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.
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