Modeling of complex biological systems 1000-719bMSB
We examine modern challenges in modeling and understanding complex biological systems through data. High-throughput molecular measurements have necessitated development and application of statistics and machine learning, giving rise to computational biology. Microarray and sequencing technologies enable us to quantify how complex systems are responding to and influenced by experimental and external conditions. It may lead to better understanding fundamental organizational principles and functionalities of molecules and cells. Lately, there have been interesting developments in single cell analyses, spatial genomics, imaging and others that involve higher resolutions, scales, and complexities.
In this course, we study exploratory data analysis, statistical learning, and neural networks that are specifically designed for such biological studies. Good understanding of statistics and programming are prerequisites. Students will program in R and Python, read primary literature weekly, and complete data analysis projects.
Type of course
Course coordinators
Course dedicated to a programme
Learning outcomes
At the end of the course, the students will:
- know major developments in computational biology and computational models for select biological systems,
- be able to analyze selected biological data underlying complex systems,
- be able to read and write scientific reports.
Assessment criteria
Participation, Homeworks, Project Report, Presentation.
Bibliography
An Introduction to Statistical Learning with Applications in R
by Gareth James, Daniela Witten, Trevor Hastie and Rob Tibshirani
The Elements of Statistical Learning: Data Mining, Inference, and Prediction.
by Trevor Hastie, Robert Tibshirani, Jerome Friedman
Deep Learning with Python
by Francois Chollet
Students will be asked to read selected original research and review papers.
Additional information
Information on level of this course, year of study and semester when the course unit is delivered, types and amount of class hours - can be found in course structure diagrams of apropriate study programmes. This course is related to the following study programmes:
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