From 0f7394eab539df98d350e2a7c76c0b5e6fd0319a Mon Sep 17 00:00:00 2001
From: Christoph Helma <helma@in-silico.ch>
Date: Mon, 1 Feb 2016 13:38:45 +0100
Subject: workshop presentation improved

---
 public/enm-workshop.html | 83 +++++++++++++++++++++++++++++++-----------------
 public/enm-workshop.rst  | 63 ++++++++++++++++++++----------------
 2 files changed, 89 insertions(+), 57 deletions(-)

diff --git a/public/enm-workshop.html b/public/enm-workshop.html
index f0c6781..05d4308 100644
--- a/public/enm-workshop.html
+++ b/public/enm-workshop.html
@@ -371,20 +371,20 @@ ul.auto-toc {
 <div class="slide" id="slide0">
 <h1 class="title">Read across toxicity predictions with nano-lazar</h1>
 
-<p class="center">Christoph Helma</p>
+<p class="center">Christoph Helma, Denis Gebele, Micha Rautenberg</p>
 <p class="center">in silico toxicology gmbh</p>
 <img alt="http://www.enanomapper.net/sites/all/themes/theme807/logo.png" class="center align-center" src="http://www.enanomapper.net/sites/all/themes/theme807/logo.png" />
 
 </div>
-<div class="slide" id="requirements">
-<h1>Requirements</h1>
-<ul class="simple">
+<div class="slide" id="requirements-for-nanoparticle-read-across">
+<h1>Requirements for nanoparticle read-across</h1>
+<ul class="incremental simple">
 <li>Nanoparticle characterisation</li>
 <li>Toxicity measurements</li>
 </ul>
 </div>
-<div class="slide" id="enanomapper-data-import">
-<h1>eNanoMapper data import</h1>
+<div class="slide" id="enanomapper-particle-characterisation">
+<h1>eNanoMapper particle characterisation</h1>
 <ul class="incremental simple">
 <li>Nanoparticles imported: 464</li>
 <li>Nanoparticles with particle characterisation: 394</li>
@@ -403,42 +403,65 @@ ul.auto-toc {
 <div class="slide" id="selected-data">
 <h1>Selected data</h1>
 <p>Protein corona dataset Au particles (106 particles)
-Toxicity endpoint:</p>
+Toxicity endpoint: Net cell association (A549 cell line)</p>
 </div>
 <div class="slide" id="read-across-procedure">
 <h1>Read across procedure</h1>
 <ul class="incremental simple">
-<li>Identify relevant fragments (significant correlation with toxicity)
-TODO list of fragments, number</li>
-<li>Calculate similarities (weighted cosine similarity, correlation coefficients = weights)</li>
-<li>Identify neighbors (particles with more than 0.95 similarity)</li>
-<li>Calculate prediction (weighted average from neighbors, similarities = weights)</li>
+<li>Identify relevant properties (statistically significant correlation with toxicity: 14 from 30 properties)</li>
+<li>Calculate similarities (weighted cosine similarity with correlation coefficients as weights)</li>
+<li>Identify neighbors (particles with similarity &gt; 0.95)</li>
+<li>Calculate prediction (weighted average from neighbors with similarities as weights)</li>
 </ul>
+<p class="incremental">Algorithms for feature selection, similarity calculation and predictions may change in the future.</p>
 </div>
-<div class="slide" id="future-development">
-<h1>Future development</h1>
+<div class="slide" id="future-development-i">
+<h1>Future development (I)</h1>
 <ul class="simple">
 <li>Validation of predictions</li>
 <li>Applicability domain/reliability of predictions</li>
-<li>Accuracy improvements:
-- additional data
-- feature selection
-- similarity calculation
-- predictions (local regression models)</li>
-<li>Usability improvements:
-- additional data (extension of applicability domain, additional endpoints and chemistries)
-- inclusion of ontologies
-- descriptor calculation directly from core and coating chemistries</li>
+<li>Accuracy improvements:<ul>
+<li>additional data</li>
+<li>feature selection</li>
+<li>similarity calculation</li>
+<li>predictions (local regression models)</li>
+</ul>
+</li>
 </ul>
 </div>
-<div class="slide" id="webinterface">
-<h1>Webinterface</h1>
-<p><a class="reference external" href="https://nano-lazar.in-silico.ch/predict">https://nano-lazar.in-silico.ch/predict</a></p>
-<p>Your recommendations?</p>
+<div class="slide" id="id1">
+<h1>Future development (I)</h1>
+<ul class="simple">
+<li>Usability improvements:<ul>
+<li>additional data (extension of applicability domain, additional endpoints and chemistries)</li>
+<li>inclusion of ontologies</li>
+<li>inclusion of protein corona characterisation?</li>
+<li>particle characterisation without experimental data<ul>
+<li>descriptor calculation from core and coating chemistries</li>
+<li>ontological descriptors</li>
+</ul>
+</li>
+</ul>
+</li>
+</ul>
 </div>
-<div class="slide" id="source-code">
-<h1>Source code</h1>
-<p><a class="reference external" href="https://github.com/opentox/nano-lazar">https://github.com/opentox/nano-lazar</a></p>
+<div class="slide" id="nano-lazar">
+<h1>nano-lazar</h1>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field"><th class="field-name">Webinterface:</th><td class="field-body"><a class="reference external" href="https://nano-lazar.in-silico.ch/predict">https://nano-lazar.in-silico.ch/predict</a></td>
+</tr>
+<tr class="field"><th class="field-name">Presentation:</th><td class="field-body"><a class="reference external" href="https://nano-lazar.in-silico.ch/predict/enm-workshop.html">https://nano-lazar.in-silico.ch/predict/enm-workshop.html</a></td>
+</tr>
+<tr class="field"><th class="field-name">Source code:</th><td class="field-body"><a class="reference external" href="https://github.com/enanomapper/nano-lazar-gui">https://github.com/enanomapper/nano-lazar-gui</a></td>
+</tr>
+<tr class="field"><th class="field-name">Issues:</th><td class="field-body"><a class="reference external" href="https://github.com/enanomapper/nano-lazar-gui/issues">https://github.com/enanomapper/nano-lazar-gui/issues</a></td>
+</tr>
+</tbody>
+</table>
+<p>Your comments, ideas, recommendations?</p>
 </div>
 </div>
 </body>
diff --git a/public/enm-workshop.rst b/public/enm-workshop.rst
index 26a3524..d54f4cb 100644
--- a/public/enm-workshop.rst
+++ b/public/enm-workshop.rst
@@ -1,29 +1,29 @@
 .. |date| date::
 
