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 · 59
WASP: a versatile, web-accessible single cell RNA-Seq processing platform.
PMID 33736596 · PMC7977290 · BMC genomics · 2021 · 7 claims · 7 setups
WASP is a software platform for processing Drop-Seq-based scRNA-seq data generated with ddSEQ or 10x protocols, combining a Snakemake pre-processing pipeline with an R Shiny post-processing application.
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Identification and analysis of co-occurrence networks with NetCutter.
PMID 18781200 · PMC2526157 · PloS one · 2008 · 8 claims · 4 setups
Random sampling from a complete permutation set of the bipartite graph permits co-occurrence analysis with optimal stringency, and the edge-swapping (ES) model closely approximates this and is the preferred null-model among six tested.
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Has reproduction · 67
GEMmaker: process massive RNA-seq datasets on heterogeneous computational infrastructure.
PMID 35501696 · PMC9063052 · BMC bioinformatics · 2022 · 6 claims · 3 setups
GEMmaker, an nf-core compliant Nextflow workflow, can quantify gene expression from small to massive RNA-seq datasets while remaining reproducible via versioned containerized software.
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Evolutionarily conserved and diverged alternative splicing events show different expression and functional profiles.
PMID 16195578 · PMC1240112 · Nucleic acids research · 2005 · 8 claims · 5 setups
Alternative splices in 10,818 human-mouse gene pairs can be classified as conserved, novel, or diverged based on genomic and transcript-level cross-species comparison.
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Applications for protein sequence-function evolution data: mRNA/protein expression analysis and coding SNP scoring tools.
PMID 16912992 · PMC1538848 · Nucleic acids research · 2006 · 7 claims · 8 setups
PANTHER HMMs built from family/subfamily multiple sequence alignments can classify novel protein sequences into functional groups based on statistically significant HMM match scores
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Reconstructing transcriptional regulatory networks through genomics data.
PMID 20048387 · PMC3666560 · Statistical methods in medical research · 2009 · 7 claims · 5 setups
Location data (ChIP-chip/ChIP-seq) alone is insufficient for TRN inference because binding does not imply regulation, TF binding is dynamic across conditions/time, and TRNs involve combinatorial effects of multiple TFs not captured by single-TF ChIP experiments.