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).

• TDAGENE: Inference of Gene Regulatory Network Based on Topological Data Analysis and Graph Attention Network for Single-Cell RNA Sequencing Data.

  PMID 42093817 · PMC13139726 · Computational and structural biotechnology journal · 2026 · 7 claims · 5 setups

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  TDAGENE combines TDA features with a multilayer GAT via gate-controlled fusion to improve GRN inference accuracy

  scrna-seq gene string chip-seq grn persistent prior

• GRNFormer: accurate gene regulatory network inference using graph transformer.

  PMID 41883144 · PMC13069479 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 8 setups

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  GRNFormer is a generalizable graph transformer framework for GRN inference from single-cell or bulk transcriptomics data across species, cell types, and platforms without cell-type annotations or prior regulatory information

  hematopoietic embryonic dendritic hepatocytes scrna-seq chip-seq string

• 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

• Predicting the protein interaction landscape of a free-living bacterium with pooled-AlphaFold3.

  PMID 41559189 · PMC13047044 · Molecular systems biology · 2026 · 8 claims · 6 setups

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  Pooled-AlphaFold3 prediction improves accuracy of genome-scale PPI screens compared to a paired approach while reducing inference time (~2-fold) and job count (~100-fold)

  mycoplasma subset genitalium simulated pooled paired benchmarking

• CaHoT-GRN: context-aware high-order topology learning for robust single-cell gene regulatory network inference.

  PMID 42059479 · PMC13130071 · Briefings in bioinformatics · 2026 · 7 claims · 5 setups

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  CaHoT-GRN integrates pretrained biological language model embeddings (DNABERT for DNA, ESM for protein) with scRNA-seq expression data to improve GRN inference

  embryonic gene dataset-specific same scrna-seq-based sequence protein-protein