 
-
 =============================================================
 Read across toxicity predictions with nano-lazar
 =============================================================
 
 .. class:: center
 
-  Christoph Helma
+  Christoph Helma, Denis Gebele, Micha Rautenberg
 
   in silico toxicology gmbh
 
   .. image:: http://www.enanomapper.net/sites/all/themes/theme807/logo.png
     :align: center
 
-Requirements
-============
+Requirements for nanoparticle read-across
+=========================================
 
-- Nanoparticle characterisation
-- Toxicity measurements
+.. class:: incremental
 
+  - Nanoparticle characterisation
+  - Toxicity measurements
 
-eNanoMapper data import
-=======================
+eNanoMapper particle characterisation
+=====================================
 
 .. class:: incremental
 
@@ -38,52 +38,61 @@ 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
+  - 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:
+Toxicity endpoint: Net cell association (A549 cell line)
 
 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)
+  - Identify relevant properties (statistically significant correlation with toxicity: 14 from 30 properties)
+  - Calculate similarities (weighted cosine similarity with correlation coefficients as weights)
+  - Identify neighbors (particles with similarity > 0.95)
+  - Calculate prediction (weighted average from neighbors with similarities as weights)
 
-Future development
-==================
+  Algorithms for feature selection, similarity calculation and predictions may change in the future.
+
+Future development (I)
+======================
 
 - Validation of predictions
 - Applicability domain/reliability of predictions
 
 - Accuracy improvements:
+
   - additional data
   - feature selection
   - similarity calculation
   - predictions (local regression models)
 
+Future development (I)
+======================
+
 - Usability improvements:
+
   - additional data (extension of applicability domain, additional endpoints and chemistries)
   - inclusion of ontologies
-  - descriptor calculation directly from core and coating chemistries
+  - inclusion of protein corona characterisation?
+  - particle characterisation without experimental data
 
-Webinterface
-============
+    - descriptor calculation from core and coating chemistries
+    - ontological descriptors 
 
-https://nano-lazar.in-silico.ch/predict
+nano-lazar
+=====================
 
-Your recommendations?
+:Webinterface: https://nano-lazar.in-silico.ch/predict
+:Presentation: https://nano-lazar.in-silico.ch/predict/enm-workshop.html
+:Source code: https://github.com/enanomapper/nano-lazar-gui
+:Issues: https://github.com/enanomapper/nano-lazar-gui/issues
 
-Source code
-===========
+Your comments, ideas, recommendations?
 
-https://github.com/opentox/nano-lazar
-- 
cgit v1.2.3