MBG1002 Introduction to BioinformaticsBahçeşehir UniversityDegree Programs ELECTRICAL AND ELECTRONICS ENGINEERINGGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
ELECTRICAL AND ELECTRONICS ENGINEERING
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
MBG1002 Introduction to Bioinformatics Fall 3 0 3 5
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 Lecturer(s): Prof. Dr. SÜREYYA AKYÜZ
Dr. Öğr. Üyesi SERKAN AYVAZ
Recommended Optional Program Components: There is none.
Course Objectives: This course aims to prepare the students to work in the interdisciplinary area, bioinformatics that marry the advances in high-performance computing with the exploiting information resources of the human genome and related data.

Learning Outcomes

The students who have succeeded in this course;
1. Recognize the working in interdisciplinary teams of biologists, biochemists, medical researchers, geneticists, and computer engineers.
2. Perform sophisticated searches over enormous databases, and to interpret results.
3. Perform genomic comparisons, display genes and large genomic regions in Genome Browsers.
4. Recognize the basic bioinformatics problems and their solutions, including: fragment assembly, gene finding, protein folding and microarray studies.
5. Anayze the results in probabilistic terms using statistical significance.
6. Recognize the sequencing techniques, inherent computational problems, possible solutions.
7. Define Markov Model building and its usage for gene prediction.
8. Define computational methods for analysis of microarray data, and discuss the interpretations of gene expression from this data.
9. Discuss ethical, legal, and social issues associated with the Human Genome Project and its outcomes.

Course Content

Bioinformatics is a rapidly growing field that integrates molecular biology, statistics, and computer science. This course is devoted to the mathematical models and computer algorithms of DNA and protein sequence analysis. In this course, the students will learn many of the popular tools for performing bioinformatics analysis and you will be introduced to the thinking that drives these algorithms. Various existing bioinformatics methods will be critically described and the strengths and limitations of each will be discussed.

Weekly Detailed Course Contents

Week Subject Related Preparation
1) Introduction: Probability and statistics in a nut shell.
2) Analysis of nucleic acid and protein sequences.
3) Molecular Biology Databases on the Web.
4) Bioinformatics softwares on the internet
5) How the Genome is Studied, Maps and Sequences, The Human Genome Project
6) Sequencing: Next Gen, Exome, Shotgun
7) Fragment Assembly Problem; Sequence Alignment Models: Shortest Common Superstring, Reconstruction, Multicontig, Graph Model
8) Restriction mapping: a) Double Digest Problem, b) Partial Digest Problem
9) Computational Gene Hunting, Gene finding methods; sequence patterns, Hidden Markov Models.
10) Bioinformatics approaches to gene expression
11) Protein folding problem
12) Genome Rearrangements
13) Suffix trees I
14) Suffix trees II

Sources

Course Notes / Textbooks: Biyoinformatik ders notları haftalık olarak verilecektir.
Course material will be supplied weekly.
References: 1) Pevsner J., Bioinformatics and Functional Genomics, Wiley-Liss, 2009
2) Mount D.W., Bioinformatics: Sequence and Genome Analysis (2nd edition), Cold Spring Harbor Laboratory Press, 2004
3) Krane D.E., Raymer M.L., Fundamental Concepts of Bioinformatics, Benjamin Cummings, 2003
4) Setubal C., Meidanis J., Introduction to Computational Molecular Biology, PWS Publishing, 1997"

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Homework Assignments 2 % 15
Project 1 % 20
Midterms 1 % 25
Final 1 % 40
Total % 100
PERCENTAGE OF SEMESTER WORK % 40
PERCENTAGE OF FINAL WORK % 60
Total % 100

ECTS / Workload Table

Activities Number of Activities Duration (Hours) Workload
Course Hours 14 3 42
Study Hours Out of Class 14 5 70
Project 1 10 10
Midterms 1 2 2
Final 1 2 2
Total Workload 126

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) Adequate knowledge in mathematics, science and electric-electronic engineering subjects; ability to use theoretical and applied information in these areas to model and solve engineering problems.
2) Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose.
3) Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose. (Realistic constraints and conditions may include factors such as economic and environmental issues, sustainability, manufacturability, ethics, health, safety issues, and social and political issues, according to the nature of the design.)
4) Ability to devise, select, and use modern techniques and tools needed for electrical-electronic engineering practice; ability to employ information technologies effectively.
5) Ability to design and conduct experiments, gather data, analyze and interpret results for investigating engineering problems.
6) Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
7) Ability to communicate effectively in English and Turkish (if he/she is a Turkish citizen), both orally and in writing.
8) Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
9) Awareness of professional and ethical responsibility.
10) Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development.
11) Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of engineering solutions.