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).

• Machine learning-based identification of biomarkers and drugs in immunologically cold and hot pancreatic adenocarcinomas.

  PMID 39152432 · PMC11328457 · Journal of translational medicine · 2024 · 7 claims · 8 setups

  Has reproduction · 42

  PAAD patients can be stratified into immunologically hot and cold subtypes with distinct immune infiltration and survival outcomes.

  paad target bulk single-cell immunohistochemistry

• Machine Learning-Based Integrated Analysis of PANoptosis Patterns in Acute Myeloid Leukemia Reveals a Signature Predicting Survival and Immunotherapy.

  PMID 38322112 · PMC10846924 · International journal of clinical practice · 2024 · 7 claims · 7 setups

  Has reproduction · 71

  AML patients can be categorized into two distinct PANRG-based clusters with differing prognosis and immune characteristics

  aml leukemia bulk consensus immune

• Machine learning algorithm predicts fibrosis-related blood diagnosis markers of intervertebral disc degeneration.

  PMID 37915003 · PMC10619283 · BMC medical genomics · 2023 · 7 claims · 7 setups

  Has reproduction · 68

  CEP120 and SPDL1 are fibrosis-related diagnostic genes for IDD, identified via a random forest model from 29 differentially expressed fibrosis-related genes

  blood gse150408 prediction pbmcs bulk machine roc

• Machine learning reveals microbial interactions driving plastic degradation across plastisphere environments.

  PMID 41657981 · PMC12876002 · Frontiers in microbiology · 2025 · 6 claims · 7 setups

  Has reproduction · 87

  Wastewater plastispheres harbor the most diverse and compositionally even microbial communities among the three habitats.

  ocean wastewater surface plastisphere 16s alpha beta

• Predicting the pathogenicity of missense variants using features derived from AlphaFold2.

  PMID 37084271 · PMC10203375 · Bioinformatics (Oxford, England) · 2023 · 6 claims · 8 setups

  Has reproduction · 85

  AlphaFold2-derived structural features (solvent accessibility, amino acid network features, physicochemical environment, pLDDT) can be used to train a random forest classifier (AlphScore) that distinguishes proxy-benign from proxy-pathogenic missense variants.

  gnomad alphafold2-predicted alphscore proteins machine secondary physicochemical

• Machine learning developed an intratumor heterogeneity signature for predicting clinical outcome and immunotherapy benefit in bladder cancer.

  PMID 39100839 · PMC11291408 · Translational andrology and urology · 2024 · 8 claims · 8 setups

  Has reproduction · 40

  An integrative machine learning procedure (10 methods, 101 algorithm combinations) identified an Enet (alpha=0.2)-based intratumor heterogeneity-related signature (IRS) with the highest average C-index (0.69) across TCGA and GEO cohorts

  bladder skin bulk integrative immune

• Machine learning-based identification of an immunotherapy-related signature to enhance outcomes and immunotherapy responses in melanoma.

  PMID 39355255 · PMC11442245 · Frontiers in immunology · 2024 · 8 claims · 8 setups

  Has reproduction · 69

  66 consensus immunotherapy prognostic genes (CITPGs) were identified from the intersection of WGCNA modules, immunotherapy responder-vs-non-responder DEGs, and tumor-vs-normal DEGs

  melanoma tcga-skcm prjeb23709 microarray wgcna differential consensus

• Predicting deleterious nsSNPs: an analysis of sequence and structural attributes.

  PMID 16630345 · PMC1489951 · BMC bioinformatics · 2006 · 8 claims · 7 setups

  Full-text index only

  Sequence conservation (PSIC score difference) at the nsSNP position is the single most useful attribute for predicting deleterious vs neutral status.

  swissprot nssnp-containing nssnps machine single-attribute sequence

• Machine-learning approaches for classifying haplogroup from Y chromosome STR data.

  PMID 18551166 · PMC2396484 · PLoS computational biology · 2008 · 8 claims · 5 setups

  Full-text index only

  Y-STR allelic variability is partitioned more by differences among haplogroups than by differences among populations, suggesting Y-STRs carry haplogroup information

  globally same computational publicly y-str snp supervised

• Molecular Classification Models for Triple Negative Breast Cancer Subtype Using Machine Learning.

  PMID 34575658 · PMC8472680 · Journal of personalized medicine · 2021 · 6 claims · 4 setups

  Has reproduction · 86

  A training gene set of 719 unique upregulated DEGs (subtype-specific) can be used to build ML models that classify TNBC into BLIA, BLIS, MES, and LAR subtypes.

  known tnbc unique unknown gene machine term

• Multiomic machine learning on lactylation for molecular typing and prognosis of lung adenocarcinoma.

