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).

• SenSet defines cell-type specific senescence signatures in the aged human lung.

  PMID 41963555 · PMC13187336 · The EMBO journal · 2026 · 8 claims · 4 setups

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  SenSet comprises 106 genes identified by covariate-shift-aware positive-unlabeled (PUc) learning applied across single cells from the Human Lung Cell Atlas (HLCA)

  lung replicative hlca single-cell gene targeted

• Benchmarking component choices for unpaired single cell RNA and epigenomic integration.

  PMID 41987329 · PMC13192178 · Genome biology · 2026 · 7 claims · 8 setups

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  Gene activity scores (GAS) show limited correlation with actual gene expression but effectively preserve cellular neighborhood structure and support clustering.

  e18 pbmc brain kidney scrna-seq share-seq gas

• UBD: incorporating uncertainty in cell type proportion estimates from bulk samples to infer cell-type-specific profiles.

  PMID 41520227 · PMC12895075 · Briefings in bioinformatics · 2026 · 7 claims · 4 setups

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  Existing CTS deconvolution methods (e.g., CIBERSORTx, TCA, bMIND, CellDMC, HBI) require cell type proportions that are in practice only estimated, not known, introducing unaccounted uncertainty into CTS inference.

  simulated rosmap onek1k bulk simulation-based cell-type-specific type

• RaMBat: Accurate identification of medulloblastoma subtypes from diverse data sources with severe batch effects.

  PMID 41571436 · PMC13060657 · Molecular oncology · 2026 · 7 claims · 5 setups

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  RaMBat achieves a median accuracy of 99% across 13 independent benchmark datasets, significantly outperforming state-of-the-art MB subtyping methods and conventional ML classifiers

  medulloblastoma gse85217 ger microarray bulk intrasample

• IFDlong: a model-based isoform and fusion detector for accurate annotation and quantification of long-read RNA-seq data.

  PMID 41851882 · PMC13113378 · Genome biology · 2026 · 8 claims · 2 setups

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  IFDlong is the only tool that can discover fusion transcripts at isoform resolution

  in-silico type long-read computational

• scGACL: a generative adversarial network with multi-scale contrastive learning for accurate single-cell RNA sequencing imputation.

  PMID 41632596 · PMC12866930 · Briefings in bioinformatics · 2026 · 8 claims · 6 setups

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  scGACL, a GAN integrated with multi-scale contrastive learning, is proposed to overcome the over-smoothing problem in scRNA-seq imputation

  simulated real-world scrna-seq scrna-seq clustering gene

• SMAC, a computational system to link literature, biomedical and expression data.

  PMID 31324861 · PMC6642118 · Scientific reports · 2019 · 8 claims · 8 setups

  Has reproduction · 50

  SMAC is a tool that extracts, prioritises, integrates and analyses biomedical and molecular data according to user-defined terms

  pubmed invasive geo genes semantic computational gene

• SGCP: a spectral self-learning method for clustering genes in co-expression networks.

  PMID 38956463 · PMC11221046 · BMC bioinformatics · 2024 · 7 claims · 4 setups

  Has reproduction · 51

  SGCP, a spectral self-learning method, yields gene co-expression modules with higher GO enrichment than WGCNA, CoExpNets, and CEMiTool across 12 real gene expression datasets.

  real microarray rna-seq same gene dna-microarray rna-sequencing

• PSGRN: Gene regulatory network inference from single-cell perturbational data through self-training with synthetic gold standards.

  PMID 42054465 · PMC13127566 · Science advances · 2026 · 8 claims · 4 setups

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  PSGRN infers GRNs by generating pseudoannotations from gene-gene correlations and iteratively refining them via a self-training classifier using pre/post-intervention expression features.

  k562 rpe1 processed single-cell computational biological

• GDSim: accurate simulation for single-cell transcriptomes based on the guided diffusion model.

