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 · 67
Sequencing mRNA from cryo-sliced Drosophila embryos to determine genome-wide spatial patterns of gene expression.
PMID 23951250 · PMC3741199 · PloS one · 2013 · 8 claims · 8 setups
Cryosectioning single blastoderm-stage D. melanogaster embryos along the A–P axis and sequencing mRNA from each slice yields reliable genome-wide spatial expression patterns.
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Has reproduction · 90
Developmental hematopoietic stem cell variation explains clonal hematopoiesis later in life.
PMID 39592593 · PMC11599844 · Nature communications · 2024 · 8 claims · 2 setups
Weak selection conferred by HSC variation created before birth can reliably yield clonal hematopoiesis later in life, demonstrated via shared prenatal circulation of monozygotic (MZ) twins.
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scGeno: a Hidden Markov Model approach to denoise chromosome-scale genotypes from single-cell data.
PMID 41982479 · PMC13075984 · Bioinformatics advances · 2026 · 7 claims · 4 setups
scGeno, a categorical HMM, infers chromosome-level genotype states in mixed-genotype organisms by modeling sequential single-cell allelic expression ratios along chromosomes
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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 gene expression patterns into co-expression networks and applying a cross-species network module finding algorithm (OrthoClust with simulated annealing) solves the problem of matching developmental stages between two species without requiring one-to-one stage mapping.
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Integrative Transcriptomic Analysis and Co-Expression Network Characterization of Soybean Developmental Tissues.
PMID 41977661 · PMC13075193 · Plants (Basel, Switzerland) · 2026 · 8 claims · 6 setups
Tissue identity (seed vs. non-seed) is the dominant driver of transcriptomic variation, as shown by clear separation on PC1
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Interpretable, flexible and spatially aware integration of multiple spatial transcriptomics datasets from diverse sources.
PMID 42045691 · PMC13175893 · Nature genetics · 2026 · 6 claims · 7 setups
INSPIRE is a deep-learning method that unifies adversarial learning with a GNN-based encoder and integrated NMF to interpretably integrate multiple spatial transcriptomics datasets