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).

Publications 1.3k Datasets 392.5k Experiments 44

System / cell line: predicted ✕ Assay: cross-validation ✕ Clear

VIRGO: computational prediction of gene functions.

PMID 16845022 · PMC1538839 · Nucleic acids research · 2006 · 8 claims · 6 setups

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VIRGO constructs a functional linkage network (FLN) from gene expression and molecular interaction data, labels genes with GO annotations, and propagates these labels to predict functions of unlabelled genes

cerevisiae sapiens leave-one-out gene protein-protein
Species-specific protein sequence and fold optimizations.

PMID 12487631 · PMC139977 · BMC bioinformatics · 2002 · 7 claims · 7 setups

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Environmental niche is a significant factor explaining variability in amino acid composition across 100 complete genomes

predicted mean over orf principal hierarchical domain-based
Interaction profile-based protein classification of death domain.

PMID 15189571 · PMC459208 · BMC bioinformatics · 2004 · 7 claims · 6 setups

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An SVM-based classifier using Residue Pair Interaction Profiles (RPIPs) can classify death domain superfamily members into subfamilies with 89% average cross-validation accuracy

homology-modeled death homology putative rigid-body homology model
InSite: a computational method for identifying protein-protein interaction binding sites on a proteome-wide scale.

PMID 17868464 · PMC2375030 · Genome biology · 2007 · 8 claims · 8 setups

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InSite predicts protein-pair-specific binding motifs ('Motif M on protein A binds to protein B') by integrating heterogeneous PPI and motif-motif interaction evidence within a Bayesian network trained by EM

saccharomyces homo bank computational yeast tandem
CanPredict: a computational tool for predicting cancer-associated missense mutations.

PMID 17537827 · PMC1933186 · Nucleic acids research · 2007 · 8 claims · 7 setups

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CanPredict is a web application providing public access to a random forest classifier that combines SIFT, LogR.E-value, and GOSS scores to predict whether a missense mutation is cancer-associated

missense observed sjoblom refseq cross-validation recurrence comparative
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
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
Broad network-based predictability of Saccharomyces cerevisiae gene loss-of-function phenotypes.

PMID 18053250 · PMC2246260 · Genome biology · 2007 · 8 claims · 4 setups

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Loss-of-function phenotypes in yeast are predictable from a gene's connections in a functional gene network via guilt-by-association.

saccharomyces guilt-by-association comparison network-guided
Predicting the phenotypic effects of non-synonymous single nucleotide polymorphisms based on support vector machines.

PMID 18005451 · PMC2216041 · BMC bioinformatics · 2007 · 8 claims · 5 setups

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Parepro, an SVM-based method integrating three attribute sets (RD, MI, IE) derived from evolutionary and residue-property information, predicts whether an nsSNP is deleterious or neutral.

sequences target svm benchmark homology
ProMiR II: a web server for the probabilistic prediction of clustered, nonclustered, conserved and nonconserved microRNAs.

PMID 16845048 · PMC1538778 · Nucleic acids research · 2006 · 6 claims · 4 setups

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ProMiR II improves on the original ProMiR by integrating free energy, G/C ratio, conservation score and entropy for more controllable miRNA prediction

genome cytomegalovirus six probabilistic 5-fold directional
Genome-scale modeling identifies dynamic metabolic vulnerabilities during the epithelial to mesenchymal transition.

PMID 39730911 · PMC11681178 · Communications biology · 2024 · 8 claims · 8 setups

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EMT involves temporal, stage-specific metabolic reprogramming with distinct dependencies in glycolysis and glutamine metabolism.

a549 recon1 cancer lung bulk single-cell genome-scale
A Decentralized Kidney Transplant Biopsy Classifier for Transplant Rejection Developed Using Genes of the Banff-Human Organ Transplant Panel.

PMID 35619722 · PMC9128066 · Frontiers in immunology · 2022 · 6 claims · 6 setups

Has reproduction · 90

A random forest model trained solely on B-HOT panel genes (B-HOT Model) accurately classifies kidney transplant biopsies as NR, ABMR, or TCMR.

kidney gene combined microarray machine sequential
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
MiPred: classification of real and pseudo microRNA precursors using random forest prediction model with combined features.

