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).

• Integrated analysis of genetic and proteomic data identifies biomarkers associated with adverse events following smallpox vaccination.

  PMID 18923431 · PMC2692715 · Genes and immunity · 2009 · 7 claims · 6 setups

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  A two-stage strategy (Random Forest filtering followed by decision tree modeling) can integrate categorical genetic and continuous proteomic data to identify biomarkers of AE risk

  ebv-transformed serum combined rf-filtered snp serum random

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

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

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  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

• Development of proteomic patterns for detecting lung cancer.

  PMID 14757945 · PMC3851077 · Disease markers · 2003 · 8 claims · 3 setups

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  A decision tree classification algorithm built on three serum protein mass peaks (8122Da, 1452Da, 1610Da) can discriminate lung cancer patients from healthy controls

  serum pooled seldi-tof-ms decision reproducibility

• Comparative analysis of molecular signatures reveals a hybrid approach in breast cancer: Combining the Nottingham Prognostic Index with gene expressions into a hybrid signature.

  PMID 35143511 · PMC8830616 · PloS one · 2022 · 8 claims · 6 setups

  Has reproduction · 48

  A hybrid signature combining the Nottingham Prognostic Index with SIS-selected gene expressions can be built in a data-driven fashion (NPI treated as a gene expression during feature selection).

  metabric scan-b gene rna-seq feature

• 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

• In silico analysis of missense substitutions using sequence-alignment based methods.

  PMID 18951440 · PMC3431198 · Human mutation · 2008 · 8 claims · 7 setups

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  Carefully validated PMSA-based computational algorithms can achieve predictive values of ~75-95% for classifying missense substitutions as pathogenic or neutral.

  clinically sequence curated deep blosum62 sift align-gvgd

• A urine extracellular vesicle lncRNA classifier for high-grade prostate cancer and increased risk of progression: A multi-center study.

  PMID 37852185 · PMC10591064 · Cell reports. Medicine · 2023 · 8 claims · 8 setups

  Has reproduction · 65

  A 3-lncRNA urine extracellular vesicle classifier (Clnc: AC015987.1, CTD-2589M5.4, RP11-363E6.3) detects high-grade PCa with higher accuracy than PCA3, mpMRI, PCPT-RC 2.0, and ERSPC-RC

  urinary tcga paired urine sequencing lncrna qrt-pcr

• Boosting accuracy of automated classification of fluorescence microscope images for location proteomics.

  PMID 15207009 · PMC449699 · BMC bioinformatics · 2004 · 8 claims · 8 setups

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  New classifiers (SVMs, ensembles) and new wavelet-derived (Gabor, Daubechies) features improve recognition of protein subcellular location patterns over the previous neural network approach

  hela automated stepwise training-set-size

• Limitations in SELDI-TOF MS whole serum proteomic profiling with IMAC surface to specifically detect colorectal cancer.

  PMID 19689818 · PMC2743709 · BMC cancer · 2009 · 7 claims · 3 setups

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  The previously reported classifier (m/z 8,132 and 4,002) failed to discriminate CRC patients from healthy volunteers in this independent validation cohort

  serum pooled seldi-tof comparative decision

• 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