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).

• maxATAC: Genome-scale transcription-factor binding prediction from ATAC-seq with deep neural networks.

  PMID 36719906 · PMC9917285 · PLoS computational biology · 2023 · 8 claims · 6 setups

  Has reproduction · 98

  maxATAC is a suite of deep neural network models enabling state-of-the-art, genome-scale TFBS prediction from ATAC-seq, with models for 127 human transcription factors

  lines hepg2 types single chip-seq omni-atac-seq atac-seq

• Multimodal-based analysis of single-cell ATAC-seq data enables highly accurate delineation of clinically relevant tumor cell subpopulations.

  PMID 41530870 · PMC12888741 · Genome medicine · 2026 · 8 claims · 8 setups

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  MAAS integrates chromatin accessibility, CNVs, and SNVs from scATAC-seq data to identify functional tumor cell subpopulations

  tumor pediatric b-cell glioblastoma scatac-seq bulk gene

• 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

• CellPredX, a computational framework for cross-data type, cross-sample, and cross-protocol cell type annotation through domain adaptation and deep metric learning.

  PMID 41481570 · PMC12758788 · PLoS computational biology · 2026 · 8 claims · 7 setups

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  CellPredX is a unified semi-supervised framework integrating domain adaptation and deep metric learning to align heterogeneous embeddings for cross-modality cell type annotation.

  pbmc fetal pancreas gse149683 matched unmatched cross-protocol

• CIRCE: a scalable Python package to predict cis-regulatory DNA interactions from single-cell chromatin accessibility data.

  PMID 41734268 · PMC12987762 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 5 setups

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  CIRCE re-implements the Cicero co-accessibility algorithm in Python, producing near-identical results while running much faster and using far less memory

  bmmc pbmc foetal cis-regulatory enhancer-promoter scalability

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

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

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  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