LIFE SCIENCES AND COMPUTER ENGINEERING

BİL172

Course Code: BİL172
Semester: Second Term (Spring)
Theory+Practice: 2 + 1
ECTS: 4

Course Type

Compulsory Course

Course Level

Bachelor's Degree

Year of Study

Semester

Second Term (Spring)

ECTS

Name of Lecturer(s)

Assistant Professor Tolga Tarkan Ölmez

Learning Outcomes

At the end of this course, the students;

Be informed about basic life sciences.
understand the importance of computer engineering in this field.
learn modern computer applications in medicine
be able to disseminate the applicability of computer applications in life science.

Mode of Delivery

Face to face

Prerequisites

Recommended Optional Programme Components

None

Course Description

A survey of biological principles covered in a range from cell to genetic engineering. Integration of computer engineering and the life sciences, with a foundation in biology, chemistry and bioengineering methods. Introduction to biochemistry, biosystems, human metabolism and genetics. Modern evolutionary theory and animal/plant systems. Biological data and information flow. Application of computer engineering techniques to problems arising in biosciences.

Course Contents

WEEK	TOPICS
1^st Week	Intro to Life Sciences, Theory of Evolution, Chemical Fundamentals of Life
2^nd Week	Structure of DNA & RNA, Central Dogma, Transcription and Translation, Replication
3^rd Week	Structure of Proteins and Protein Folding, Photosynthesis and Respiration
4^th Week	Cell and Membranes, Organelles
5^th Week	Cell Division, Cell Cycles & Cancer
6^th Week	Introduction to Python 1
7^th Week	Programming in Python 1 (LAB 1)
8^th Week	Midterm
9^th Week	Bioinformatics, Sequence Alignment
10^th Week	Bioinformatics (LAB 2)
11^th Week	Introduction to Python 2
12^th Week	Programming in Python 2 (LAB 3)
13^th Week	Programming in Python 3 (LAB 4)
14^th Week	Ambient Assisted Living, Imaging Techniques, Virtual and Augmented
15^th Week	Reality Applications in Health (UN SDG and its Relation to Computer Science Applications in Health)

Recommended or Required Reading

1. Lehninger, A. L., Nelson, D. L. and Cox, M. M., Principles of Biochemistry, Worth Publishers, 1993.
2. J. D. Watson, Molecular Biology of the Gene, Second edition, Benjamin/Cummings, Menlo Park, 1987.
3. Genetic and Evolutionary Computation, Goldberg, David, Koza, John R. Springer, 2010.
4. Deitel&Deitel, Liperi and Wiedermann, Python How To Program, Prentice Hall, 2002

Planned Learning Activities and Teaching Methods

Lecture
Questions/Answers
Report Preparation
Practice

Assessment Methods and Criteria

	Quantity	Percentage (%)
Mid-term	1	30
Assignment	3	3
Quiz	4	12
Practice	4	12
Attendance	1	3
Total(%)		60
Contribution of In-term Studies to Overall Grade(%)		60
Contribution of Final Examination to Overall Grade(%)		40
Total(%)		100

ECTS Allocated Based on Student Workload

Activities	Quantity	Duration (Hour)	Total Workload (Hour)
Midterm exam	1	1.5	1.5
Preparation for Quiz	4	4	16
Individual or group work
Preparation for Final exam	1	40	40
Course hours	14	3	42
Preparation for Midterm exam	1	30	30
Laboratory (including preparation)	4	2	8
Final exam	1	1.5	1.5
Homework	3	1	3
Quiz	4	1	4
Total Work Load			146
Total Work Load / 30 (h)			4.86
ECTS Credit of the Course			4

Language of Instruction

English

Work Placement(s)

Programme Qualifications / Learning Outcomes

	LO1	LO2	LO3	LO4
K1	X
K2
K3
K4		X		X
K5
K6
K7
K8			X
K9
K10
K11	X	X	X	X