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).

• The flexible pocketome engine for structural chemogenomics.

  PMID 19727619 · PMC2975493 · Methods in molecular biology (Clifton, N.J.) · 2009 · 8 claims · 8 setups

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  A comprehensive structural Pocketome combined with ensemble docking enables de novo, structure-based prediction of ligand binding poses and activities for new proteins and new chemical scaffolds.

  pdb bacteriorhodopsin enr asn automated virtual energy-based

• Accurate splice site prediction using support vector machines.

  PMID 18269701 · PMC2230508 · BMC bioinformatics · 2007 · 8 claims · 5 setups

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  Weighted degree (WD) kernel SVMs outperform Markov Chains, GeneSplicer and SpliceMachine for genome-wide splice site recognition

  nn269 dgsplicer caenorhabditis arabidopsis svm genome-wide

• Intrinsic structural disorder confers cellular viability on oncogenic fusion proteins.

  PMID 19888473 · PMC2768585 · PLoS computational biology · 2009 · 8 claims · 5 setups

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  Translocation-related human proteins are significantly enriched in intrinsic structural disorder compared to all human proteins

  translocation-related translocation cyclin-dependent intrinsic pfam randomized

• Analysis of mitochondrial DNA sequences in childhood encephalomyopathies reveals new disease-associated variants.

  PMID 17895983 · PMC1976591 · PloS one · 2007 · 8 claims · 5 setups

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  Sequencing of complete mtDNA genomes in 23 pediatric patients identified 27 significant variants (12 novel, 15 known) associated with mitochondrial encephalomyopathies.

  blood-derived lymphocytes maternal wild-type complete respiratory pcr-rflp

• Using structural bioinformatics to investigate the impact of non synonymous SNPs and disease mutations: scope and limitations.

  PMID 19758473 · PMC2745591 · BMC bioinformatics · 2009 · 8 claims · 8 setups

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  None of 39 tested structural properties can be used as a sole classification criterion to separate neutral SNPs from disease mutations.

  ensembl swissprot same structural foldx side

• Genetic parallels in biomineralization of the calcareous sponge Sycon ciliatum and stony corals.

  PMID 40922549 · PMC12419799 · eLife · 2025 · 8 claims · 8 setups

  Has reproduction · 50

  829 genes are overexpressed in the oscular region of increased calcite spicule formation in S. ciliatum

  sycon ciliatum sponges differential go-term genome

• Unraveling the role of bacteria with heritable versus non-heritable relative abundance in the gut on boar semen quality.

  PMID 41199168 · PMC12590650 · Genetics, selection, evolution : GSE · 2025 · 6 claims · 7 setups

  Has reproduction · 61

  39 heritable and 91 non-heritable bacterial genera were identified in the boar gut based on heritability of relative abundance

  fecal blood boar gut 16s snp gas

• MODBASE, a database of annotated comparative protein structure models and associated resources.

  PMID 18948282 · PMC2686492 · Nucleic acids research · 2009 · 8 claims · 8 setups

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  MODBASE contains 5,152,695 reliable comparative protein structure models for 1,593,209 unique protein sequences.

  sequences chains template chain comparative pairwise ligand

• A nonsense mutation in CRYGC associated with autosomal dominant congenital nuclear cataract in a Chinese family.

  PMID 18618005 · PMC2447816 · Molecular vision · 2008 · 6 claims · 4 setups

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  A heterozygous c.327C>A transversion in exon 3 of CRYGC causes a nonsense mutation (C109X) that cosegregates with autosomal dominant congenital nuclear cataract in a Chinese family.

  genomic type family γc-crystallin pcr comparative clinical

• Predicting positive p53 cancer rescue regions using Most Informative Positive (MIP) active learning.

  PMID 19756158 · PMC2742196 · PLoS computational biology · 2009 · 8 claims · 4 setups

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  MIP active learning is a novel active learning method that preferentially seeks informative Positive (functionally active) examples rather than only maximizing classifier accuracy.

  engineered p53 computational yeast-based regional homology