Laboratoire de Chémoinformatique – UMR 7140 CNRS

Strasbourg Summer School in Chemoinformatics – 2020

Program

The program includes plenary lectures, poster session, oral presentations and hands-on tutorials. It covers the following topics :

  • Big Data in chemistry
  • Material Informatics
  • Machine-Learning methods
  • Virtual screening techniques
  • In silico pharmacology

Chemoinformatics Strasbourg Summer School
(University of Strasbourg, 29 June – 3 July 2020)

Monday 29 June
Jürgen BAJORATH
(University of Bonn, Germany)
Evaluating Progress in Lead Optimization
Tuesday 30 June
Artem CHERKASOV
(University of British Columbia, Canada)
Deep Docking – a DNN Enabled Approach for Virtual Screening and its Application for COVID-19 Drug Discovery
Ola ENGKVIST
(ASTRAZENECA, Gothenburg, Sweden)

Cancelled
AI in drug discovery an industrial perspective
Alex TROPSHA
(University of North Carolina, USA)
Biomedical Big Data Analytics : From Knowledge Graphs to de novo Drug Discovery
José L. MEDINA-FRANCO
(National Autonomous University of Mexico, Mexico)
StARs and constellations in chemical space : a visual representation of Structure-Activity Relationships (download pdf)
Wednesday 1 July
Matthias RAREY
(University of Hamburg, Germany)
SMARTS.plus Supporting Chemical Pattern Design
Christoph SOTRIFFER
(University of Wuerzburg, Germany)
Simulation-driven model builing :
Towards prediction of site-specific bioconjugation
Thursday 2 July
Johannes KIRCHMAIR
(University of Vienna, Austria)
Chemoinformatics in Natural Product-Based Drug Discovery
Roger SAYLE
(NextMove Software, UK)
Automated mining of a database of 9.4M reactions from the patent literature, and its application to synthesis planning (download pdf)
Friday 3 July
Hanoch SENDEROWITZ
(Bar Ilan University, Israel)
Materials Informatics : The marriage of data and materials sciences
Artem OGANOV
(Skolkovo Institute of Science and Technology, Russia)
Computational materials discovery guided by artificial intelligence (download pdf)
Thierry LANGER
(University of Vienna, Austria)
A Computational Approach to Identify Potential Novel Inhibitors Against The Coronavirus SARS-CoV-2
Olivier TABOUREAU
(Paris Diderot University, France)
Network Sciences applied in pharmacology