Applied Pharmaceutical Bioinformatics
The course is a continuation of the course “Pharmaceutical Bioinformatics” with the purpose to learn how to practically apply the predictive modeling methods introduced there.
This continuation-course provides a deepened understanding of statistical modeling methods for applications in the pharmaceutical field, life sciences and pharmacology, focusing on how to practically solve problems using different informatics methods.
The course covers:
- Introduction to statistical modeling in pharmaceutical bioinformatics, with an in depth review of QSAR and proteochemometrics.
- Calculation of different kinds of descriptors for datasets of organic molecules, peptides and proteins using Bioclipse and R.
- Introduction of software for statistical modeling, including R, LIBSVM, Weka and Bioclipse.
- Hands-on exercises on supervised and unsupervised methods for statistical modeling/analysis, including use of PCA, PLS , SVM, SOM, random forest and k -NN with Weka and Bioclipse Modeling.
- Hands-on exercises in building of QSAR and proteochemometrics models with R: obtaining of dataset and pre-processing, model building, predictions and interpretations.
- Hands-on exercises of cluster analysis with R.
- Hands-on exercises on statistical molecular design for optimization of lead compounds.
Eligibility: At least 150 ECTS credits in chemistry, biology, biochemistry, pharmacy, medicine or dentistry. It is also required that you have passed the main course on Pharmaceutical Bioinformatic, 7.5 ECTS credits .
Teaching: On the internet via a web-based teaching platform.
Examination: Written examination at the end of the course and approved compulsory modules.
Credits: 5 ECTS credits is given on passing the course.
Course literature: Provided online with the course and freely available computer programs that can be downloaded from the web and installed on your own computer.
Next course start: The course is given twice a year, each course running over eight weeks. The next course starts November 7, 2016.
Signing up: To sign up click here . (Important: When you sign up, please state in the message field that you sign up for the course Applied Pharmaceutical Bioinformatics).