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).

• Automatic discovery of cross-family sequence features associated with protein function.

  PMID 16409628 · PMC1395344 · BMC bioinformatics · 2006 · 8 claims · 6 setups

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  A self-supervised data mining approach can find relationships between sequence features and functional annotations without preconceived functional categories.

  non-redundant same evolved eukaryotic self-supervised experiment self-organizing

• Oligomeric protein structure networks: insights into protein-protein interactions.

  PMID 16336694 · PMC1326230 · BMC bioinformatics · 2005 · 8 claims · 6 setups

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  Interface amino acid clusters identified at Imin=6% correlate well with residues losing accessible surface area (δASA) upon oligomerization

  non-redundant same known complexes structure hub comparison

• Predicting deleterious nsSNPs: an analysis of sequence and structural attributes.

  PMID 16630345 · PMC1489951 · BMC bioinformatics · 2006 · 8 claims · 7 setups

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  Sequence conservation (PSIC score difference) at the nsSNP position is the single most useful attribute for predicting deleterious vs neutral status.

  swissprot nssnp-containing nssnps machine single-attribute sequence

• Functional coverage of the human genome by existing structures, structural genomics targets, and homology models.

  PMID 16118666 · PMC1188274 · PLoS computational biology · 2005 · 8 claims · 5 setups

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  Existing PDB structures provide single-domain coverage for 37% of functional classes in the human genome and complete (whole-protein) structure coverage for 25%.

  genome functional registered omim comparative kendall's homology

• An SVM-based system for predicting protein subnuclear localizations.

  PMID 16336650 · PMC1325059 · BMC bioinformatics · 2005 · 7 claims · 3 setups

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  New kernels defined on k-peptide vectors mapped by BLOSUM62-based high-scored pair matrices (D1, D2, D3) improve SVM discrimination of protein subnuclear localization compared to conventional k-peptide encodings.

  single-localization multi-localization same svm sequence