From: Dyport: dynamic importance-based biomedical hypothesis generation benchmarking technique
Semantic Pair | Text mining | Benchmark | Non-cross-ref DBs | Dataset size |
---|---|---|---|---|
Gene or Genome \(\leftrightarrow\) Gene or Genome | 0.858 | 0.612 | 0.530 | 42625 |
Gene or Genome \(\leftrightarrow\) Organic Chemical | 0.910 | 0.733 | 0.575 | 27060 |
Organic Chemical \(\leftrightarrow\) Organic Chemical | 0.905 | 0.922 | 0.679 | 15081 |
Amino Acid, Peptide, or Protein \(\leftrightarrow\) Gene or Genome | 0.897 | 0.695 | 0.591 | 14542 |
Gene or Genome \(\leftrightarrow\) Pharmacologic Substance | 0.901 | 0.702 | 0.592 | 7843 |
Disease or Syndrome \(\leftrightarrow\) Organic Chemical | 0.900 | 0.856 | 0.660 | 7612 |
Amino Acid, Peptide, or Protein \(\leftrightarrow\) Organic Chemical | 0.906 | 0.820 | 0.564 | 6072 |
Organic Chemical \(\leftrightarrow\) Pharmacologic Substance | 0.898 | 0.890 | 0.616 | 4070 |
Disease or Syndrome \(\leftrightarrow\) Disease or Syndrome | 0.853 | 0.854 | 0.666 | 2893 |
Disease or Syndrome \(\leftrightarrow\) Gene or Genome | 0.847 | 0.690 | 0.575 | 2442 |
Non-stratified ROC AUC | 0.886 | 0.715 | 0.579 | 130240 |