PMID 17553836 · PMC1933124 · Nucleic acids research · 2007 · 8 claims · 8 setups

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A hybrid feature combining local contiguous triplet structure-sequence composition, MFE of the secondary structure, and P-value of a randomization test improves classification of real vs pseudo pre-miRNAs

real combined pre-mirna training random independent repeated
Prodepth: predict residue depth by support vector regression approach from protein sequences only.

PMID 19759917 · PMC2742725 · PloS one · 2009 · 8 claims · 8 setups

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Residue depth can be reliably predicted solely from protein primary sequence using support vector regression on sequence-derived features.

structure sequences sequence residue dssp psi-blast
SNAP predicts effect of mutations on protein function.

PMID 18757876 · PMC2562009 · Bioinformatics (Oxford, England) · 2008 · 8 claims · 3 setups

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SNAP is a publicly available web-server implementation predicting functional effects (neutral/non-neutral) of single amino acid substitutions.

mutant insulin neural alanine mutation
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
Bayesian prediction of microbial oxygen requirement.

PMID 26913185 · PMC4743139 · F1000Research · 2013 · 7 claims · 8 setups

Has reproduction · 76

A naive Bayesian classifier based on presence/absence of class-associated Pfam-A domains can distinguish three oxygen requirement classes (aerobe, anaerobe, facultative anaerobe) from genome sequence, unlike prior studies that only made pairwise distinctions.

bacterial selected predicted pfam-a genome gene domain
Statistical learning of peptide retention behavior in chromatographic separations: a new kernel-based approach for computational proteomics.

PMID 18053132 · PMC2254445 · BMC bioinformatics · 2007 · 6 claims · 5 setups

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The paired oligo-border kernel (POBK) combined with SVMs predicts peptide adsorption/elution in SAX-SPE and retention time in IP-RP-HPLC more accurately than existing methods.

peptides peptide sax-spe ip-rp-hplc cross-run
Genomic variation in myeloma: design, content, and initial application of the Bank On A Cure SNP Panel to detect associations with progression-free survival.

PMID 18778477 · PMC2553089 · BMC medicine · 2008 · 7 claims · 7 setups

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A custom BOAC SNP panel of 3404 SNPs in 983 genes was developed using the Affymetrix GeneChip Targeted Genotyping Platform, focused on non-synonymous coding SNPs and regulatory-region SNPs in candidate genes.

coriell myeloma duplicate snp targeted genotyping machine

Experiments

VIRGO: computational prediction of gene functions.

Species-specific protein sequence and fold optimizations.

Interaction profile-based protein classification of death domain.

InSite: a computational method for identifying protein-protein interaction binding sites on a proteome-wide scale.

CanPredict: a computational tool for predicting cancer-associated missense mutations.

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

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

Broad network-based predictability of Saccharomyces cerevisiae gene loss-of-function phenotypes.

Predicting the phenotypic effects of non-synonymous single nucleotide polymorphisms based on support vector machines.

ProMiR II: a web server for the probabilistic prediction of clustered, nonclustered, conserved and nonconserved microRNAs.

Genome-scale modeling identifies dynamic metabolic vulnerabilities during the epithelial to mesenchymal transition.

A Decentralized Kidney Transplant Biopsy Classifier for Transplant Rejection Developed Using Genes of the Banff-Human Organ Transplant Panel.

Ab initio identification of human microRNAs based on structure motifs.

MiPred: classification of real and pseudo microRNA precursors using random forest prediction model with combined features.

Prodepth: predict residue depth by support vector regression approach from protein sequences only.

SNAP predicts effect of mutations on protein function.

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

Bayesian prediction of microbial oxygen requirement.

Statistical learning of peptide retention behavior in chromatographic separations: a new kernel-based approach for computational proteomics.

Genomic variation in myeloma: design, content, and initial application of the Bank On A Cure SNP Panel to detect associations with progression-free survival.