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 · 64
Starvation-induced transgenerational inheritance of small RNAs in C. elegans.
PMID 25018105 · PMC4377509 · Cell · 2014 · 8 claims · 7 setups
L1 starvation induces changes in endogenous 22G small RNAs (STGs) that are inherited for at least three generations in fed descendants.
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Has reproduction · 100
A comprehensive framework for analysis of microRNA sequencing data in metastatic colorectal cancer.
PMID 35047825 · PMC8759566 · NAR cancer · 2022 · 7 claims · 7 setups
Five miRNAs (Mir-210_3p, Mir-191_5p, Mir-8-P1b_3p [miR-141-3p], Mir-1307_5p, Mir-155_5p) are up-regulated at multiple metastatic sites in colorectal cancer.
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Has reproduction
miRge3.0: a comprehensive microRNA and tRF sequencing analysis pipeline.
PMID 34308351 · PMC8294687 · NAR genomics and bioinformatics · 2021 · 6 claims · 5 setups
miRge3.0 with 12 CPUs consistently has the best execution speed compared to miRge2.0, Chimira and sRNAbench
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Has reproduction · 74
An open RNA-Seq data analysis pipeline tutorial with an example of reprocessing data from a recent Zika virus study.
PMID 27583132 · PMC4972086 · F1000Research · 2016 · 6 claims · 6 setups
An open-source, reproducible RNA-seq pipeline delivered as an IPython notebook and Docker image can process raw RNA-seq data into interactive PCA/HC plots, enrichment results, and small-molecule predictions with minimal setup overhead
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Has reproduction · 65
Interpretable and integrative analysis of single-cell multiomics with scMKL.
PMID 40770488 · PMC12328712 · Communications biology · 2025 · 8 claims · 7 setups
scMKL combines multiple kernel learning with random Fourier features and group Lasso to jointly model transcriptomic and epigenomic single-cell data interpretably