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323103 VU Data science approaches for advancing drug discovery - MPS5 (2019S)

2.00 ECTS (1.00 SWS), SPL 32 - Pharmazie
Continuous assessment of course work


Language: English



Dear students!

We will meet on March 8, at 10 am in seminar room 2D 313 in order to discuss the content, structure and the dates for the VU.

Best regards,

Barbara Zdrazil and Lars Richter


Aims, contents and method of the course

Data science has become an important field in drug discovery and development nowadays. It offers a level of understanding of health, disease and treatment on a scale never before imagined, i.e. it can help researchers to find new drugs or re-use old drugs for new indications. In this lecture and seminar we will talk about existing data sources in the open domain, database schemes/structures, statistics, chemical data & cheminformatics approaches in drug discovery etc. We will further introduce you into the data management/manipulation tools Knime and R and give some more specialized seminars on the uses of KNIME and R in some of the expanding fields in data science (such as machine learning).

Drug discovery and development: from old paradigms to rational approaches:

- VO 1: Traditional drug discovery paradigms and rational drug discovery

Data-driven drug discovery: the holistic view:

- VO 2: Introduction to data-driven drug discovery and translational medicine
- VO 3: Statistics for data sciences: Distributions, correlations, hypothesis testing
- VO 4: Basics of statistical learning
- VO 5: Chemical Data: chemical structure representations, chemical descriptors
- VO 6: Cheminformatics approaches in drug discovery
- VO 7: Data sources, data integration: ChEMBL, OpenPHACTS
- VO 8: Database scheme/structures, Data querying

Predictive Modelling with R/KNIME (Practical part):

- UE 1: QSAR and machine learning in KNIME
- UE 2: Pathway/disease analysis in KNIME
- UE 3: Applied Cheminformatics in R
- UE 4: Data analyses and data visualization in R

Assessment and permitted materials

Written exam at the end of the VU;
Active contribution during the Practical part

Minimum requirements and assessment criteria

Written exam at the end of the VU;
Active contribution during the Practical part;
Presence at the 8 lectures and 4 practical units;
material for further reading will be pointed to in each individual lecture

Examination topics

Content of the lectures and the material for further reading

Reading list

Association in the course directory

Last modified: We 20.02.2019 09:48