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).

• Ab initio identification of human microRNAs based on structure motifs.

  PMID 18088431 · PMC2238772 · BMC bioinformatics · 2007 · 8 claims · 7 setups

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  MiRPred predicts miRNA precursors ab initio using only predicted secondary structure motifs, ignoring nucleotide sequence

  genome mirna hairpins chromosome secondary linear five-fold

• 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

• Prediction of candidate primary immunodeficiency disease genes using a support vector machine learning approach.

  PMID 19801557 · PMC2780952 · DNA research : an international journal for rapid publication of reports on genes and genomes · 2009 · 6 claims · 3 setups

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  An SVM trained on 69 binary features of known PID genes can accurately classify PID vs non-PID genes and predict novel candidate PID genes

  genome training svm support leave-one-out sensitivity

• Integration of Transcriptomics With Interpretable Artificial Intelligence for Identifying Molecular Signatures of Physiological Stress in Sleep Deprivation.

  PMID 42216239 · PMC13240488 · Journal of cellular and molecular medicine · 2026 · 8 claims · 8 setups

  Has reproduction · 49

  S100A3 is a robust candidate biomarker showing consistent discriminatory performance across the acute sleep deprivation training cohort, an independent sleep deprivation cohort, and a chronic insomnia cohort.

  peripheral blood normal integrated bulk interpretable immune

• Application of machine learning in SNP discovery.

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

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

  diverse soybean candidate same sts polybayes polyphred

• 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

• 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

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

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

  Has reproduction · 83

  Ten multiomics clustering algorithms identify two distinct lactylation cancer subtypes (CS1 and CS2) in LUAD

  tcga gse13213 gse31210 multiomics closest ssgsea

• 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

• STAT1 and IL-7 as potential diagnostic biomarkers for distinguishing high-grade from low-grade serous ovarian cancer: a multi-cohort analysis.

  PMID 42058211 · PMC13120972 · Frontiers in immunology · 2026 · 7 claims · 6 setups

  Has reproduction · 50

  STAT1 and IL-7 are differentially expressed immune-related genes that can distinguish HGSOC from LGSOC and may serve as ancillary diagnostic biomarkers.

  hgsoc training independent paraffin-embedded transcriptome machine-learning diagnostic

• 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

• 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 tumors can be consensus-clustered into immunologically hot and cold subtypes based on CIBERSORT-derived immune cell fractions, with significantly different survival outcomes.

  paad degs bulk consensus tumor

• 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

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

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

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  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

• Scalable Prediction of Acute Myeloid Leukemia Using High-Dimensional Machine Learning and Blood Transcriptomics.

  PMID 31918046 · PMC6992905 · iScience · 2020 · 8 claims · 8 setups

  Has reproduction · 96

  Data-driven, high-dimensional ML approaches that learn multivariate signatures directly from genome-wide transcriptomic data (no prior gene selection) yield accurate and robust AML classifiers.

  peripheral pbmc datasets hg-u133 gene bulk machine

• Predicting Bone Metastasis Using Gene Expression-Based Machine Learning Models.

  PMID 34858485 · PMC8631472 · Frontiers in genetics · 2021 · 7 claims · 5 setups

  Has reproduction · 62

  A DNN model using the top 34 betweenness-centrality-ranked hub genes predicts bone metastasis with AUC of 92.11% on the GEO validation data.

  breast degs geo tcga gene protein-protein machine

• Swarm intelligence based wavelet coefficient feature selection for mass spectral classification: an application to proteomics data.

  PMID 19733729 · PMC2748225 · Analytica chimica acta · 2009 · 8 claims · 4 setups

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  ACA-based wavelet coefficient feature selection can achieve up to 100% classification accuracy on training, validating, and independent testing sets using only 5 selected features.

  blood baseline-corrected 953-dimensional training seldi-tof wavelet ant

• Cancer-specific high-throughput annotation of somatic mutations: computational prediction of driver missense mutations.

  PMID 19654296 · PMC2763410 · Cancer research · 2009 · 7 claims · 7 setups

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  CHASM, a Random Forest-based computational method, was developed to identify and prioritize missense mutations likely to be functional drivers of tumor cell proliferation.

  missense same synthetic tp53 random support principal

• Integrative transcriptomics and single-cell transcriptomics analyses reveal potential biomarkers and mechanisms of action in papillary thyroid carcinoma.

  PMID 40520228 · PMC12162626 · Frontiers in genetics · 2025 · 8 claims · 8 setups

  Has reproduction · 49

  ENTPD1, SERPINA1, and TACSTD2 are potential transcriptomic biomarkers for PTC

  ptc degs key bulk kegg weighted

• Speeding disease gene discovery by sequence based candidate prioritization.

  PMID 15766383 · PMC1274252 · BMC bioinformatics · 2005 · 7 claims · 8 setups

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  Disease genes (OMIM) differ significantly from non-disease genes in sequence-based features including gene/cDNA/protein size, exon number, homolog conservation, secretion signal, 3' UTR length, CpG islands, and distance to nearest gene.

  ensembl training same hgmd comparative machine tenfold