Special Topics in BIO: Systems and Integrative Biology (BIO 58005)

2020 Fall
Faculty of Engineering and Natural Sciences
Christopher Mayack cmayack@sabanciuniv.edu,
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Doctoral, Master
Formal lecture,Interactive lecture,Workshop
Learner centered,Discussion based learning,Project based learning,Case Study
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Students will take part in the following sections of this course 1)Literature survey to gain more background knowledge: this aims to introduce the students from a range of backgrounds in the biological and physical sciences, mathematics, computer science, and engineering to the basic concepts and theories behind Integrative and Systems Biology. 2)An introduction to integrative data collection and analysis: this section will cover experimental design and analysis and then use actual datasets previously collected from integrative biology experiments to explore the various analytical tools for integrating `omics? approaches (transcriptomics, proteomics and and metabolomics), to arrive at testing a hypothesis. This section will emphasize the pros and cons of dealing with large amounts of data. 3)Systems engineering and mathematical modelling approaches: this section of the course will involve computer -based network modelling and a systems engineering framework required for studying a multifactorial complex problem. Students will embody tools of mathematics, informatics and statistics. 4)Wetlab experimental tools used in integrative biology: the molecular and cellular tools commonly used to integrate across behavioral, physiological, and neurological levels will be introduced. Students will have to devise their own experimental design to test a novel hypothesis generated on their own that will enhance their current thesis work. This section will include possible practical work if it is deemed feasible and results obtained will be presented orally by the end of the course. In addition to the above sections which incorporate lectures and practical classes, students will be required to carry out an independent research project of their own, applying what they have learned in class.


Students will learn how to define and connect concepts across different levels of
biological organization. Students will be able to describe and analyze systems biology
datasets. In general, they should be able employ complex statistical and computational
tools to analyze integrative biological datasets.
By the end of the course students should be able to:
1. demonstrate an understanding of the biological, computational, engineering,
mathematical, and physical sciences relevant to integrative biology
2. critically analyze literature and contemporary topics in integrative and systems
biology, and present such analyses in written and oral formats
3. adopt a model-building approach to analyze large-scale experimental data
4. explain the importance and impact of topics in integrative biology to individuals from
other disciplines in the natural sciences and engineering as well as the general public
5. demonstrate cutting-edge experimental techniques that are currently being used in
integrative and systems biology.


  Percentage (%)
Midterm 28
Assignment 11
Term-Paper 13
Case Study 13
Participation 7
Individual Project 28



Computational Systems Biology by Andres Kriete and Roland Eils


Current primary literature in the field of systems biology