Selected Topics in Computational Drug Discovery and Pharmaceutical Bioinformatics
This course can be considered as a project (case study) with a major practical application for a topic of the previously described courses. Furthermore, topics are not taught in the curriculum are also welcome, such as fragment-based approaches, vaccine design, antibody design, protein design, deep docking, big dataset screening…etc. Any topic can also be considered based on mutual agreement with the instructors and the candidates. At the end of this course, it is highly encouraged to formulate the outcomes as a publication.
In this course, different types of supervised and unsupervised machine learning methods such as PCA, HCA, and ANN, that were exploited in drug and nanoparticle formulation and delivery aspects will be demonstrated and discussed.