FACULTY OF ENGINEERING
Department of Genetics and Bioengineering
BME 311 | Course Introduction and Application Information
| Course Name |
Computational Bioinformatics
|
|
Code
|
Semester
|
Theory
(hour/week) |
Application/Lab
(hour/week) |
Local Credits
|
ECTS
|
|
BME 311
|
Fall/Spring
|
2
|
2
|
3
|
6
|
| Prerequisites |
|
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| Course Language |
English
|
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| Course Type |
Elective
|
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| Course Level |
First Cycle
|
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| Mode of Delivery | - | |||||||||
| Teaching Methods and Techniques of the Course | DiscussionGroup WorkProblem SolvingApplication: Experiment / Laboratory / WorkshopLecture / Presentation | |||||||||
| Course Coordinator | ||||||||||
| Course Lecturer(s) | ||||||||||
| Assistant(s) | ||||||||||
| Course Objectives | This course aims to teach the algorithms used for analysis of biological data and file formats that these biological data are stored in online databases. |
| Learning Outcomes |
The students who succeeded in this course;
|
| Course Description | The course covers algorithms used for sequence alignment, motif discovery in DNA and protein sequences, clustering protein networks, protein complex discovery using interaction networks, phylogenetic tree construction and next generation sequencing. |
|
|
Core Courses | |
| Major Area Courses | ||
| Supportive Courses | ||
| Media and Management Skills Courses | ||
| Transferable Skill Courses |
WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES
| Week | Subjects | Related Preparation |
| 1 | Introduction to Python | Chapter 2, Bioinformatics for beginners, Genes, Genomes, Molecular Evolution, Databases and Analytical Tools. Supratim Choudhuri. Elservier, 2014, ISBN: 9780124105102 |
| 2 | Variables, if/else blocks, importing modules | Chapter 1, Bioinformatics for beginners, Genes, Genomes, Molecular Evolution, Databases and Analytical Tools. Supratim Choudhuri. Elservier, 2014, ISBN: 9780124105102 Chapter 3, N. C. Jones and P. A. Pevzner, An Introduction to Bioinformatics Algorithms, MIT press, 2004, ISBN: 9780124105102 |
| 3 | Functions and modules | Chapter 5, Bioinformatics for beginners, Genes, Genomes, Molecular Evolution, Databases and Analytical Tools. Supratim Choudhuri. Elservier, 2014, ISBN: 9780124105102 |
| 4 | Collections and comprehensions | Chapter 5, N. C. Jones and P. A. Pevzner, An Introduction to Bioinformatics Algorithms, MIT press, 2004, ISBN: 9780262101066 |
| 5 | Reading from FASTA and Genbank files | Chapter 7, Bioinformatics for beginners, Genes, Genomes, Molecular Evolution, Databases and Analytical Tools. Supratim Choudhuri. Elservier, 2014, ISBN: 9780124105102 |
| 6 | Using K-mer to find repeats in DNA sequences. | Chapter 7, Bioinformatics for beginners, Genes, Genomes, Molecular Evolution, Databases and Analytical Tools. Supratim Choudhuri. Elservier, 2014, ISBN: 9780124105102 |
| 7 | Using RegEx to find motifs | Chapter 4, N. C. Jones and P. A. Pevzner, An Introduction to Bioinformatics Algorithms, MIT press, 2004, ISBN: 9780262101066 |
| 8 | Clustering biological data using K-means | Chapter 10, N. C. Jones and P. A. Pevzner, An Introduction to Bioinformatics Algorithms, MIT press, 2004, ISBN: 9780262101066 |
| 9 | Protein complex discovery in interaction networks. | Chapter 8, Bioinformatics for beginners, Genes, Genomes, Molecular Evolution, Databases and Analytical Tools. Supratim Choudhuri. Elservier, 2014, ISBN: 9780124105102 |
| 10 | Sequence alignment using Biopython | Chapter 6, Bioinformatics for beginners, Genes, Genomes, Molecular Evolution, Databases and Analytical Tools. Supratim Choudhuri. Elservier, 2014, ISBN: 9780124105102 |
| 11 | Affine gap cost in sequence alignment. | Chapter 6, N. C. Jones and P. A. Pevzner, An Introduction to Bioinformatics Algorithms, MIT press, 2004, ISBN: 9780262101066 |
| 12 | Midterm I | |
| 13 | Algorithms used in next generation sequencing analysis and multiple sequence alignment. | Chapter 7, Bioinformatics for beginners, Genes, Genomes, Molecular Evolution, Databases and Analytical Tools. Supratim Choudhuri. Elservier, 2014, ISBN: 9780124105102 |
| 14 | UPMGA and Neighbor-joining tree construction algorithms. | Chapter 10, N. C. Jones and P. A. Pevzner, An Introduction to Bioinformatics Algorithms, MIT press, 2004, ISBN: 9780262101066 |
| 15 | Review of the Semester | |
