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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Wiggle-predicting functionally flexible regions from primary sequence.
PMID 16839194 · PMC1500818 · PLoS computational biology · 2006 · 7 claims · 6 setups
A GNM-derived, correlation-weighted 'FF score' can objectively define functionally flexible regions (FFRs) that match experimentally confirmed flexible/functional regions (hinges, recognition loops, catalytic loops).
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JIGSAW, GeneZilla, and GlimmerHMM: puzzling out the features of human genes in the ENCODE regions.
PMID 16925843 · PMC1810558 · Genome biology · 2006 · 8 claims · 4 setups
Adding model states for specific biological features (signal peptides, CpG islands, etc.) to non-comparative GHMM gene finders did little or nothing to enhance predictive accuracy, sometimes reducing it.
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In silico segmentations of lentivirus envelope sequences.
PMID 17376229 · PMC1847453 · BMC bioinformatics · 2007 · 8 claims · 8 setups
C and V regions of lentivirus SU sequences have distinct statistical (oligonucleotide/amino-acid) compositions that HMMs can learn and use to delimit them.
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AUGUSTUS at EGASP: using EST, protein and genomic alignments for improved gene prediction in the human genome.
PMID 16925833 · PMC1810548 · Genome biology · 2006 · 8 claims · 5 setups
AUGUSTUS predicted significantly more genes correctly than any other ab initio program in EGASP
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Using several pair-wise informant sequences for de novo prediction of alternatively spliced transcripts.
PMID 16925842 · PMC1810557 · Genome biology · 2006 · 8 claims · 4 setups
MARS, an extension of the Twinscan algorithm, uses multiple pairwise informant genomes to predict human alternatively spliced transcripts de novo without expressed sequence information.
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The MAPPER database: a multi-genome catalog of putative transcription factor binding sites.
PMID 15608292 · PMC540057 · Nucleic acids research · 2005 · 8 claims · 6 setups
Built a library of 1134 HMM models (359 matrix-derived, 718 factor-derived, 57 JASPAR-derived), corresponding to 863 distinct TF names, from TRANSFAC and JASPAR binding site data
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Has reproduction · 99
Systematic benchmarking of tools for CpG methylation detection from nanopore sequencing.
PMID 34103501 · PMC8187371 · Nature communications · 2021 · 7 claims · 4 setups
Nanopore methylation detection tools exhibit a tradeoff between false positives and false negatives and high dispersion relative to expected per-site methylation frequencies.
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Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine.
PMID 16381612 · PMC1360673 · BMC bioinformatics · 2005 · 7 claims · 7 setups
A 32-dimensional triplet structure-sequence feature vector combined with SVM (triplet-SVM) can distinguish real human pre-miRNAs from pseudo pre-miRNA hairpins with ~90% accuracy.
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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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Predicting failure rate of PCR in large genomes.
PMID 18492719 · PMC2441781 · Nucleic acids research · 2008 · 7 claims · 8 setups
The number of predicted primer-binding sites in genomic DNA is the most important factor determining PCR failure.
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Has reproduction · 76
Tracing human genetic histories and natural selection with precise local ancestry inference.
PMID 40379651 · PMC12084304 · Nature communications · 2025 · 7 claims · 7 setups
Orchestra, a two-stage LAI method combining a recombination-distance base layer with a deep learning (convolutional + attention) smoothing module, outperforms RFmix, FLARE and Gnomix in precision and recall across simulated admixture generations.
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Has reproduction · 70
Predicting enhancers in mammalian genomes using supervised hidden Markov models.
PMID 30917778 · PMC6437899 · BMC bioinformatics · 2019 · 8 claims · 8 setups
eHMM predicts enhancers with high precision and recall comparable to state-of-the-art methods and consistently outperforms them in accuracy and resolution
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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