Course Details

COMPUTATIONAL BIOLOGY

Course Information

Semester	Course Unit Code	Course Unit Title	T+P+L	Credit	Number of ECTS Credits
5	MBG402	COMPUTATIONAL BIOLOGY	3+0+0	3	5

Course Details

Language of Instruction	English
Level of Course Unit	Bachelor's Degree
Department / Program	BIOENGINEERING
Type of Program	Formal Education
Type of Course Unit	Elective
Course Delivery Method	Face To Face
Objectives of the Course	1. To introduce basic understanding of theories and methodologies in computational biology. 2. To make student well equipped with the necessary skills to contextualize biomedical problems in terms of computational models/tools.
Course Content	This course will provide up-to-date theories and methodologies in computational biology with emphasis on structural and dynamical aspects of biological systems at atomic scale. The classes consist of both classroom lectures and computer labs. Upon completion of the course, the students should be able to perform various computational analyses on biological systems. The topics include Linux basics, molecular modelling and visualization, molecular dynamics, search altorighms, statistical analysis of biological data.
Course Methods and Techniques
Prerequisites and co-requisities	None
Course Coordinator	Instructor Dr. Ömer Faruk Bay omerfaruk.bay@agu.edu.tr
Name of Lecturers	None
Assistants	None
Work Placement(s)	No

Recommended or Required Reading

Resources	Thiele, I., Palsson, B. A protocol for generating a high-quality genome-scale metabolic reconstruction. Nat Protoc 5, 93–121 (2010). https://doi.org/10.1038/nprot.2009.203 https://cobrapy.readthedocs.io/en/latest/getting_started.html PalssonBØ.Systems Biology: Constraint-Based Reconstruction and Analysis. Cambridge University Press; 2015. Gu, C., Kim, G.B., Kim, W.J.et al.Current status and applications of genome-scale metabolic models.Genome Biol20, 121 (2019). https://doi.org/10.1186/s13059-019-1730-3

Course Category

Mathematics and Basic Sciences	%30
Engineering	%30
Engineering Design	%0
Social Sciences	%0
Education	%0
Science	%20
Health	%20
Field	%0

Planned Learning Activities and Teaching Methods

Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria

ECTS Allocated Based on Student Workload

Activities	Quantity	Duration	Total Work Load
Ev Ödevi	1	3	3
Sınıf İçi Aktivitesi	12	2	24
Teslim İçin Hazırlık	6	6	36
Soru Çözümü	12	2	24
Yazılım Deneyimi	10	2	20
Teslim	1	3	3
Yüz Yüze Ders	14	3	42
Final Sınavı	1	2	2
Total Work Load			Number of ECTS Credits 5 154

Course Learning Outcomes: Upon the successful completion of this course, students will be able to:

No	Learning Outcomes
1	Get acquainted with Linux operating system and how to write small scripts to run specific workflows
2	Learn available tools and their main functions in structural biology
3	Design a small project to apply the rules and information they have learnt
4	Have a look inside the biological molecules and their data representations and their visualizations

Weekly Detailed Course Contents

Week	Topics	Study Materials	Materials
1	Course Schedule and Login to Cocalc Platform.
2	Unix coding introduction.
3	Scripting with shell, data manipulation
4	Introduction to Python Programming
5	Functions, modules and object-oriented programming concepts
6	Introduction to data structures and data manipulation
7	Basic data visualisation and working with files
8	Fall Breaks
9	Active learning week
10	Data visualisation, working with files and data manipulation
11	Introduction to metabolic networks
12	Building a small metabolic network
13	Importing and analysing an existing metabolic model
14	Simulations and analysis
15	Recap

Recommended Optional Programme Components

Veri yok

Contribution of Learning Outcomes to Programme Outcomes

Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant

https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=71984&lang=en