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).

• CanSig Benchmarks Methods for Reproducible Cancer Cell State Discovery from Single-Cell Transcriptomic Data.

  PMID 41231245 · PMC13053056 · Cancer research · 2026 · 7 claims · 7 setups

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  CanSig is a comprehensive benchmarking tool for evaluating computational methods that identify shared transcriptional signatures in cancer from scRNA-seq data

  neftel kim scrna-seq same scrna-seq ground-truth robustness

• Integrating and mapping single-cell transcriptomics across the entire gene expression space.

  PMID 42059480 · PMC13130072 · Briefings in bioinformatics · 2026 · 8 claims · 1 setups

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  scGES is a deep learning framework that corrects batch effects across the entire gene expression space by leveraging information from both HVGs and LVGs

  real scrna-seq

• 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

• GAMMI: graph-guided contrastive and adversarial integration of single-cell and spatial multi-omics data.

  PMID 42108634 · PMC13158126 · Briefings in bioinformatics · 2026 · 6 claims · 5 setups

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  GAMMI consistently outperforms state-of-the-art integration methods (GLUE, Harmony, MIDAS, scMoMaT) in biological conservation and batch correction across five mosaic single-cell multi-omics benchmarks

  pbmc postmortem gse138852 gammi-derived multi-omics scrna-seq differential

• Multi-species integration, alignment and annotation of single-cell RNA-seq data with CAMEX.

  PMID 41723123 · PMC13035843 · Nature communications · 2026 · 8 claims · 6 setups

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  CAMEX outperforms state-of-the-art integration methods on cross-species scRNA-seq benchmarking datasets ranging from one to eleven species

  liver ovary pancreas testis scrna-seq type

• Integrative Learning of Disentangled Representations from Single-Cell RNA-Sequencing Datasets.

  PMID 41971949 · PMC13068006 · Computational and structural biotechnology journal · 2026 · 8 claims · 6 setups

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  spVIPES decomposes unpaired scRNA-seq datasets with nonmatching features into shared and private latent representations using a Product of Experts framework

  simulated zebrafish kidney peripheral simulated cross-species scrna-seq

• Embeddings from language models are good learners for single-cell data analysis.

  PMID 41726097 · PMC12921509 · Patterns (New York, N.Y.) · 2026 · 8 claims · 8 setups

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  scELMo combines LLM-derived embeddings of gene and cell metadata with raw single-cell expression data via matrix operations to generate cell embeddings without pretraining a new model

  scrna-seq multi-batch diseased perturbation clustering batch cell-type

• Celline: a flexible tool for one-step retrieval and integrative analysis of public single-cell RNA sequencing data.

  PMID 41458999 · PMC12738925 · Frontiers in bioinformatics · 2025 · 8 claims · 6 setups

  Has reproduction · 64

  Celline is a Python package that automates the full scRNA-seq workflow (retrieval, metadata extraction, preprocessing, cell-type annotation, batch correction, trajectory inference) via single-line commands.

  c57bl embryonic scrna-seq quality cell-type

• Pre-existing cell states predict resistance to multiple treatments.

  PMID 41916275 · PMC13261651 · Cell genomics · 2026 · 8 claims · 5 setups

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  Rare melanoma clones can develop resistance to multiple diverse treatments simultaneously, not just single treatments

  wm989 time-lapse barcode single-cell

• 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

• An AI-Enabled Single-Cell Transcriptomic Analysis Pipeline for Gene Signature Discovery in Natural Killer Cells Linked to Remission Outcomes in Chronic Myeloid Leukemia.

  PMID 41972591 · PMC13072394 · Biology · 2026 · 8 claims · 7 setups

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  GAFA integrates latent-space representation, pseudotime trajectory modeling, GRN inference, and machine learning-based gene panel discovery into a single coherent pipeline, unlike existing workflows that treat these steps independently.

  peripheral subset immune assigned scrna-seq latent-space automated