  PMID 41978379 · PMC13076945 · Briefings in bioinformatics · 2026 · 8 claims · 4 setups

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  GDSim, a label-guided diffusion-based deep generative network, can simulate scRNA-seq data that closely reflects the true distribution of original data

  real simulated annotated scrna-seq subtype differential

• scZiva: imputation method for single-cell RNA-seq data with zero-inflated variational autoencoder.

  PMID 41857511 · PMC13122936 · BMC bioinformatics · 2026 · 8 claims · 1 setups

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  scZiva is a novel VAE-based imputation method for scRNA-seq data using a Zero-Inflated Negative Binomial (ZINB) likelihood.

  simulated scrna-seq

• Digital sorting of complex tissues for cell type-specific gene expression profiles.

  PMID 23497278 · PMC3626856 · BMC bioinformatics · 2013 · 8 claims · 8 setups

  Has reproduction · 85

  The Digital Sorting Algorithm (DSA) deconvolves mixed tissue expression into cell type-specific profiles using only marker genes, without requiring prior knowledge of cell type frequencies or in vitro pure-cell profiles.

  liver im-9 immune deconvolved microarray simulation roc

• Using random walks to identify cancer-associated modules in expression data.

  PMID 24128261 · PMC4015830 · BioData mining · 2013 · 8 claims · 8 setups

  Has reproduction

  Walktrap-GM, a random-walk community detection algorithm adapted with stopping criteria (maximum modularity, maximum size, maximum module score), identifies modules significantly enriched with cancer genes in expression-weighted interaction networks.

  hepatocellular breast sporadic geo gene differential interaction

• Functional annotation and identification of candidate disease genes by computational analysis of normal tissue gene expression data.

  PMID 18560577 · PMC2409962 · PloS one · 2008 · 7 claims · 5 setups

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  Ranked Coexpression Groups (RCG) built from k=6 nearest coexpressed genes, combined with a majority-rule functional characterization, integrate multiple datasets/coexpression measures to generate high-confidence functional annotation predictions

  normal genome-wide same omim microarray sage computational

• 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

• Genomics--from Neanderthals to high-throughput sequencing.

  PMID 16934106 · PMC1779599 · Genome biology · 2006 · 8 claims · 8 setups

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  Next-generation sequencing platforms (GS20/454 and Solexa) can deliver the throughput and cost reductions needed for population-scale and medical resequencing.

  bacterial ion-channel drosophila arrays next-generation pooled multiplex

• RummaGEO: Automatic mining of human and mouse gene sets from GEO.

  PMID 39569206 · PMC11573963 · Patterns (New York, N.Y.) · 2024 · 8 claims · 7 setups

  Has reproduction · 63

  RummaGEO is a gene expression signature search engine built from automatically mined human and mouse RNA-seq perturbation studies in GEO

  genes rummageo rummageo-derived leiden bulk gene leiden

• Developing prognostic gene panel of survival time in lung adenocarcinoma patients using machine learning.

  PMID 35117753 · PMC8799101 · Translational cancer research · 2020 · 8 claims · 5 setups

  Has reproduction · 32

  Naïve Bayes using a 22-gene panel is the best-performing and most stable machine learning model for predicting LUAD survival time (>3 vs <3 years)

  tcga geo rna-seq methylation sequencing

• GoMiner: a resource for biological interpretation of genomic and proteomic data.

  PMID 12702209 · PMC154579 · Genome biology · 2003 · 8 claims · 4 setups

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  GoMiner organizes 'interesting' gene lists (e.g., differentially expressed genes) into the Gene Ontology hierarchy for biological interpretation, displaying results as both a tree and a directed acyclic graph (DAG).

  du145 gene gominer cdna flow category

• Deep-Learning Tool ScVital Enables Species-Agnostic Integration of Cancer Cell States.

  PMID 41223329 · PMC13053053 · Cancer research · 2026 · 7 claims · 7 setups

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  scVital is a variational autoencoder with an adversarially trained discriminator that embeds scRNA-seq data from different species into a species-agnostic latent space to overcome batch effect.

  pbmc normal pancreatic lung scrna-seq