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).

• PICDGI: A framework for predicting cancer driver genes through dynamic gene-gene interaction modeling of single-cell data.

  PMID 42044093 · PMC13119913 · PLoS computational biology · 2026 · 8 claims · 3 setups

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  PICDGI is a Bayesian framework that predicts driver-like regulatory genes by integrating dynamic gene-gene interaction modeling with scRNA-seq data, without using DNA mutation calls

  lung pediatric same scrna-seq moran's

• S3RL: Enhancing Spatial Single-Cell Transcriptomics With Separable Representation Learning.

  PMID 41556263 · PMC13042551 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026 · 8 claims · 8 setups

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  S3RL is a separable representation learning framework that denoises sparse spatial transcriptomic data and enhances biologically relevant signals by integrating gene expression, spatial coordinates, and histological image features.

  dorsolateral dlpfc nanostring spatial cell-type multi-platform

• Large-scale integration of single-cell transcriptomic data captures transitional progenitor states in mouse skeletal muscle regeneration.

  PMID 34773081 · PMC8589952 · Communications biology · 2021 · 8 claims · 7 setups

  Has reproduction · 92

  Large-scale integration of 111 sc/snRNAseq datasets captures rare, transitional myogenic progenitor states (commitment and fusion) that are poorly represented in individual datasets.

  skeletal merged myogenic muscle scrnaseq batch-correction differential

• Benchmarking LLM-based agents for single-cell omics analysis.

  PMID 41742311 · PMC13064268 · Genome biology · 2026 · 8 claims · 8 setups

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  Introduces a comprehensive benchmarking evaluation system comprising an open-source agent platform, 18 evaluation metrics across four dimensions, and 50 real-world single-cell omics tasks

  agent single-cell spatial scatac-seq llm-agent scrna-seq spatial