COMPUTATIONAL BIOLOGY (3 SCU)

Learning Outcomes:

Upon successful completion of this course, students are expected to be able to develop an understanding of techniques and concepts used in Computational Biology; apply computational method for visualizing central tendency and distribution of dataset; apply computational method to approximate function with series; apply computational method to obtain approximation solutions and be able to apply computational methods to solve problems in a selected domain.

Topics:

Computational Biology is a part of natural science where quantitative approaches are used to discover and understand biological and medical phenomena. This course introduces computation method for computing approximate solution to solve problems using statistics. The material is presented using problem-oriented perspective with examples from the applied sciences. Topics to be covered include algorithms design, programming, probability theory, statistical data analysis, multivariate statistics, string algorithms, molecular evolution, Markov models, and machine learning.

Prerequisite(s): None