Applied Pharmaceutical Bioinformatics

About the course

This course teaches how to solve practical problems in pharmacology, life sciences, chemistry and bioinformatics through predictive modelling. The course is a continuation of the course Pharmaceutical Bioinformatics. The focus of this course is practical applications and continuation studies on how to use predictive statistical modelling methods, primarily directed to applications in the pharmaceutical field.

The course includes specifically:

• Introduction to statistical modelling in pharmaceutical bioinformatics.
• Continuation on QSAR and proteochemometrics and descriptors of proteins, peptides and organic molecules.
• Managed and unmanaged methods for statistical modelling/analysis, such as PCA, PLS, SVM and random forest.
• Cluster analysis; methods and tools.
• Software for statistical modellings, such as R and Bioclipse.
• Practical exercises on cluster analysis.
• Practical exercises on the use of PCA, PLS, SVM and random forest.
• Practical exercises in building QSAR and proteochemometrics models.

Outline for distance course: The course is given as web-lectures, through down-loadable documents for self-studies and teacher-supervised exercises online through a web-based teaching platform, and through exercises that student solves on his own computer using software that can be downloaded from the net. The course has no fixed times and the student can carry out their duties at any time of each study week. Communication between teacher and student is via educational platform and via email. Written examination is performed online at the end of the course.