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).

• AutoGERN: single-cell RNA-seq gene regulatory network inference via explicit link modeling and adaptive architectures.

  PMID 41871930 · PMC13064981 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 3 setups

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  AutoGERN explicitly models regulatory information in the message-passing space via learned link (edge) embeddings, which are scored by a lightweight MLP to infer TF–target interactions.

  seven same scrna-seq-based chip-seq cold-start

• scTWAS: a powerful statistical framework for single-cell transcriptome-wide association studies.

  PMID 41820391 · PMC13121454 · Nature communications · 2026 · 8 claims · 5 setups

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  scTWAS uses a latent-variable expression-measurement model combined with a moment-based regression to more accurately estimate genetic regulation of gene expression from single-cell data, improving GReX prediction across cell types and datasets

  onek1k-derived onek1k-based immune brain simulated two-sample stage

• 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