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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Geometry-aware graph attention networks to explain single-cell chromatin states and gene expression with SEAGALL.
PMID 42026624 · PMC13238118 · Genome biology · 2026 · 8 claims · 6 setups
SEAGALL combines a geometry-regularised autoencoder (GRAE) to embed cells and build a cell-cell graph with a graph attention network (GAT) classifier and GNNExplainer-based XAI to identify features driving cell type/phenotype.
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Bayesian inference of tissue-migration histories in metastatic cancer from cell-lineage tracing data.
PMID 41916276 · PMC13261679 · Cell genomics · 2026 · 8 claims · 5 setups
BEAM jointly infers a full posterior distribution over cell-lineage phylogenies and tissue-migration graphs using a Bayesian model built on BEAST 2
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Spider: a flexible and unified framework for simulating spatial transcriptomics data.
PMID 41237053 · PMC12790819 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 6 setups
Spider simulates ST data without requiring real ST data as a reference
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Has reproduction · 75
Graph-Based Approaches Significantly Improve the Recovery of Antibiotic Resistance Genes From Complex Metagenomic Datasets.
PMID 34690959 · PMC8528159 · Frontiers in microbiology · 2021 · 8 claims · 6 setups
GraphAMR, a Nextflow pipeline that aligns AMR profile HMMs (or AA sequences) to metagenomic assembly graphs via PathRacer, then dereplicates and annotates hits, recovers more and more complete AMR genes than contig-based or read-based methods.
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The use of edge-betweenness clustering to investigate biological function in protein interaction networks.
PMID 15740614 · PMC555937 · BMC bioinformatics · 2005 · 8 claims · 7 setups
Edge-Betweenness clustering separates protein interaction graphs into subgraphs whose GO term distributions show significant correlations, revealing biologically meaningful functional modules.
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A chromosome-level reference genome and pangenome for barn swallow population genomics.
PMID 36662619 · PMC10044405 · Cell reports · 2023 · 8 claims · 8 setups
A chromosome-level, karyotype-validated reference genome (bHirRus1) was assembled using the VGP pipeline combining PacBio CLR, 10x Linked-Reads, Bionano optical maps, and Hi-C data
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Has reproduction · 86
LMAS: evaluating metagenomic short de novo assembly methods through defined communities.
PMID 36576131 · PMC9795473 · GigaScience · 2022 · 8 claims · 5 setups
LMAS (Last Metagenomic Assembler Standing) is a flexible, Nextflow-based, Docker-containerized automated workflow for benchmarking de novo metagenomic assemblers against defined mock communities, producing an interactive HTML report.
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Integrated multi-omic atlas reveals the hierarchy of spatiotemporal regulatory networks of mouse gastrulation.
PMID 41526381 · PMC12902073 · Nature communications · 2026 · 8 claims · 8 setups
BioCRE, a novel bi-orientation regression algorithm, more accurately links genes to candidate cis-regulatory elements (CREs) than existing tools Signac and ArchR
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MultiPert: An adversarial alignment and dual attention framework for single-cell multi-omics perturbation prediction.
PMID 41811907 · PMC12998955 · PLoS computational biology · 2026 · 8 claims · 7 setups
MultiPert reliably predicts both perturbed gene expression and protein abundance profiles from single-cell multi-omics data
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Harvesting more reads from single-cell combinatorial barcoding data with scarecrow.
PMID 41967853 · PMC13125751 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 3 setups
scarecrow screens a subsample of reads to generate position-specific barcode profiles, then flexibly identifies barcode sequences in reads while accounting for positional jitter
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Accessing medically relevant complex regions with a pangenome graph of 20 near-complete Japanese haplotypes.
PMID 42203797 · PMC13216315 · Nature communications · 2026 · 8 claims · 8 setups
Generated 20 near-complete haplotypes from 10 Japanese male individuals using PacBio HiFi, ONT ultra-long, and Omni-C reads, all with contig N50 exceeding 100 Mbp
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Variant-resolved prediction of context-specific isoform variation with a graph-based attention model.
PMID 41547351 · PMC13069856 · Cell genomics · 2026 · 8 claims · 8 setups
Otari, an attention-based graph neural network trained on long-read transcriptomes across 30 tissues/brain regions, predicts tissue-specific differential isoform abundance
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The sequence and de novo assembly of the giant panda genome.
PMID 20010809 · PMC3951497 · Nature · 2010 · 8 claims · 8 setups
A draft giant panda genome was successfully generated and assembled de novo using only Illumina Genome Analyser short-read sequencing
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ASCL1 promotes nuclear shrinkage in transdifferentiation by suppressing NUP37.
PMID 41759523 · PMC12985393 · Stem cell reports · 2026 · 7 claims · 8 setups
ASCL1-mediated transdifferentiation (AMp) of human fibroblasts to induced neurons causes marked nuclear shrinkage while cell size remains unchanged
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Has reproduction · 67
Generative and integrative modeling for transcriptomics with formalin fixed paraffin embedded material.
PMID 41029822 · PMC12486589 · Journal of translational medicine · 2025 · 8 claims · 6 setups
The negative binomial distribution best fits fRNA-seq transcript counts, with little evidence supporting zero-inflated extensions
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A novel deep learning-driven framework for improving lncRNA comprehensive annotation with LncADeep 2.0.
PMID 41923359 · PMC13090826 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 8 setups
LncADeep 2.0 outperforms LncADeep and other existing tools for lncRNA identification on both GENCODE annotated transcripts and independent RNA-seq data
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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.