MBG4059 Computational Methods in BioinformaticsBahçeşehir UniversityDegree Programs ARCHITECTUREGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
ARCHITECTURE
Bachelor TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF-LLL: Level 6

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
MBG4059 Computational Methods in Bioinformatics Spring 3 0 3 6
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction: English
Type of course: Non-Departmental Elective
Course Level: Bachelor’s Degree (First Cycle)
Mode of Delivery: Face to face
Course Coordinator : Dr. Öğr. Üyesi ELIZABETH HEMOND
Course Objectives: The goal of this course is to provide an understanding of the fundamental computational methods used in bioinformatics and the set of algorithms that have important applications both inside and outside of the bioinformatics field.

Learning Outcomes

The students who have succeeded in this course;
1. Recognize the fundamental models of computation useful in modeling nucleic acid and protein sequences.
2. Design and implement algorithms useful for analyzing various molecular biology data.
3. Discuss Genetic Algorithm and its applications in bioinformatics.
4. Discuss Greedy Algorithms and its applications in bioinformatics.
5. Discuss Gibbs sampling and its applications in bioinformatics.
6. Recognize Expectation Maximization and its applications in bioinformatics.
7. Recognize Hidden Markov models and its applications in bioinformatics.
8. Define Bayesian networks and its applications in bioinformatics.
9. Define graphs and its applications in bioinformatics.

Course Content

This course will provide a broad and thorough background in computational methods and algorithms that are widely used in bioinformatics applications. Various existing methods will be critically described and the strengths and limitations of each will be discussed.

Weekly Detailed Course Contents

Week Subject Related Preparation
1) A brief introduction to computational complexity and algorithm design techniques
2) Exact sequence search algorithms
3) Rabin-Karp algorithm, pattern matching, suffix trees
4) Elements of dynamic programming, Manhattan tourist problem, k-band algorithm
5) Approximate string matching, divide and conquer algorithms
6) Branch and bound search
7) Genetic Algorithm
8) Greedy Algorithms
9) Gibbs sampling
10) Expectation Maximization
11) Hidden Markov models
12) Bayesian networks
13) Graphs
14) Review

Sources

Course Notes / Textbooks: Haftalık ders notları iletilecektir.
Weekly course notes will be provided.
References: An Introduction to Bioinformatics Algorithms (Computational Molecular Biology), Neil Jones and Pavel Pevzner, MIT Press, 2004.

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Homework Assignments 2 % 10
Project 1 % 15
Midterms 1 % 25
Final 1 % 50
Total % 100
PERCENTAGE OF SEMESTER WORK % 35
PERCENTAGE OF FINAL WORK % 65
Total % 100

ECTS / Workload Table

Activities Number of Activities Duration (Hours) Workload
Course Hours 14 3 42
Study Hours Out of Class 14 6 84
Presentations / Seminar 5 4 20
Midterms 1 2 2
Final 1 2 2
Total Workload 150

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Using the theoretical/conceptual and practical knowledge acquired for architectural design, design activities and research.
2) Identifying, defining and effectively discussing aesthetic, functional and structural requirements for solving design problems using critical thinking methods.
3) Being aware of the diversity of social patterns and user needs, values and behavioral norms, which are important inputs in the formation of the built environment, at local, regional, national and international scales.
4) Gaining knowledge and skills about architectural design methods that are focused on people and society, sensitive to natural and built environment in the field of architecture.
5) Gaining skills to understand the relationship between architecture and other disciplines, to be able to cooperate, to develop comprehensive projects; to take responsibility in independent studies and group work.
6) Giving importance to the protection of natural and cultural values in the design of the built environment by being aware of the responsibilities in terms of human rights and social interests.
7) Giving importance to sustainability in the solution of design problems and the use of natural and artificial resources by considering the social, cultural and environmental issues of architecture.
8) Being able to convey and communicate all kinds of conceptual and practical thoughts related to the field of architecture by using written, verbal and visual media and information technologies.
9) Gaining the ability to understand and use technical information about building technology such as structural systems, building materials, building service systems, construction systems, life safety.
10) Being aware of legal and ethical responsibilities in design and application processes.