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 catalytic residues using Support Vector Machine with selected protein sequence and structural properties.
PMID 16790052 · PMC1534064 · BMC bioinformatics · 2006 · 8 claims · 7 setups
The Sequential Minimal Optimization (SMO) SVM algorithm was the best-performing classifier among 26 WEKA classifiers for predicting catalytic residues
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Exhaustive prediction of disease susceptibility to coding base changes in the human genome.
PMID 18793467 · PMC2537574 · BMC bioinformatics · 2008 · 8 claims · 7 setups
Inter-species conservation is the strongest single predictor of disease-associated coding mutations among the factors tested.
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EGASP: the human ENCODE Genome Annotation Assessment Project.
PMID 16925836 · PMC1810551 · Genome biology · 2006 · 8 claims · 6 setups
Best-performing computational gene prediction methods correctly predict at least one transcript for close to 70% of annotated genes in the ENCODE regions.
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Has reproduction · 89
miRge 2.0 for comprehensive analysis of microRNA sequencing data.
PMID 30153801 · PMC6112139 · BMC bioinformatics · 2018 · 8 claims · 6 setups
miRge 2.0 introduces a novel SVM-based miRNA detection method using both hairpin structure and isomiR composition, yielding higher specificity for miRNA identification
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Has reproduction · 84
An accurate method for identifying recent recombinants from unaligned sequences.
PMID 35025988 · PMC8963311 · Bioinformatics (Oxford, England) · 2022 · 8 claims · 4 setups
A novel algorithm combining the JHMM (Zilversmit et al. 2013) mosaic representation with a distance-based triple comparison can identify recombinant sequences and their parents from unaligned, gene-length sequences without a reference panel.
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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.