- Course Code
- MBGE403
- Semester
- Seventh Term (Fall)
- Theory+Practice
- 2 + 2
- ECTS
- 5
| Course Type | Compulsory Course |
|---|
| Course Level | Bachelor's Degree |
|---|
| Year of Study | 4 |
|---|
| Semester | Seventh Term (Fall) |
|---|
| ECTS | 5 |
|---|
| Name of Lecturer(s) |
|
| Learning Outcomes |
At the end of this course, the students;
- Explain the scope of bioinformatics, biological databases, sequence alignment, and the basic principles and algorithms of similarity scanning in
databases.
- Perform and interpret regulatory region prediction analyses.
- Explain protein structure analysis and three dimensional structure prediction methods, including traditional approaches and AI-based tools.
- Understand gene expression analyses and interpret their results.
- Analyze relationships between genes or proteins using network biology.
- Learn genome mapping and comparison analyses and interpret the data.
|
| Mode of Delivery | Face to face |
|---|
| Prerequisites | No |
|---|
| Recommended Optional Programme Components | No |
|---|
| Course Description | Bioinformatics is the synthesis of the fields of mathematics, statistics, computer science, molecular biology and genetics in order to make sense, storage, visualization of biological data and make the most of this huge knowledge. Another definition is the science of compiling and analyzing complex biological data. |
|---|
| Course Contents |
| WEEK |
TOPICS |
|
1st Week |
Bioinformatics Definition and Scope |
|
2nd Week |
Biological Databases |
|
3rd Week |
Array Alignment |
|
4th Week |
Database Similarity Scans |
|
5th Week |
Basic Algorithms |
|
6th Week |
Gene Prediction |
|
7th Week |
Promoter and Regulatory Region Estimates |
|
8th Week |
Protein Structure Analysis and Artificial Intelligence-Based Three-Dimensional Structure Modeling |
|
9th Week |
Gene Expression Analysis |
|
10th Week |
Noncoding RNA Analysis |
|
11th Week |
Network Biology |
|
12th Week |
Genome Mapping and Comparison |
|
13th Week |
Phylogenetic Trees |
|
14th Week |
Genome Wide Applications |
|
| Recommended or Required Reading | Essential Bioinformatics, Jin Xiong. Cambridge University Press, 2006.
Bioinformatics For Biologists, Pavel Pevzner and Ron Shamir, Cambridge University Press, 2011.
Essentials of Bioinformatics, Volume I, Understanding Bioinformatics: Genes to Proteins, Editors: Shaik, N.A., Hakeem, K.R., Banaganapalli, B., Elango, R. Springer, 2019.
|
|---|
| Planned Learning Activities and Teaching Methods |
- Lecture
- Discussion
- Problem Solving
- Practice
|
|---|
| Assessment Methods and Criteria |
|
Quantity |
Percentage (%) |
| Mid-term |
1 |
35 |
| Assignment |
12 |
10 |
| Project |
1 |
15 |
| 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 |
2 |
2 |
| Preparation for Quiz |
|
|
|
| Individual or group work |
|
|
|
| Preparation for Final exam |
1 |
30 |
30 |
| Course hours |
14 |
2 |
28 |
| Preparation for Midterm exam |
1 |
20 |
20 |
| Laboratory (including preparation) |
|
|
|
| Final exam |
1 |
2 |
2 |
| Homework |
12 |
3 |
36 |
| Project |
1 |
8 |
8 |
| Performance Practice |
13 |
2 |
26 |
| Total Work Load | 152 |
| Total Work Load / 30 (h) | 5.06 |
| ECTS Credit of the Course | 5 |
|
| Language of Instruction | English |
|---|
| Work Placement(s) | No |
|---|
Programme Qualifications / Learning Outcomes
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LO1 |
LO2 |
LO3 |
LO4 |
LO5 |
LO6 |
| K1 |
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X |
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| K2 |
X |
X |
X |
X |
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| K3 |
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| K4 |
X |
X |
X |
X |
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| K5 |
X |
X |
X |
X |
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| K6 |
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X |
| K7 |
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X |
| K8 |
X |
X |
X |
X |
X |
X |
| K9 |
X |
X |
X |
X |
X |
X |
| K10 |
X |
X |
X |
X |
X |
X |
| K11 |
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X |
| K12 |
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X |
| K13 |
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