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).

• scGeno: a Hidden Markov Model approach to denoise chromosome-scale genotypes from single-cell data.

  PMID 41982479 · PMC13075984 · Bioinformatics advances · 2026 · 7 claims · 4 setups

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  scGeno, a categorical HMM, infers chromosome-level genotype states in mixed-genotype organisms by modeling sequential single-cell allelic expression ratios along chromosomes

  wild-type dnmt1 synthetic embryo single-cell posterior down-sampling

• 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

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  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

• FLYNC: a machine-learning-driven framework for discovering long noncoding RNAs in Drosophila melanogaster.

  PMID 41551930 · PMC12805895 · NAR genomics and bioinformatics · 2026 · 7 claims · 8 setups

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  FLYNC, an explainable boosting machine (EBM) model, accurately predicts the probability that a newly identified RNA transcript in D. melanogaster is a lncRNA

  melanogaster drosophila automated ebm hyperparameter

• Construction of a SEMA3 family-based model to predict prognosis and molecular subtypes in pancreatic ductal adenocarcinoma.

  PMID 41792569 · PMC13079247 · Discover oncology · 2026 · 8 claims · 8 setups

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  SEMA3 family expression defines two molecular subtypes (A and B) of PDAC with significantly different overall survival

  pdac bulk ssgsea differential

• Inference of transcriptional regulation using gene expression data from the bovine and human genomes.

  PMID 17683551 · PMC1978505 · BMC genomics · 2007 · 7 claims · 8 setups

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  Using human reference promoter sequences is a useful approach for studying gene expression regulation in species with limited or non-existing genomic sequence, such as cattle.

  muscle-specific bovine refseq cardiac novo est blastn

• Discovery and identification of potential biomarkers of papillary thyroid carcinoma.

  PMID 19785722 · PMC2761863 · Molecular cancer · 2009 · 8 claims · 7 setups

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  A 3-peak (m/z 9190, 6631, 8697 Da) SVM classification model discriminates PTC from non-cancer controls with high sensitivity and specificity

  serum hplc-purified trypsin-digested crude seldi-tof-ms solid-phase maldi-tof-ms

• ChromBERT: A foundation model for learning interpretable representations for context-specific transcriptional regulatory networks.

  PMID 41592570 · PMC13069865 · Cell genomics · 2026 · 8 claims · 7 setups

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  ChromBERT is pre-trained via masked reconstruction on the Cistrome-Human-6K dataset (6,391 cistromes, 991 transcription regulators) to learn genome-wide interaction syntax of transcription regulators

  lines chromosome embryonic transcription chip-seq chromhmm hi-c

• Combining evidence of preferential gene-tissue relationships from multiple sources.

  PMID 23950964 · PMC3741196 · PloS one · 2013 · 8 claims · 8 setups

  Has reproduction · 53

  A high-level integration approach combining three methods across four human microarray datasets, merged by consensus voting and a rule-based inner/total score, predicts preferentially expressed genes while reducing method- and study-specific bias.

  normal four microarray genes microarray computational bayes

• Fibroblast-associated CTHRC1 as a key indicator of recurrence risk in prostate cancer.

  PMID 41832493 · PMC13101373 · World journal of surgical oncology · 2026 · 7 claims · 8 setups

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  Pathological T stage, N stage, Gleason score, and TP53 mutation are associated with higher PRAD recurrence risk

  tcga geo prad scrna-seq bulk single-cell cell-cell

• Hi-Compass: a depth-aware deep learning framework for predicting cell-type-specific 3D genome organization from single-cell to spatial resolution.

  PMID 41980945 · PMC13250166 · Nature communications · 2026 · 8 claims · 8 setups

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  Hi-Compass predicts cell-type-specific Hi-C contact maps using only ATAC-seq as cell-type-specific input, plus DNA sequence and a generalized CTCF binding profile

  gm12878 curated bulk training hi-c ctcf matched

• BCG-trained macrophages promote pan-anti-tumor activity through epigenetic rewiring of NOX2-ROS axis.

