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).

• Identifying COVID-19-Specific Transcriptomic Biomarkers with Machine Learning Methods.

  PMID 34307679 · PMC8272456 · BioMed research international · 2021 · 7 claims · 2 setups

  Has reproduction · 32

  A pipeline combining Boruta and mRMR feature selection with incremental feature selection (IFS) was used to identify COVID-19-specific transcriptomic biomarkers from blood gene expression data.

  blood bulk kegg

• Estimation of relevant variables on high-dimensional biological patterns using iterated weighted kernel functions.

  PMID 18509521 · PMC2396875 · PloS one · 2008 · 7 claims · 6 setups

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  wKIERA combines a weighted-kernel discriminant (kernel perceptron) with an iterative stochastic probability estimation-of-distribution algorithm to estimate a relevance distribution over variables

  serum colon glioblastoma synthetic seldi-tof gene computational

• 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

• 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

• Constructing support vector machine ensembles for cancer classification based on proteomic profiling.

  PMID 16689692 · PMC5173238 · Genomics, proteomics & bioinformatics · 2005 · 7 claims · 4 setups

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  CSVME, built by selecting a subset of base SVMs via SVM-RFE ranking and fusing them with a trained upper-layer SVM, achieves better classification performance than an ensemble of all base SVMs.

  serum computational seldi-tof svm-rfe-based 10-fold

• 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

• A comparison of classification methods for predicting Chronic Fatigue Syndrome based on genetic data.

  PMID 19772600 · PMC2765429 · Journal of translational medicine · 2009 · 7 claims · 3 setups

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  The naive Bayes model with the wrapper-based feature selection approach performed best among all predictive models tested for distinguishing CFS from controls.

  subjects naive svm c4.5

• Discovery and validation of molecular patterns and immune characteristics in the peripheral blood of ischemic stroke patients.

  PMID 38650649 · PMC11034498 · PeerJ · 2024 · 8 claims · 8 setups

  Has reproduction · 83

  188 differentially expressed genes (DEGs) between IS and control blood samples were identified and enriched in immune-related biological pathways

  blood degs peripheral hub microarray kegg cibersort