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Sathyabama Institute of Science and Technology B.Tech - BioTechnology SBMA4002 Modelling of Physiological Systems Syllabus

SATHYABAMA INSTITUTE OF SCIENCE AND TECHNOLOGY SCHOOL OF MECHANICAL ENGINEERING

SBMA4002 MODELLING OF PHYSIOLOGICAL SYSTEMS
L T P Credits Total Marks
3 0 0 3 100

UNIT 1 PHYSIOLOGICAL COMPLEXITY AND THE NEED FOR MODELS 9 Hrs.
Introduction - Complexity - Feedback - Negative Feedback - Positive Feedback - Inherent Feedback - Combining Negative
and Positive Feedback - Derivative and Integral Feedback - Effects of Feedback on the Complexity of System Dynamics
Control in Physiological Systems - General Features - Enzymes - Hormones - Hierarchy - Redundancy - Function and
Behavior and their Measurement.

UNIT 2 MODELS AND THE MODELING PROCESS 9 Hrs.
Introduction - The Purpose of Modeling - The Modeling Process - Model Formulation - Model Identification - Model
Validation - Model Simulation - The Basis of Data Modeling - Approaches to Data Modeling - Modeling a Single Variable
Occurring Spontaneously - Temperature 38 - Urine Potassium - Gastro-intestinal Rhythms - Hormonal Time Series -
Modeling a Single Variable in Response to a Perturbation - Glucose Home Monitoring Data - Response to Drug Therapy

UNIT 3 MODELING THE SYSTEM 9 Hrs.
Static Models - Linear Modeling - The Wind kessel Circulatory Model - Elimination from a Single Compartment - Gas
Exchange - The Dynamics of a Swinging Limb - A Model of Glucose Regulation - Distributed Modeling - Blood-tissue
Exchange - Hepatic Removal of Materials - Renal Medulla - Nonlinear Modeling - Baroreceptors - Central Nervous Control
of Heart Rate - Compartmental Modeling - Insulin Receptor Regulation - Insulin Action Modeling - Thyroid Hormone
Regulation - Modeling the Chemical Control of Breathing Time-varying Modeling

UNIT 4 NON- LINEAR DYNAMICS 9 Hrs.
Gene lets and synthetic biochemical circuits – Transcriptional oscillators – Synthetic biochemical dynamic circuits – Non –
linear dynamics – The brain and the heart Electrophysiology in human cortex – Multiscale network organization – Neuronal
oscillations – Cardiac electrophysiology/

UNIT 5 CASE STUDIES 9 Hrs.
A Sum of Exponentials Tracer Disappearance Model - Blood Flow Modeling - Cerebral Glucose Modeling - Models of the
Ligand-Receptor System - A Simulation Model of the Glucose-Insulin System - Model Formulation - A Model of Insulin
Control - Bayesian Estimation
Max. 45 Hrs
.
COURSE OUTCOMES
On completion of the course, student will be able to
CO1 - Understands the living system from a holistic perspective.
CO2 - Remembers the electrophysiological studies in clinical studies
CO3 - Appreciate the complexity in living systems and understand the need to model.
CO4 - Interprets the process of systematic modeling.
CO5 - Analyse the purpose behind and logic and applications of the existing models.
CO6 - Compares the Model in new cases and hypothetical scenarios.

TEXT / REFERENCE BOOKS
1 Cobelli, Claudio, and Ewart R. Carson. Introduction to Modeling in Physiology and Medicine, Elsevier Science &
Technology, 2008.
2 Multiscale Analysis and Nonlinear Dynamics: From Genes to the Brain, edited by Preseason, Misha Meyer, John Wiley
& Sons, Incorporated, 2013.

END SEMESTER EXAMINATION QUESTION PAPER PATTERN
Max. Marks: 100 Exam Duration: 3 Hrs.
PART A: 10 Questions of 2 marks each - No choice 20 Marks
PART B: 2 Questions from each unit of internal choice; each carrying 16 marks 80 Marks