From b614689b3c293be1cbd566f28996e6c3a41f70a3 Mon Sep 17 00:00:00 2001 From: gebele Date: Wed, 9 Aug 2017 12:31:27 +0000 Subject: deleted obsolete files --- presentation/enm-workshop.rst | 89 ------------------------------------------- 1 file changed, 89 deletions(-) delete mode 100644 presentation/enm-workshop.rst (limited to 'presentation/enm-workshop.rst') diff --git a/presentation/enm-workshop.rst b/presentation/enm-workshop.rst deleted file mode 100644 index 26a3524..0000000 --- a/presentation/enm-workshop.rst +++ /dev/null @@ -1,89 +0,0 @@ -.. |date| date:: - - - -============================================================= -Read across toxicity predictions with nano-lazar -============================================================= - -.. class:: center - - Christoph Helma - - in silico toxicology gmbh - - .. image:: http://www.enanomapper.net/sites/all/themes/theme807/logo.png - :align: center - -Requirements -============ - -- Nanoparticle characterisation -- Toxicity measurements - - -eNanoMapper data import -======================= - -.. class:: incremental - - - Nanoparticles imported: 464 - - Nanoparticles with particle characterisation: 394 - - Nanoparticles with toxicity data: 167 - - Nanoparticles with toxicity data and particle characterisation: 160 - - -eNanoMapper toxicity endpoints -============================== - -.. class:: incremental - -- Toxicity endpoints: 41 -- Toxicity endpoints with more than one measurement value: 22 -- Toxicity endpoints with more than 10 measurements: 2 - -Selected data -============= - -Protein corona dataset Au particles (106 particles) -Toxicity endpoint: - -Read across procedure -===================== - -.. class:: incremental - -- Identify relevant fragments (significant correlation with toxicity) - TODO list of fragments, number -- Calculate similarities (weighted cosine similarity, correlation coefficients = weights) -- Identify neighbors (particles with more than 0.95 similarity) -- Calculate prediction (weighted average from neighbors, similarities = weights) - -Future development -================== - -- Validation of predictions -- Applicability domain/reliability of predictions - -- Accuracy improvements: - - additional data - - feature selection - - similarity calculation - - predictions (local regression models) - -- Usability improvements: - - additional data (extension of applicability domain, additional endpoints and chemistries) - - inclusion of ontologies - - descriptor calculation directly from core and coating chemistries - -Webinterface -============ - -https://nano-lazar.in-silico.ch/predict - -Your recommendations? - -Source code -=========== - -https://github.com/opentox/nano-lazar -- cgit v1.2.3