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).

• DeCAF defines clinical fibroblast subtypes and multidimensional tumor-stroma crosstalk shaping prognosis and immunotherapy response.

  PMID 41707654 · PMC12923980 · Cell reports. Medicine · 2026 · 8 claims · 8 setups

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  DeCAF is a single-sample kTSP classifier using 9 TSP gene pairs that predicts proCAF vs restCAF subtypes from bulk expression data

  pdac cptac external elyada-sc bulk single-sample classifier

• Prediction of myeloid malignant cells in Fanconi anemia using machine learning.

  PMID 41557613 · PMC12818649 · PloS one · 2026 · 6 claims · 7 setups

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  A DNN classifier trained on AML scRNA-seq data accurately predicts AML-like transcriptional profiles at single-cell resolution

  bone predicted-aml healthy scrna-seq reference-based stemnet

• Systems spatiotemporal dynamics of traumatic brain injury at single-cell resolution reveals humanin as a therapeutic target.

  PMID 35951114 · PMC9372016 · Cellular and molecular life sciences : CMLS · 2022 · 8 claims · 8 setups

  Has reproduction · 98

  Coordinated gene expression patterns across cell types are disrupted and re-organized by mTBI with distinct regional, cellular, and temporal (24-h vs 7-day) specificity.

  hippocampus frontal peripheral cell-type single-cell svm-based ligand-receptor

• 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

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  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.

  count same scchip-seq ten count latent classification

• The evolution of gene regulation in mammalian cerebellum development.

  PMID 41610256 · PMC7618896 · Science (New York, N.Y.) · 2026 · 8 claims · 8 setups

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  Combined single-nucleus RNA-seq and ATAC-seq atlases of cerebellum development were generated/integrated across six mammals (human, bonobo, macaque, marmoset, mouse, opossum)

  developing opossum marmoset cultures single-nucleus bulk gene

• Towards the identification of essential genes using targeted genome sequencing and comparative analysis.

  PMID 17052348 · PMC1624830 · BMC genomics · 2006 · 8 claims · 8 setups

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  Phyletic retention (ortholog presence across organisms) is the single most predictive feature of gene essentiality in both E. coli and S. cerevisiae.

  coli cerevisiae comparative machine single-gene

• 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

• FLYNC: a machine-learning-driven framework for discovering long noncoding RNAs in Drosophila melanogaster.

  PMID 41551930 · PMC12805895 · NAR genomics and bioinformatics · 2026 · 7 claims · 8 setups

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  FLYNC, an explainable boosting machine (EBM) model, accurately predicts the probability that a newly identified RNA transcript in D. melanogaster is a lncRNA

  melanogaster drosophila automated ebm hyperparameter

• Predicting positive p53 cancer rescue regions using Most Informative Positive (MIP) active learning.

  PMID 19756158 · PMC2742196 · PLoS computational biology · 2009 · 8 claims · 4 setups

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  MIP active learning is a novel active learning method that preferentially seeks informative Positive (functionally active) examples rather than only maximizing classifier accuracy.

  engineered p53 computational yeast-based regional homology

• A multi-modal diffusion model with dual-cross-attention for multi-omics data generation and translation.

  PMID 41980989 · PMC13253844 · Nature communications · 2026 · 8 claims · 7 setups

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  scDiffusion-X is a multi-modal latent denoising diffusion probabilistic model for single-cell multi-omics data generation, translation, and interpretation.

  openproblem 10x babel miniatlas paired modality augmentation

• Wochenende - modular and flexible alignment-based shotgun metagenome analysis.

  PMID 36368923 · PMC9650795 · BMC genomics · 2022 · 8 claims · 6 setups

  Has reproduction · 88

  Wochenende is a modular, transparent alignment-based pipeline for shotgun metagenome analysis supporting short and long reads across all kingdoms of life

  zymo bacterial reference shotgun comparative reference

• A cellular epigenetic classification system for glioblastoma.

  PMID 41499453 · PMC13128495 · Neuro-oncology · 2026 · 8 claims · 8 setups

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  ITHresolveGBM, a hierarchical two-step NMF method, deconvolutes bulk GBM DNA methylation profiles into three non-malignant (immune, glial, neuronal) and three malignant components

  gbm healthy pseudo-bulk tcga illumina single-cell deconvolution

• WBT-DC pipeline: a cross-cohort and cross-platform disease classification pipeline based on whole-blood transcriptomics.

  PMID 42116144 · PMC13173921 · Journal of translational medicine · 2026 · 8 claims · 8 setups

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  WBT-DC integrates rank-based GSVA feature extraction with an ensemble random forest framework using cross-validation and hyperparameter optimization to mitigate batch effects.

  blood circulating whole-blood bulk microarray single-cell

• High-resolution aCGH and expression profiling identifies a novel genomic subtype of ER negative breast cancer.

  PMID 17925008 · PMC2246289 · Genome biology · 2007 · 7 claims · 8 setups

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  A novel subtype of high-grade ER-negative breast cancer exists, characterized by a low genomic instability index (GII)

  breast computational array-cgh gene bac

• Detection of alternative splicing: deep sequencing or deep learning?

  PMID 41520225 · PMC12790623 · Briefings in bioinformatics · 2026 · 8 claims · 8 setups

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  Sequence-based deep learning tools (AlphaGenome, SpliceAI, DeepSplice) show potential for initial hypothesis development and as additional filters in standard RNA-seq pipelines, especially when sequencing depth is limited.

  dilated dcm sequence subsampled bulk rna-seq deep