| 16 | Final Exam |
| Course Notes/Textbooks |
|
| Suggested Readings/Materials |
EVALUATION SYSTEM
| Semester Activities | Number | Weigthing |
| Participation | ||
| Laboratory / Application | ||
| Field Work | ||
| Quizzes / Studio Critiques | ||
| Portfolio | ||
| Homework / Assignments |
1
|
10
|
| Presentation / Jury | ||
| Project |
1
|
20
|
| Seminar / Workshop | ||
| Oral Exams | ||
| Midterm |
1
|
30
|
| Final Exam |
1
|
40
|
| Total |
| Weighting of Semester Activities on the Final Grade |
4
|
60
|
| Weighting of End-of-Semester Activities on the Final Grade |
1
|
40
|
| Total |
ECTS / WORKLOAD TABLE
| Semester Activities | Number | Duration (Hours) | Workload |
|---|---|---|---|
| Theoretical Course Hours (Including exam week: 16 x total hours) |
16
|
2
|
32
|
| Laboratory / Application Hours (Including exam week: '.16.' x total hours) |
16
|
2
|
32
|
| Study Hours Out of Class |
14
|
3
|
42
|
| Field Work |
0
|
||
| Quizzes / Studio Critiques |
0
|
||
| Portfolio |
0
|
||
| Homework / Assignments |
1
|
14
|
14
|
| Presentation / Jury |
0
|
||
| Project |
1
|
16
|
16
|
| Seminar / Workshop |
0
|
||
| Oral Exam |
0
|
||
| Midterms |
1
|
20
|
20
|
| Final Exam |
1
|
24
|
24
|
| Total |
180
|
COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP
|
#
|
Program Competencies/Outcomes |
* Contribution Level
|
||||
|
1
|
2
|
3
|
4
|
5
|
||
| 1 | To have adequate knowledge in Mathematics, Science and Genetics and Bioengineering; to be able to use theoretical and applied information in these areas on complex engineering problems. |
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| 2 | To be able to identify, define, formulate, and solve complex Genetics and Bioengineering problems; to be able to select and apply proper analysis and modeling methods for this purpose. |
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| 3 | To be able to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the requirements; to be able to apply modern design methods for this purpose. |
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| 4 | To be able to devise, select, and use modern techniques and tools needed for analysis and solution of complex problems in Genetics and Bioengineering applications; to be able to use information technologies effectively. |
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| 5 | To be able to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or Genetics and Bioengineering research topics. |
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| 6 | To be able to work efficiently in Genetics and Bioengineering disciplinary and multi-disciplinary teams; to be able to work individually. |
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| 7 | To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively, to be able to give and receive clear and comprehensible instructions. |
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| 8 | To have knowledge about global and social impact of Genetics and Bioengineering practices on health, environment, and safety; to have knowledge about contemporary issues as they pertain to engineering; to be aware of the legal ramifications of Genetics and Bioengineering solutions. |
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| 9 | To be aware of ethical behavior, professional and ethical responsibility; to have knowledge about standards utilized in Genetics and Bioengineering applications. |
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| 10 | To have knowledge about industrial practices such as project management, risk management, and change management; to have awareness of entrepreneurship and innovation; to have knowledge about sustainable development. |
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| 11 | To be able to collect data in the area of Genetics and Bioengineering, and to be able to communicate with colleagues in a foreign language. |
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| 12 | To be able to speak a second foreign language at a medium level of fluency efficiently. |
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| 13 | To recognize the need for lifelong learning; to be able to access information, to be able to stay current with developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Genetics and Bioengineering. |
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*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest
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