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).

• SNAP: predict effect of non-synonymous polymorphisms on function.

  PMID 17526529 · PMC1920242 · Nucleic acids research · 2007 · 7 claims · 8 setups

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  SNAP, a neural network-based method using sequence-derived information, predicts whether a non-synonymous SNP is neutral or non-neutral for protein function

  combined escherichia bacteriophage hiv-1 neural benchmark comparative

• Prioritization of candidate cancer genes--an aid to oncogenomic studies.

  PMID 18710882 · PMC2566894 · Nucleic acids research · 2008 · 8 claims · 8 setups

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  Computational classifiers using combinations of protein conservation, gene structure, protein domains, protein interactions, and regulatory data can distinguish known cancer genes (CD/CR) from unlabelled human genes

  genes cancer interpro interactome averaged cross-validation domain

• Discovering cancer genes by integrating network and functional properties.

  PMID 19765316 · PMC2758898 · BMC medical genomics · 2009 · 8 claims · 6 setups

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  Cancer genes have distinct PPI network topology (higher connectivity, higher clustering coefficient, shorter path length to known cancer genes) compared to non-cancer genes

  genes gene colon ppi pfam term

• Improved epigenetic age prediction models by combining sex chromosome and autosomal markers.

  PMID 40665390 · PMC12261677 · Epigenetics & chromatin · 2025 · 7 claims · 5 setups

  Has reproduction · 48

  Combining sex chromosomal DNAm markers with autosomal age-informative markers can produce a high-accuracy age prediction model competitive with autosomal-only models

  blood buffy methylation random spearman

• 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

• Genome-wide prioritization of disease genes and identification of disease-disease associations from an integrated human functional linkage network.

  PMID 19728866 · PMC2768980 · Genome biology · 2009 · 6 claims · 6 setups

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  Integrating 16 genomic features (32 sub-features) via a naïve Bayes classifier produces a genome-scale FLN of 21,657 human genes and 22,388,609 weighted links that outperforms any individual data source for inferring functional linkages.

  genome gene omim known naïve linkage disease-centric

• Local combinational variables: an approach used in DNA-binding helix-turn-helix motif prediction with sequence information.

  PMID 19651875 · PMC2761287 · Nucleic acids research · 2009 · 8 claims · 7 setups

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  The LCV approach predicts HTH motifs with 93.29% accuracy, 93.93% sensitivity and 92.66% specificity using only primary sequence information

  quintessentialset-88 hth same newly lcs svm traditional

• 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

• Predicting enhancers in mammalian genomes using supervised hidden Markov models.

  PMID 30917778 · PMC6437899 · BMC bioinformatics · 2019 · 8 claims · 8 setups

  Has reproduction · 70

  eHMM predicts enhancers with high precision and recall comparable to state-of-the-art methods and consistently outperforms them in accuracy and resolution

  esc atac-seq chip-seq cage

• Gene Set Enrichment Analysis Reveals Individual Variability in Host Responses in Tuberculosis Patients.

  PMID 34421903 · PMC8375662 · Frontiers in immunology · 2021 · 8 claims · 8 setups

  Has reproduction · 71

  TB patients show substantial individual variability in the intensity of hallmark IFN responses, as well as in complement system, metabolic, and other pathway responses.

  blood cynomolgus external gene differential principal

• Filtering high-throughput protein-protein interaction data using a combination of genomic features.

  PMID 15833142 · PMC1127019 · BMC bioinformatics · 2005 · 8 claims · 8 setups

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  A combination of three genomic features (interacting Pfam domains, GO annotations, sequence homology) using naive Bayesian networks predicts true protein-protein interactions with high sensitivity and good specificity.

  saccharomyces bank caenorhabditis homo yeast mass naive

• Towards precise classification of cancers based on robust gene functional expression profiles.

  PMID 15774002 · PMC1274255 · BMC bioinformatics · 2005 · 6 claims · 7 setups

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  Functional expression profiles (FEPs) achieve comparable or better classification performance than conventional gene expression profiles (GEPs) across four public microarray datasets

  nci60 lymphoma fep go-annotated cdna recursive hypergeometric

• 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

• 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

• An SVM-based system for predicting protein subnuclear localizations.

  PMID 16336650 · PMC1325059 · BMC bioinformatics · 2005 · 7 claims · 3 setups

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  New kernels defined on k-peptide vectors mapped by BLOSUM62-based high-scored pair matrices (D1, D2, D3) improve SVM discrimination of protein subnuclear localization compared to conventional k-peptide encodings.

  single-localization multi-localization same svm sequence