  PMID 39856156 · PMC11760357 · Scientific reports · 2025 · 7 claims · 8 setups

  Has reproduction · 83

  Two lactylation cancer subtypes (CS1, CS2) can be identified in LUAD by multiomics ensemble clustering, with CS1 linked to better overall survival than CS2

  tcga gse31210 multiomics lncrna methylation

• miRbiom: Machine-learning on Bayesian causal nets of RBP-miRNA interactions successfully predicts miRNA profiles.

  PMID 34637468 · PMC8509996 · PloS one · 2021 · 7 claims · 6 setups

  Has reproduction · 100

  RBPs beyond Drosha/DGCR8/Dicer are involved in regulating miRNA biogenesis and explain its spatio-temporal nature

  tissues computational rbps clip-seq rna-seq srna-seq

• Prediction of catalytic residues using Support Vector Machine with selected protein sequence and structural properties.

  PMID 16790052 · PMC1534064 · BMC bioinformatics · 2006 · 8 claims · 7 setups

  Full-text index only

  The Sequential Minimal Optimization (SMO) SVM algorithm was the best-performing classifier among 26 WEKA classifiers for predicting catalytic residues

  benchmarking same pirsf pdb supervised wrapper sequence

• Application of machine learning in SNP discovery.

  PMID 16398931 · PMC1955739 · BMC bioinformatics · 2006 · 8 claims · 6 setups

  Full-text index only

  PolyBayes produces high false-positive SNP predictions even with stringent parameters

  diverse soybean candidate same sts polybayes polyphred

• Comparing the utility of in vivo transposon mutagenesis approaches in yeast species to infer gene essentiality.

  PMID 32681306 · PMC7599172 · Current genetics · 2020 · 7 claims · 7 setups

  Has reproduction · 81

  A Random Forest machine-learning approach can predict gene essentiality from in vivo transposon insertion data across multiple yeast species and transposon systems

  cerevisiae pombe albicans hermes acds piggybac

• Transcriptome and machine learning analysis of the impact of COVID-19 on mitochondria and multiorgan damage.

  PMID 38295140 · PMC10830027 · PloS one · 2024 · 6 claims · 7 setups

  Has reproduction · 71

  Potential cardiac, hepatic, and renal impairments in COVID-19 are associated with ACE2, inflammatory cytokine storms, and mitochondrial pathways.

  nasopharyngeal heart leukocytes blood bulk pathway machine

• Application of Machine Learning in Predicting Hepatic Metastasis or Primary Site in Gastroenteropancreatic Neuroendocrine Tumors.

  PMID 37887568 · PMC10605255 · Current oncology (Toronto, Ont.) · 2023 · 8 claims · 7 setups

  Has reproduction · 59

  Multi-gene random forest models classify primary tumor vs. liver metastasis samples with 100% accuracy in training/test cohorts and >90% accuracy in an independent validation cohort

  pancreatic rna-seq liver tumor bulk machine multi-label

• Clustering and machine learning-based integration identify cancer associated fibroblasts genes' signature in head and neck squamous cell carcinoma.

  PMID 37065499 · PMC10098459 · Frontiers in genetics · 2023 · 8 claims · 8 setups

  Has reproduction · 63

  Clustering of 31 CAFs genes across 868 HNSCC samples identifies two distinct molecular patterns (C1, C2) with different survival outcomes

  hnscc combined gse164690 tcga-hnsc ssgsea unsupervised immune

• A platelet-related signature for predicting the prognosis and immunotherapy benefit in bladder cancer based on machine learning combinations.

  PMID 39280688 · PMC11399026 · Translational andrology and urology · 2024 · 8 claims · 8 setups

  Has reproduction · 51

  An Enet (alpha=0.4) machine-learning-derived 10-gene platelet-related signature is the optimal prognostic model for bladder cancer, with the highest average C-index of 0.73.

  bladder um-uc-3 bulk machine immune

• Integrative transcriptomic and machine learning framework reveals candidate genes and potential mechanisms of aflatoxin B1 exposure in breast cancer.

  PMID 41688730 · PMC12982753 · Scientific reports · 2026 · 7 claims · 8 setups

  Has reproduction · 83

  Twenty-two genes lie at the intersection of AFB1-predicted targets and breast cancer-associated co-expression modules/DEGs

  afb1 breast training candidate computational bulk weighted