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).

• Dynamic Gene Attention Focus (DyGAF): Enhancing Biomarker Identification Through Dual-Model Attention Networks.

  PMID 40160891 · PMC11951896 · Bioinformatics and biology insights · 2025 · 6 claims · 5 setups

  Has reproduction · 44

  DyGAF, a dual-model attention neural network (independent Model A + dependent Model B), identifies and ranks genes by significance for COVID-19 biomarker discovery more effectively than differential expression analysis (DEA) and random forest (RF) feature selection

  nasopharyngeal same dygaf-ranked bulk differential random

• Decoding unchanged transcriptome of Alzheimer's disease reveals an NCAM1 mRNA switch as a potential biomarker.

  PMID 42006342 · PMC13090632 · iScience · 2026 · 8 claims · 7 setups

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  Most genes are gene-level non-differentially expressed (nDEGs) in AD but nDEGs are strongly associated with neuronal function pathways

  hippocampus brain bulk alternative isoform

• Molecular profiling of breast cancer in native American women reveals distinct genomic and transcriptomic features.

  PMID 41844957 · PMC13144316 · NPJ precision oncology · 2026 · 8 claims · 6 setups

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  This is the first multi-omics (mutation, CNV, RNA-seq) characterization of breast tumors from Native American women, providing a resource for future studies

  breast degs targeted panel-derived whole-transcriptome

• Annotation-free prediction of immunotherapy response in melanoma using single-cell transcriptomic data.

  PMID 41758825 · PMC12948085 · PloS one · 2026 · 8 claims · 6 setups

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  AI-based predictive models built on unannotated scRNA-seq data (cell-by-gene expression matrices) can classify melanoma patients as ICI responders vs. non-responders

  cd45+ scrna-seq independent scrna-seq single-gene-level pathway-level

• Assessment of dispersion metrics for estimating single-cell transcriptional variability.

  PMID 41770747 · PMC12970974 · PLoS computational biology · 2026 · 7 claims · 4 setups

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  The variance-to-mean ratio (VMR/Fano factor) scales approximately linearly with increasing dispersion and is independent of dataset size.

  simulated manivannan lana-elola yuzwa computational scrna-seq