| | 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.
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.
Language: English.
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.
Course starts: The course is given twice a year; each spring and each autumn. Each course is running over eight weeks.
Signing up: To sign up click here | |
