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 · 90
Prioritized mass spectrometry increases the depth, sensitivity and data completeness of single-cell proteomics.
PMID 37012480 · PMC10172113 · Nature methods · 2023 · 8 claims · 5 setups
pSCoPE (prioritized precursor selection via MaxQuant.Live) increases sensitivity, data completeness, and proteome coverage more than twofold over shotgun single-cell proteomics
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Full-text index only
scSurv: a deep generative model for single-cell survival analysis.
PMID 41429574 · PMC12797213 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 6 setups
scSurv combines a Cox proportional hazards model with a deep generative model (VAE) of single-cell transcriptomes to estimate individual cellular contributions to clinical outcomes
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Has reproduction · 85
Prediction of condition-specific regulatory genes using machine learning.
PMID 32329779 · PMC7293043 · Nucleic acids research · 2020 · 8 claims · 6 setups
ConSReg integrates expression, DAP-seq TF-DNA binding, and ATAC-seq open chromatin data into machine learning models to predict condition-specific regulatory genes
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Has reproduction · 38
RNA-Seq transcriptome profiling of upland cotton (Gossypium hirsutum L.) root tissue under water-deficit stress.
PMID 24324815 · PMC3855774 · PloS one · 2013 · 8 claims · 8 setups
A total of 1,530 transcripts were differentially expressed between well-watered and water-deficit stressed field-grown upland cotton root tissues (913 up-regulated, 617 down-regulated).
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Has reproduction · 90
Optimal Dual RNA-Seq Mapping for Accurate Pathogen Detection in Complex Eukaryotic Hosts.
PMID 39959292 · PMC11825298 · Bio-protocol · 2025 · 7 claims · 6 setups
Mapping adapter-trimmed reads first to the pathogen genome recovers more pathogen reads than the traditional host-first mapping approach.