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).

• Macrel: antimicrobial peptide screening in genomes and metagenomes.

  PMID 33384902 · PMC7751412 · PeerJ · 2020 · 8 claims · 8 setups

  Has reproduction · 83

  Macrel introduces a novel set of 22 peptide features (6 local, 16 global), including a new Free Energy Transition (FET) feature group, for AMP and hemolytic activity classification

  curated hemopi-1 xiao peptide random benchmark homology-aware

• 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

• scDBic: a novel deep learning-based biclustering algorithm for analyzing scRNA-seq data.

  PMID 41746287 · PMC13012890 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 6 setups

  Full-text index only

  scDBic improves cell clustering by combining deep autoencoder-based cell clustering, gene clustering, and reverse-strategy identification of key gene clusters

  e-mtab-3321 e-mtab-2600 gse45719 gse52529 biclustering ablation

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

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

  Full-text index only

  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

• InParanoid 7: new algorithms and tools for eukaryotic orthology analysis.

  PMID 19892828 · PMC2808972 · Nucleic acids research · 2010 · 8 claims · 7 setups

  Full-text index only

  InParanoid 7 expands the database by an order of magnitude to 100 species, 1.3 million proteins, and 42.7 million pairwise ortholog groups.

  eukaryotic homo sequence species pairwise algorithm low-complexity

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

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

  Full-text index only

  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

• scSurv: a deep generative model for single-cell survival analysis.

  PMID 41429574 · PMC12797213 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 6 setups

  Full-text index only

  scSurv combines a Cox proportional hazards model with a deep generative model (VAE) of single-cell transcriptomes to estimate individual cellular contributions to clinical outcomes

  simulated tcga melanoma renal scrna-seq bulk single-cell

• 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

  Full-text index only

  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

• CellMap: precision mapping of cellular landscape in spatial transcriptomics.

  PMID 41505103 · PMC12781899 · Nucleic acids research · 2026 · 7 claims · 3 setups

  Full-text index only

  CellMap combines co-linearity of seed genes, a random forest model, and the linear assignment algorithm to achieve optimal assignment of single cells to spatial spots

  platforms single-cell expression computational scrna-seq spatial

• 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

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

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

  Full-text index only

  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

• DANST enables cell-type deconvolution in spatial transcriptomics using deep domain adversarial neural networks.

  PMID 41663685 · PMC12996496 · Communications biology · 2026 · 7 claims · 6 setups

  Full-text index only

  DANST, a deconvolution framework using deep domain adversarial neural networks, achieves superior cell-type deconvolution accuracy compared with existing methods on human and mouse benchmark datasets

  heart cortex visual brain spatial cell-type

• SGCRNA: spectral clustering-guided co-expression network analysis without scale-free constraints for multi-omic data.

  PMID 41615289 · PMC12856952 · Briefings in bioinformatics · 2026 · 8 claims · 8 setups

  Full-text index only

  WGCNA's reliance on a scale-free topology assumption is problematic because real co-expression networks do not consistently exhibit scale-free properties

  gse114007 gse261545 dryad.37pvmcvsg prjna762466 bulk spatial merfish

• Spatial information matters: are traditional imputation methods effective for spatial transcriptomics data?

  PMID 41627342 · PMC12862982 · Briefings in bioinformatics · 2026 · 7 claims · 3 setups

  Has reproduction · 89

  No single existing SOTA imputation method consistently performs well across newer SRT platforms/datasets

  datasets srt same computational proposed

• pmid-41857511

  PMID 41857511 · PMC13122936 · 8 claims · 1 setups

  Full-text index only

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

  simulated scrna-seq

• metaFun: An analysis pipeline for metagenomic big data with fast and unified functional searches.

  PMID 41530917 · PMC12818822 · Gut microbes · 2026 · 8 claims · 8 setups

  Full-text index only

  metaFun is an open-source, end-to-end Nextflow/Apptainer pipeline integrating quality control, taxonomic profiling, functional profiling, de novo assembly, binning, genome assessment, comparative genomics, network analysis, and strain-level microdiversity analysis into a unified framework

  simulated selected gut mags novo binning pangenome-based

• Spider: a flexible and unified framework for simulating spatial transcriptomics data.

  PMID 41237053 · PMC12790819 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 6 setups

  Full-text index only

  Spider simulates ST data without requiring real ST data as a reference

  simulated hypothalamus dorsolateral spatial clustering cell-cell

• A reference profile-free deconvolution method to infer cancer cell-intrinsic subtypes and tumor-type-specific stromal profiles.

  PMID 32111252 · PMC7049190 · Genome medicine · 2020 · 8 claims · 8 setups

  Has reproduction · 91

  DeClust is a reference-profile-free deconvolution method that incorporates molecular subtyping directly into the deconvolution process, outputting cohort-level cancer subtype and stromal reference profiles rather than per-individual profiles

  tcga simulated muscle-invasive ccrcc computational simulation-based deconvolution

• Prioritized mass spectrometry increases the depth, sensitivity and data completeness of single-cell proteomics.

  PMID 37012480 · PMC10172113 · Nature methods · 2023 · 8 claims · 5 setups

  Has reproduction · 90

  pSCoPE (prioritized precursor selection via MaxQuant.Live) increases sensitivity, data completeness, and proteome coverage more than twofold over shotgun single-cell proteomics

  bulk hek293 single-cell bone prioritized single-cell spike-in

• EpiXFormer: a cross-attention neural network for predicting cell type-specific transcription factor binding sites.

  PMID 41527854 · PMC12796812 · Briefings in bioinformatics · 2026 · 8 claims · 8 setups

  Full-text index only

  EpiXFormer achieves high accuracy (mean AUROC ~0.99) predicting binding sites of both TFs and non-sequence-specific DBPs across 199 DBP-cell type pairs

  dbps tfs common ctcf deep comparative feature-ablation