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author | Christoph Helma <helma@in-silico.ch> | 2017-02-09 14:25:19 +0100 |
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committer | Christoph Helma <helma@in-silico.ch> | 2017-02-09 14:25:19 +0100 |
commit | db82eef974b8783c40e7daa504feead3f555fdb8 (patch) | |
tree | a9bf02a6455cb2cb399b15bed3fcd759cb2b3448 /loael.md | |
parent | 7ad7c10c1e708f6b5a3473de24dbeab03d0b74a3 (diff) |
directories restructured
Diffstat (limited to 'loael.md')
-rw-r--r-- | loael.md | 2 |
1 files changed, 1 insertions, 1 deletions
@@ -163,7 +163,7 @@ of connected atoms. MolPrint2D fingerprints are generated dynamically from chemical structures and do not rely on predefined lists of fragments (such as OpenBabel FP3, FP4 or -MACCs fingerprints or lists of toxocophores/toxicophobes). This has the +MACCs fingerprints or lists of toxocophores/toxicophobes). That has the advantage the they may capture substructures of toxicological relevance that are not included in other fingerprints. Preliminary experiments have shown that predictions with MolPrint2D fingerprints are indeed more accurate than |