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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TDAGENE: Inference of Gene Regulatory Network Based on Topological Data Analysis and Graph Attention Network for Single-Cell RNA Sequencing Data.
PMID 42093817 · PMC13139726 · Computational and structural biotechnology journal · 2026 · 7 claims · 5 setups
TDAGENE combines TDA features with a multilayer GAT via gate-controlled fusion to improve GRN inference accuracy
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GRNFormer: accurate gene regulatory network inference using graph transformer.
PMID 41883144 · PMC13069479 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 8 setups
GRNFormer is a generalizable graph transformer framework for GRN inference from single-cell or bulk transcriptomics data across species, cell types, and platforms without cell-type annotations or prior regulatory information
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AutoGERN: single-cell RNA-seq gene regulatory network inference via explicit link modeling and adaptive architectures.
PMID 41871930 · PMC13064981 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 3 setups
AutoGERN explicitly models regulatory information in the message-passing space via learned link (edge) embeddings, which are scored by a lightweight MLP to infer TF–target interactions.
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Has reproduction · 75
Identification of Key Differentially Expressed Genes in Arabidopsis thaliana Under Short- and Long-Term High Light Stress.
PMID 40869111 · PMC12386182 · International journal of molecular sciences · 2025 · 8 claims · 6 setups
Meta-analysis of 21 experiments covering 58 HL conditions yielded ~218,000 DEG instances corresponding to ~19,000 unique A. thaliana genes
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Has reproduction · 85
A mechanistic model captures the emergence and implications of non-genetic heterogeneity and reversible drug resistance in ER+ breast cancer cells.
PMID 34316714 · PMC8271219 · NAR cancer · 2021 · 7 claims · 8 setups
EMT and tamoxifen-resistance (TamR) regulatory axes can drive one another, enabling non-genetic heterogeneity via six co-existing phenotypes (ES, ER, HS, HR, MS, MR)
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PSGRN: Gene regulatory network inference from single-cell perturbational data through self-training with synthetic gold standards.
PMID 42054465 · PMC13127566 · Science advances · 2026 · 8 claims · 4 setups
PSGRN infers GRNs by generating pseudoannotations from gene-gene correlations and iteratively refining them via a self-training classifier using pre/post-intervention expression features.
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Has reproduction · 70
Spatial transcriptomics reveals the molecular signatures of prodromal and advanced α-synucleinopathy.
PMID 41736854 · PMC12927100 · iScience · 2026 · 7 claims · 6 setups
Early-stage (prodromal) aSyn pathology in M83+/+ mouse brainstem is associated with upregulation of ATP/energy metabolism pathways (glycolysis, oxidative phosphorylation, fatty acid metabolism)
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Has reproduction · 59
Advances in genomic and pharmacokinetic profiling for clinical stratification of metastatic breast cancer.
PMID 41369820 · PMC12799884 · Discover oncology · 2025 · 8 claims · 8 setups
Key genes AR, AKT1, UBC, CDH1, SMAD3, ROR1, and ROR2 are associated with chemotherapy resistance and poor prognosis in metastatic breast cancer
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Has reproduction · 95
A systems-level analysis of the mutually antagonistic roles of RKIP and BACH1 in dynamics of cancer cell plasticity.
PMID 37963558 · PMC10645512 · Journal of the Royal Society, Interface · 2023 · 8 claims · 7 setups
RKIP and BACH1 are negatively correlated with each other across most cancer types in TCGA
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Interpretable learning of temporal cellular dynamics from single-cell data.
PMID 41875867 · PMC13030976 · Cell reports methods · 2026 · 7 claims · 7 setups
NeuroVelo couples a linear latent phase-space projection with a non-linear neural ODE, using RNA velocity as a physics-informed loss penalty, to jointly model cellular dynamics and enable gene-level interpretability