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).
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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
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
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Speeding disease gene discovery by sequence based candidate prioritization.
PMID 15766383 · PMC1274252 · BMC bioinformatics · 2005 · 7 claims · 8 setups
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.
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Ab initio identification of human microRNAs based on structure motifs.
PMID 18088431 · PMC2238772 · BMC bioinformatics · 2007 · 8 claims · 7 setups
MiRPred predicts miRNA precursors ab initio using only predicted secondary structure motifs, ignoring nucleotide sequence
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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
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
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Has reproduction · 83
Macrel: antimicrobial peptide screening in genomes and metagenomes.
PMID 33384902 · PMC7751412 · PeerJ · 2020 · 8 claims · 8 setups
Macrel is an end-to-end pipeline that predicts high-quality AMP candidates from peptides, contigs, or reads of (meta)genomes
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CanPredict: a computational tool for predicting cancer-associated missense mutations.
PMID 17537827 · PMC1933186 · Nucleic acids research · 2007 · 8 claims · 7 setups
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
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Clustering of phosphorylation site recognition motifs can be exploited to predict the targets of cyclin-dependent kinase.
PMID 17316440 · PMC1852407 · Genome biology · 2007 · 8 claims · 6 setups
CDK consensus motifs are frequently clustered (closely spaced) in known CDK substrate proteins rather than uniformly distributed
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Computational disease gene identification: a concert of methods prioritizes type 2 diabetes and obesity candidate genes.
PMID 16757574 · PMC1475747 · Nucleic acids research · 2006 · 6 claims · 8 setups
Applying seven independent computational disease-gene prioritization methods in concert to 9556 positional candidate genes identifies a prioritized set of likely T2D and obesity candidate genes
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Non-EST-based prediction of novel alternatively spliced cassette exons with cell signaling function in Caenorhabditis elegans and human.
PMID 17452356 · PMC1904267 · Nucleic acids research · 2007 · 8 claims · 7 setups
PASE (Prediction of Alternative Signaling Exons) is a computational algorithm combining Markov splice-site models, a Bayesian classifier, species conservation, and Scansite motif scoring to identify novel alternative cassette exons involved in cell signaling.
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Has reproduction · 83
Accurate prediction of metagenome-assembled genome completeness by MAGISTA, a random forest model built on alignment-free intra-bin statistics.
PMID 35248155 · PMC8898458 · Environmental microbiome · 2022 · 7 claims · 7 setups
MAGISTA, a random forest model built on alignment-free intra-bin distance-distribution statistics, can estimate MAG completeness and purity without relying on reference marker genes.