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).

• QuantiSNP: an Objective Bayes Hidden-Markov Model to detect and accurately map copy number variation using SNP genotyping data.

  PMID 17341461 · PMC1874617 · Nucleic acids research · 2007 · 8 claims · 7 setups

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  QuantiSNP (OB-HMM) provides probabilistic quantification of copy number states and significantly improves accuracy of segmental aneuploidy identification and breakpoint mapping relative to existing tools (BeadStudio/Illumina)

  genomic same pseudo-normal artificially snp fish molecular

• Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources.

  PMID 16469098 · PMC1409804 · BMC bioinformatics · 2006 · 7 claims · 3 setups

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  AUGUSTUS+ extends the AUGUSTUS GHMM by combining intrinsic sequence information with extrinsic hints via an extended emission alphabet, so the GHMM jointly models the DNA sequence, gene structure, and hint collection.

  chromosome genomic training ghmm-based sequence parameter

• Machine-learning approaches for classifying haplogroup from Y chromosome STR data.

  PMID 18551166 · PMC2396484 · PLoS computational biology · 2008 · 8 claims · 5 setups

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  Y-STR allelic variability is partitioned more by differences among haplogroups than by differences among populations, suggesting Y-STRs carry haplogroup information

  globally same computational publicly y-str snp supervised

• 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

• Predicting failure rate of PCR in large genomes.

  PMID 18492719 · PMC2441781 · Nucleic acids research · 2008 · 7 claims · 8 setups

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  The number of predicted primer-binding sites in genomic DNA is the most important factor determining PCR failure.

  genomic genome pcr combined large-scale exact-match mismatch-tolerant

• 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

• Tracing human genetic histories and natural selection with precise local ancestry inference.

  PMID 40379651 · PMC12084304 · Nature communications · 2025 · 7 claims · 7 setups

  Has reproduction · 76

  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.

  1kgp-16pops independent simulated 1kgp simulated population-level local

• 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

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  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.

  pre-mirnas test conserved-hairpin cross-species secondary svm cross-species

• Using ESTs to improve the accuracy of de novo gene prediction.

  PMID 16817966 · PMC1534067 · BMC bioinformatics · 2006 · 8 claims · 8 setups

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  TWINSCAN_EST combines EST alignments with TWINSCAN via a trainable 'ESTseq' representation and improves exact gene structure prediction accuracy on the whole C. elegans genome

  elegans genome chromosome novo gene partial

• A re-annotation pipeline for Illumina BeadArrays: improving the interpretation of gene expression data.

  PMID 19923232 · PMC2817484 · Nucleic acids research · 2010 · 8 claims · 7 setups

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  A Perl-based pipeline that BLASTs/BLATs Illumina probe sequences against genomes and transcript databases (RefSeq, UCSC Known Genes, UniGene/GenBank, Ensembl) can classify probes by quality grade (Perfect/Good/Bad/No match) and is applicable across 8 BeadArray platforms and other array types

  maqc hepatocytes japanese illeum microarray dasl sequence