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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Ion-Channel-Mediated Drug Repurposing Opportunities Validated by Single-Cell Perturbation in Colorectal Cancer.
PMID 42074061 · PMC13116841 · International journal of molecular sciences · 2026 · 8 claims · 6 setups
WGCNA on CRC transcriptomes identified 100 hub genes spanning three functional programs: ribosomal biogenesis, RNA processing, and immune
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Threshold-dominated regulation hides genetic variation in gene expression networks.
PMID 18062810 · PMC2238762 · BMC systems biology · 2007 · 8 claims · 2 setups
Threshold robustness (insensitivity of a singular/regulating variable's equilibrium value to parameter perturbations, except threshold changes) increases with increasing response function steepness and is present even under Michaelis-Menten conditions, not just in the step-function limit.
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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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A ligand-centered framework for γδ T cell activation in colorectal cancer revealed by single-cell and transformer-based perturbation.
PMID 41607803 · PMC12835328 · Frontiers in immunology · 2025 · 8 claims · 8 setups
CRC-infiltrating γδ T cells show varied activation levels, with the TRM-like population being the major tumor-infiltrating subtype and exhibiting the lowest effector and exhaustion signature scores.
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Characterizing gene perturbations in single cells via network divergence analysis.
PMID 41965857 · PMC13249949 · Nature communications · 2026 · 8 claims · 8 setups
scDNS quantifies gene-specific functional perturbations by measuring Jensen-Shannon divergence between condition-specific gene interaction network configurations
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Unveiling gene perturbation effects through gene regulatory networks inference from single-cell transcriptomic data.
PMID 41984780 · PMC13082667 · PLoS computational biology · 2026 · 7 claims · 4 setups
IGNITE is an unsupervised framework that infers directed, weighted, and signed GRNs directly from unperturbed scRNA-seq data using the inverse problem for a kinetic Ising model.
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Has reproduction · 84
An integrated in silico-in vitro approach for identifying therapeutic targets against osteoarthritis.
PMID 36352408 · PMC9648005 · BMC biology · 2022 · 7 claims · 5 setups
A signal transduction/gene regulatory network model of the articular chondrocyte was built combining knowledge-based curation and data-driven (machine learning) network inference
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BMP and NODAL paracrine signalling regulate the totipotent-like cell state in embryonic stem cells.
PMID 41660012 · PMC12876259 · Frontiers in cell and developmental biology · 2025 · 7 claims · 8 setups
BMP and NODAL (TGF-β) paracrine signalling are key routes of intercellular communication that respectively enhance or diminish the totipotent-like cell (TLC) state in mouse ESCs
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Has reproduction · 53
spliceJAC: transition genes and state-specific gene regulation from single-cell transcriptome data.
PMID 36321549 · PMC9627675 · Molecular systems biology · 2022 · 8 claims · 8 setups
spliceJAC uses unspliced and spliced mRNA count matrices to construct cell state-specific gene-gene regulatory interaction (Jacobian) matrices from scRNA-seq data
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Has reproduction · 100
Computational modeling demonstrates that glioblastoma cells can survive spatial environmental challenges through exploratory adaptation.
PMID 31836713 · PMC6911112 · Nature communications · 2019 · 8 claims · 6 setups
Exploratory adaptation (stochastic gene-regulatory network perturbation) explains how GBM cells adapt phenotypically across spatially distinct tumor regions
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Has reproduction · 59
Integrative network modeling reveals mechanisms underlying T cell exhaustion.
PMID 32024856 · PMC7002445 · Scientific reports · 2020 · 8 claims · 7 setups
TCE arises from changes in diverse gene regulatory interactions across a shared network rather than dysregulation of a single gene
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Glucokinase gene mutations: structural and genotype-phenotype analyses in MODY children from South Italy.
PMID 18382660 · PMC2270336 · PloS one · 2008 · 8 claims · 6 setups
16 of 30 patients with suspected MODY (53%) carry GCK mutations, confirming GCK MODY diagnosis
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Discovery of key regulators in classical monocyte phenotypes linked to COVID-19 severity using single-cell multi-omics sequencing.
PMID 41732268 · PMC12925236 · iScience · 2026 · 8 claims · 8 setups
Two severity-associated classical monocyte (cMono) subtypes, IL7R+ and CD163+, exist with distinct transcriptional and epigenetic landscapes.
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Operon information improves gene expression estimation for cDNA microarrays.
PMID 16630355 · PMC1513396 · BMC genomics · 2006 · 7 claims · 3 setups
A hierarchical Bayesian model that borrows expression information from other genes within the same operon improves estimation of relative transcript levels.
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Multiomics and deep learning dissect regulatory syntax in human development.
PMID 41951735 · PMC13216069 · Nature · 2026 · 8 claims · 8 setups
The Human Development Multiomic Atlas (HDMA) is a single-cell atlas of chromatin accessibility and gene expression from 817,740 fetal cells across 12 organs, spanning 203 cell types
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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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Embeddings from language models are good learners for single-cell data analysis.
PMID 41726097 · PMC12921509 · Patterns (New York, N.Y.) · 2026 · 8 claims · 8 setups
scELMo combines LLM-derived embeddings of gene and cell metadata with raw single-cell expression data via matrix operations to generate cell embeddings without pretraining a new model
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Has reproduction · 55
Single cell analysis reveals the roles and regulatory mechanisms of type-I interferons in Parkinson's disease.
PMID 38566100 · PMC10985960 · Cell communication and signaling : CCS · 2024 · 8 claims · 8 setups
Microglia, endothelial cells, and pericytes exhibit the highest IFN-I activity among PD midbrain cell types, with microglia and endothelial cells showing significantly elevated high-IFN-I-scoring proportions in PD versus controls
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Modeling nascent transcription from chromatin landscape and structure with CLASTER.
PMID 41691282 · PMC13011747 · Genome biology · 2026 · 7 claims · 8 setups
CLASTER, a deep neural network combining chromatin landscape tracks and 3D contact maps, accurately predicts kilobasepair-resolution nascent RNA (EU-seq) profiles in a DNA-sequence-agnostic manner
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PAH-former: Transfer learning for efficient discovery of pulmonary arterial hypertension-associated genes.
PMID 41790620 · PMC12965534 · PloS one · 2026 · 7 claims · 7 setups
PAH-former, a Geneformer model fine-tuned on public PAH scRNA-seq data, can perform in silico perturbation to identify and rank candidate PAH disease-associated genes