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).

• PeakPrime: a peak-guided primer design pipeline for target enrichment in 3'-end RNA-seq.

  PMID 41919010 · PMC13034549 · Bioinformatics advances · 2026 · 8 claims · 7 setups

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  PeakPrime is a reproducible Nextflow pipeline that calls 3′ RNA-seq coverage peaks (MACS2), selects exonic windows, designs strand-appropriate primers (Primer3), and screens specificity (Bowtie2)

  imr-32 universal candidate 10m-read rna-seq targeted quantitative

• FineST: contrastive learning integrates histology and spatial transcriptomics for nuclei-resolved ligand-receptor analysis.

  PMID 41839892 · PMC13201544 · Nature communications · 2026 · 8 claims · 6 setups

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  FineST, a bimodal contrastive learning model integrating histology (Virchow2 ViT features) and spatial gene expression, enables nuclei-resolved high-resolution RNA imputation.

  colorectal crc breast he-stained spatial type ccc

• DAESC + : high-performance, integrated software for single-cell allele-specific expression data.

  PMID 41851619 · PMC13169709 · BMC bioinformatics · 2026 · 8 claims · 6 setups

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  DAESC+ is a dual-module, end-to-end software package (DAESC-P for preprocessing, DAESC-GPU for differential analysis) for single-cell ASE data

  onek1k endoderm simulated single-cell differential runtime

• OTMODE: an optimal transport theory-based framework for identifying differential features in single-cell multi-omics data.

  PMID 41335419 · PMC12766913 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 8 setups

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  OTMODE, using an unbalanced Sinkhorn algorithm and Wald test, improves differential feature identification in single-cell multi-omics data

  simulated classical degs naive simulated bulk real