  PMID 42032669 · PMC13261971 · Journal of experimental & clinical cancer research : CR · 2026 · 7 claims · 8 setups

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  BCG training induces pan-anti-tumor activity across multiple mouse tumor models, mediated predominantly by tumor-associated macrophages (TAMs)

  llc tumor-infiltrating macrophage raw264.7 tumor flow antibody-mediated

• HArmonized single-cell RNA-seq Cell type Assisted Deconvolution (HASCAD).

  PMID 37907883 · PMC10619225 · BMC medical genomics · 2023 · 6 claims · 4 setups

  Has reproduction · 67

  Removal of batch effects in reference scRNA-seq datasets (via Harmony-Symphony) benefits the task of cell composition deconvolution

  pbmc derived tcga-lihc scrna-seq simulated bulk

• CanCellCap: robust cancer cell capture across tissue types on single-cell RNA-seq data by multi-domain learning.

  PMID 40739511 · PMC12312500 · BMC biology · 2025 · 8 claims · 7 setups

  Has reproduction · 42

  CanCellCap identifies cancer cells in scRNA-seq data across 13 tissue types, 23 cancer types, and 7 sequencing platforms with 0.977 average accuracy

  cancer testing sequencing unseen scrna-seq spatial

• How negative sampling shapes the performance of transcription factor binding site prediction models.

  PMID 41601205 · PMC12910371 · Bioinformatics (Oxford, England) · 2026 · 7 claims · 5 setups

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  Negative sampling technique significantly impacts TFBS prediction model performance and interpretation of results

  encode same genome chip-seq atac-seq deep

• Mitochondrial DNA methylation predicts immunotherapy response and prognosis in lung adenocarcinoma: evidence from scRNA-Seq and machine learning.

  PMID 41663976 · PMC12997902 · BMC cancer · 2026 · 8 claims · 8 setups

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  Differentially expressed MTDM-related genes (DEMTDMRGs) are significantly enriched in cell cycle regulation, ferroptosis, and ABC transporter pathways

  luad demtdmrgs gse131907 wgcna kegg univariate

• Comprehensive analysis for the role of macrophage-driven genes in abdominal aortic aneurysm.

  PMID 41815567 · PMC12973086 · Cardiovascular diagnosis and therapy · 2026 · 8 claims · 8 setups

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  SMU1 is identified as a novel macrophage-related gene associated with AAA development, serving as a potential diagnostic biomarker and therapeutic target

  aaa macrophage-related merged gwas single-cell bulk rt-qpcr

• iCOMIC: a graphical interface-driven bioinformatics pipeline for analyzing cancer omics data.

  PMID 35899080 · PMC9310080 · NAR genomics and bioinformatics · 2022 · 8 claims · 4 setups

  Has reproduction · 58

  iCOMIC provides a GUI-driven, Snakemake-based pipeline integrating multiple tools for DNA-Seq and RNA-Seq analysis with minimal command-line interaction.

  giab monocyte missense somatic germline rna-seq machine

• Tracing human genetic histories and natural selection with precise local ancestry inference.

  PMID 40379651 · PMC12084304 · Nature communications · 2025 · 7 claims · 7 setups

  Has reproduction · 76

  Orchestra, a two-stage LAI method combining a recombination-distance base layer with a deep learning (convolutional + attention) smoothing module, outperforms RFmix, FLARE and Gnomix in precision and recall across simulated admixture generations.

  1kgp-16pops independent simulated 1kgp simulated population-level local

• In silico segmentations of lentivirus envelope sequences.

  PMID 17376229 · PMC1847453 · BMC bioinformatics · 2007 · 8 claims · 8 setups

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  C and V regions of lentivirus SU sequences have distinct statistical (oligonucleotide/amino-acid) compositions that HMMs can learn and use to delimit them.

  eiav hiv hmm-based hmm artificial

• EPInformer: scalable and integrative prediction of gene expression from promoter-enhancer sequences with multimodal epigenomic profiles.

  PMID 41832145 · PMC13133354 · Nature communications · 2026 · 8 claims · 7 setups

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  EPInformer outperforms existing gene expression prediction models (Xpresso, CREaTor, Seq-GraphReg, Enformer, Borzoi) in rigorous 12-fold cross-chromosome validation for both RNA-seq and CAGE expression prediction

  k562 lines likely cell-type-specific rna-seq cage abc