene modules (brown and blue) enriched for immune functions.
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Integrated weighted gene co-expression network analysis with an application to chronic fatigue syndrome.
PMID 18986552 · PMC2625353 · BMC systems biology · 2008 · 8 claims · 6 setups
Integrated WGCNA (IWGCNA), which adds genetic marker-based causality testing to standard WGCNA, can identify a disease-related module and its causal drivers
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Has reproduction · 79
TSUNAMI: Translational Bioinformatics Tool Suite for Network Analysis and Mining.
PMID 33705981 · PMC9403021 · Genomics, proteomics & bioinformatics · 2021 · 8 claims · 6 setups
TSUNAMI is a freely accessible web-based tool suite that mines gene co-expression network (GCN) modules from public (GEO, TCGA) or user-uploaded numerical omics data and performs downstream gene set enrichment analysis.
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Has reproduction · 51
SGCP: a spectral self-learning method for clustering genes in co-expression networks.
PMID 38956463 · PMC11221046 · BMC bioinformatics · 2024 · 7 claims · 4 setups
SGCP, a spectral self-learning method, yields gene co-expression modules with higher GO enrichment than WGCNA, CoExpNets, and CEMiTool across 12 real gene expression datasets.
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Has reproduction · 78
Enhancing chemotherapy response prediction via matched colorectal tumor-organoid gene expression analysis and network-based biomarker selection.
PMID 39754813 · PMC11754497 · Translational oncology · 2025 · 6 claims · 8 setups
A consensus WGCNA approach combining matched tumor-organoid and independent organoid drug-response expression data identifies gene modules and hub genes predictive of 5-FU chemotherapy response
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Has reproduction · 92
A network-guided protocol to discover susceptibility genes in genome-wide association studies using stability selection.
PMID 36609152 · PMC9850185 · STAR protocols · 2023 · 5 claims · 5 setups
The protocol identifies genes that are both statistically associated with a phenotype and functionally interconnected in a biological network
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Has reproduction · 59
Comparing time series transcriptome data between plants using a network module finding algorithm.
PMID 31164912 · PMC6544932 · Plant methods · 2019 · 8 claims · 6 setups
Converting time-series expression data into co-expression networks and applying network module finding (OrthoClust) enables cross-species comparison without requiring one-to-one developmental stage mapping.
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Has reproduction · 55
Gene module regulation in dilated cardiomyopathy and the role of Na/K-ATPase.
PMID 35901050 · PMC9333241 · PloS one · 2022 · 5 claims · 8 setups
Several co-expressed gene modules are significantly associated with left ventricle ejection fraction (LVEF) and the DCM phenotype, enriched in fibrosis-related, small molecule transporting-related, and immune response-related pathways.
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Has reproduction · 83
Functional module detection through integration of single-cell RNA sequencing data with protein-protein interaction networks.
PMID 33138772 · PMC7607865 · BMC genomics · 2020 · 8 claims · 6 setups
scPPIN integrates scRNA-seq-derived p-values with PPINs to detect maximum-weight connected subgraphs (active/functional modules) via an exact Steiner-tree approach
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Identification of the proliferation/differentiation switch in the cellular network of multicellular organisms.
PMID 17166053 · PMC1664705 · PLoS computational biology · 2006 · 8 claims · 8 setups
Integrating interactome and transcriptome data reveals a pair of transcriptionally anticorrelated network modules (P and D) each comprising hundreds of genes, present across individuals and species.
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Has reproduction · 58
Identification of common genetic characteristics of rheumatoid arthritis and major depressive disorder by bioinformatics analysis and machine learning.
PMID 37415981 · PMC10320004 · Frontiers in immunology · 2023 · 7 claims · 8 setups
EAF1, SDCBP and RNF19B are common genetic characteristics (hub genes) shared by RA and MDD
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Has reproduction · 84
Network Controllability Reveals Key Mitigation Points for Tumor-Promoting Signaling in Tumor-Educated Platelets.
PMID 41226816 · PMC12609506 · International journal of molecular sciences · 2025 · 8 claims · 6 setups
TEPs in NSCLC show 111 upregulated and 108 downregulated genes versus non-cancer control platelets, enriched in ECM interaction, cytoskeleton, immune signaling, and platelet activation pathways.
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Has reproduction · 100
Gene co-expression network analysis in human spinal cord highlights mechanisms underlying amyotrophic lateral sclerosis susceptibility.
PMID 33707641 · PMC7970949 · Scientific reports · 2021 · 8 claims · 8 setups
WGCNA on control human cervical spinal cord RNA-seq identifies 13 co-expression modules (SC.M1-M13), each representing distinct biological processes or cell types.
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Has reproduction · 71
Parsimonious Gene Correlation Network Analysis (PGCNA): a tool to define modular gene co-expression for refined molecular stratification in cancer.
PMID 30993001 · PMC6459838 · NPJ systems biology and applications · 2019 · 8 claims · 7 setups
Retaining only the top ~3 most correlated edges per gene (EPG3) combined with FastUnfold clustering (termed PGCNA) produces gene co-expression modules with significantly better separation and enrichment of known biology than using all edges or other clustering methods.
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Analysis of protein sequence and interaction data for candidate disease gene prediction.
PMID 17020920 · PMC1636487 · Nucleic acids research · 2006 · 8 claims · 7 setups
Combining CPS and CMP using known disease genes as input achieves sensitivity 0.52 and specificity 0.97, reducing candidate lists 13-fold
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Evolutionary origins of human apoptosis and genome-stability gene networks.
PMID 18832373 · PMC2577361 · Nucleic acids research · 2008 · 8 claims · 8 setups
The entanglement of DNA repair, chromosome stability and apoptosis gene networks appears with the caspase gene family and the antiapoptotic gene BCL2.
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Multi-organ expression profiling uncovers a gene module in coronary artery disease involving transendothelial migration of leukocytes and LIM domain binding 2: the Stockholm Atherosclerosis Gene Expression (STAGE) study.
PMID 19997623 · PMC2780352 · PLoS genetics · 2009 · 8 claims · 6 setups
Functionally associated gene modules, not individual genes, underlie CAD development and can be identified via multi-organ expression clustering
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Has reproduction · 77
Electroacupuncture reshapes the microbial co-occurrence networks related to the behavioral and psychological symptoms of dementia in Alzheimer's disease.
PMID 41676443 · PMC12806058 · iMetaOmics · 2025 · 6 claims · 7 setups
Electroacupuncture reshapes microbial co-occurrence network topology and drives keystone species in AD-related BPSD, with R. gnavus emerging as a likely keystone species post-intervention.
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Has reproduction · 80
Colorectal Cancer Prediction Based on Weighted Gene Co-Expression Network Analysis and Variational Auto-Encoder.
PMID 32825264 · PMC7563725 · Biomolecules · 2020 · 6 claims · 7 setups
Combining WGCNA-derived hub genes with a VAE-derived 10-dimensional representation as features for an SVM classifier achieves high accuracy (0.9692) and AUC (0.9981) for colorectal cancer prediction.