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).

• 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

• Genomic transcriptional profiling identifies a candidate blood biomarker signature for the diagnosis of septicemic melioidosis.

  PMID 19903332 · PMC3091321 · Genome biology · 2009 · 6 claims · 5 setups

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  A candidate 37-transcript diagnostic signature distinguishes septicemic melioidosis from sepsis caused by other organisms with 100% accuracy in the training set and 78%/80% accuracy in two independent validation sets

  blood whole-genome unsupervised class

• 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

• MALDI profiling of human lung cancer subtypes.

  PMID 19890392 · PMC2767501 · PloS one · 2009 · 8 claims · 8 setups

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  PIMAC/MALDI-TOF peptide profiles combined with classification models can distinguish normal lung from tumor and differentiate NSCLC histological subtypes

  lung tryptic peak ffpe maldi-tof parallel stepwise

• Comprehensive benchmarking of large language models for RNA secondary structure prediction.

  PMID 40205851 · PMC11982019 · Briefings in bioinformatics · 2025 · 7 claims · 4 setups

  Has reproduction · 88

  Existing RNA-LLMs had not previously been evaluated for secondary structure prediction in a unified, fair experimental setup with the same datasets and prediction model.

  archiveii bprna large-scale secondary cross-family self-supervised