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 · 58
MZPAQ: a FASTQ data compression tool.
PMID 31171931 · PMC6547476 · Source code for biology and medicine · 2019 · 7 claims · 3 setups
MZPAQ, a hybrid of MFCompress and ZPAQ, outperforms state-of-the-art and general-purpose compression tools on all benchmark datasets in terms of compression ratio
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Has reproduction · 73
Gapless provides combined scaffolding, gap filling, and assembly correction with long reads.
PMID 37142439 · PMC10166144 · Life science alliance · 2023 · 8 claims · 5 setups
gapless is a new tool that combines assembly correction, scaffolding, and gap filling in one pipeline using PacBio or Oxford Nanopore long reads.
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Full-text index only
StrainMake: reproducible hybrid metagenomics with MAG recovery and strain-level resolution.
PMID 42097292 · PMC13188985 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 5 setups
StrainMake is a Snakemake-based, Conda-managed workflow for de novo metagenomic analysis from short, long, or hybrid sequencing data.
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Full-text index only
The 1000 Chinese Pangenome empowers medical and population genetics.
PMID 41922767 · PMC13233627 · Nature · 2026 · 8 claims · 8 setups
1,116 diploid genome assemblies (55 de novo, 1,061 pangenome-informed) were generated as part of the 1KCP project
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Has reproduction · 71
A crowdsourced set of curated structural variants for the human genome.
PMID 32559231 · PMC7329145 · PLoS computational biology · 2020 · 8 claims · 8 setups
1235 manually curated SVs were produced that can be used to evaluate SV callers or train machine learning models
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Has reproduction · 68
Bayesian transcriptome assembly.
PMID 25367074 · PMC4397945 · Genome biology · 2014 · 8 claims · 8 setups
Bayesembler, a probabilistic transcriptome assembler built on a Bayesian model of the RNA sequencing process with Gibbs sampling over expressed candidates, abundances and read assignments, is introduced.