COURSE UNIT TITLE

: CELL BASED BIOSENSORS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
BYT 6007 CELL BASED BIOSENSORS ELECTIVE 2 0 0 7

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

PROFESSOR DOCTOR ŞENOL ALPAT

Offered to

Ph.D. in Biotechnology
Ph.D. in Biotechnology
BIOTECHNOLOGY

Course Objective

Teaching the fundamentals of cell based biosensor systems and also design and usage of these biosensor systems in the applications.

Learning Outcomes of the Course Unit

1   Gain an insight about the biosensors especially microbial ones.
2   To explore and compare the advantages/disadvantages of using methods.
3   Be able to make strategic plans to determine target analyte by microbial biosensors.
4   Be able to design and develop microorganism immobilization strategies for microbial biosensors.
5   Be able to understand and use electrochemical techniques used in the biosensor studies.
6   Be able to review, compare and interpret the results of the research.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Definition of cell-based biosensor 1.1. Comparison of cell-based and enzyme biosensors 1.2. Types of cell-based biosensor 1.3. Principles of cell-based biosensor functions
2 Simple construction and properties of the cell-based biosensor 2.1. Microbial Biosensors 2.2. Tissue Biosensors 2.3. Hybrid Biosensors
3 Features of Cell-based biosensors 3.1. Comparison of cell-based biosensors and enzyme enzyme biosensors
4 Mechanisms of cell-based biosensors
5 Causes of low selectivity on Cell-based biosensors 5.1. Common reasons for all types of biosensors 5.2. Only causes of cell-based biosensors
6 Methods for Improving selectivity of cell-based biosensors
7 Immobilization Methods of Cell-Based Biosensors
8 The use of cell-based clinical biosensors
9 The usage of cell-based biosensors for analysis of nutrient
10 The usage of cell-based biosensors for fermentation process controls
11 The usage of cell-based biosensors for environmental controls
12 Microbial biosensors and oxygen electrode-based microbial biosensors
13 Respiratory inhibition-based microbial biosensors The potentiometric and optical determination-based microbial biosensors
14 Examination of Analytical parameters of Microbial Biosensors

Recomended or Required Reading

Textbook(s): Qingjun Liu and Ping Wang, Cell-Based Biosensors: Principle and Applications (Engineering in Medicine & Biology), Artech House Publishers,USA, 2009.

Planned Learning Activities and Teaching Methods

1. Presentation
2. Question-answer technique
3. Homework

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 PRS PRESENTATION
4 FIN FINAL EXAM
5 FCG FINAL COURSE GRADE MTE* 0.30 + ASG * 0.20 + PRS * 0.10 + FIN * 0.40
6 RST RESIT
7 FCGR FINAL COURSE GRADE (RESIT) MTE* 0.30 + ASG * 0.20 + PRS * 0.10 + RST * 0.40


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Meaningful learning of the basic concepts given in presentations, association of concepts with each other, establishing the cause-result relationships and making comments by using the information available for problems and evaluating idea generation are carried out with mid-term and final exams, homework and presentations.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Dokuz Eylul University, Faculty of Buca Education, Department of Chemistry
senol.alpat@deu.edu.tr

Office Hours

Wednesday 13.30 - 15.30

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 2 28
Preparation for midterm exam 1 35 35
Preparation for final exam 1 40 40
Preparing Homework and Presentations 1 35 35
Preparations before/after weekly lectures 14 2 28
Midterm 1 2 2
Final 1 2 2
TOTAL WORKLOAD (hours) 170

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6
LO.1455543
LO.2445444
LO.3554345
LO.4454553
LO.5445544
LO.6554434