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).

• 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

• QuantiSNP: an Objective Bayes Hidden-Markov Model to detect and accurately map copy number variation using SNP genotyping data.

  PMID 17341461 · PMC1874617 · Nucleic acids research · 2007 · 8 claims · 7 setups

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  QuantiSNP (OB-HMM) provides probabilistic quantification of copy number states and significantly improves accuracy of segmental aneuploidy identification and breakpoint mapping relative to existing tools (BeadStudio/Illumina)

  genomic same pseudo-normal artificially snp fish molecular

• iAODE for benchmarking and continuum modeling of single-cell chromatin accessibility.

  PMID 41775921 · PMC13066597 · Communications biology · 2026 · 8 claims · 5 setups

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  iAODE combines a ZINB-likelihood VAE, a latent Neural ODE, low-weight KL regularization, and an interpretable reconstruction (irecon) bottleneck to learn generative, temporally continuous latent spaces for scATAC-seq.

  simulated real small simulated scatac-seq

• SpaPheno: linking spatial transcriptomics to clinical phenotypes with interpretable machine learning.

  PMID 41975540 · PMC13185361 · Genome medicine · 2026 · 8 claims · 8 setups

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  SpaPheno integrates spatial transcriptomics with clinically annotated bulk RNA-seq to identify spatially resolved biomarkers predictive of patient outcomes including survival, tumor stage, and immunotherapy response

  cortex liver clear breast spatial elastic

• Evaluating the Utilities of Foundation Models in Single-Cell Data Analysis.

  PMID 41869863 · PMC13170260 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026 · 8 claims · 8 setups

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  Among ten/eleven evaluated single-cell FMs, scGPT, Geneformer, and CellFM are the top models considering both performance and user accessibility

  scrna-seq unpaired single-cell scgpt batch multi-omic cell-type