Course Name: Computational Systems Biology

Course abstract

Every living cell is the result beautifully concerted interplay of metabolic, signalling and regulatory networks. Systems biology has heralded a systematic quantitative approach to study these complex networks, to understand, predict and manipulate biological systems. Systems biology has had a positive impact on metabolic engineering as well as the pharmaceutical industry. This course seeks to introduce key concepts of mathematical modelling, in the context of different types biological networks. The course will cover important concepts from network biology, modelling of dynamic systems and parameter estimation, as well as constraint-based metabolic modelling. Finally, we will also touch upon some of the cutting-edge topics in the field. The course has a significant hands-on component, emphasizing various software tools and computational methods for systems biology.


Course Instructor

Media Object

Karthik Raman

Dr. Karthik Raman is an Assistant Professor at the Department of Biotechnology, Indian Institute of Technology Madras since April 2011. Karthik’s research group at IIT Madras works on the development of algorithms and computational tools to understand, predict and manipulate complex biological networks. The key areas of research in his group encompass in silico metabolic engineering, biological networks and biological data analysis. Karthik also co-ordinates the Initiative for Biological Systems Engineering at IIT Madras and is a core member of the Robert Bosch Centre for Data Science and Artificial Intelligence (RBC-DSAI).
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Teaching Assistant(s)

Aarthi R

M. Tech Biotechnology

IITM

Malvika Sudhakar

M.E. Biotechnology

IITM

Gayathri S

I am currently doing PhD in Computational Systems Biology. I have an Mtech in Biopharmaceutical technology

IITM

 Course Duration : Jul-Oct 2018

  View Course

 Enrollment : 18-Apr-2018 to 30-Jul-2018

 Exam registration : 25-Jun-2018 to 18-Sep-2018

 Exam Date : 28-Oct-2018

Enrolled

909

Registered

29

Certificate Eligible

5

Certified Category Count

Gold

0

Silver

0

Elite

1

Successfully completed

4

Participation

12

Success

Elite

Gold





Legend

>=90 - Elite + Gold
60-89 - Elite
40-59 - Successfully Completed
<40 - No Certificate

Final Score Calculation Logic

  • Assignment Score = Average of best 8 out of 12 assignments.
  • Final Score(Score on Certificate)= 75% of Exam Score + 25% of Assignment Score.
Computational Systems Biology - Toppers list

VARUN ULLANAT 60%

R V COLLEGE OF ENGINEERING

Enrollment Statistics

Total Enrollment: 909

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Assignment Statistics




Assignment

Exam score

Final score

Score Distribution Graph - Legend

Assignment Score: Distribution of average scores garnered by students per assignment.
Exam Score : Distribution of the final exam score of students.
Final Score : Distribution of the combined score of assignments and final exam, based on the score logic.