Ders Planı

Lesson Information

Course Credit
Course ECTS Credit
Teaching Language of Instruction	Türkçe
Level of Course	Bachelor's Degree, TYYÇ: Level 6, EQF-LLL: Level 6, QF-EHEA: First Cycle
Type of Course
Mode of Delivery	Face-to-face
Does the course require compulsory or optional work experience?
Course Coordinator
Instructor (s)
Course Assistant

Purpose and Content

The aim of the course	To gain the ability to understand the importance of bioinformatics approaches for solving problems in modern biology research, to apply software technologies, to evaluate and interpret the results.
Course Content	Bioinformatics is a rapidly developing field that integrates molecular biology, biophysics, statistics and computer science. The course provides an overview of bioinformatics that also uses information tools to solve biological problems. Topics: database search, sequence alignment, gene prediction, RNA and protein structure prediction, creation of phylogenetic trees, comparative and functional genomics.

The aim of the course

To gain the ability to understand the importance of bioinformatics approaches for solving problems in modern biology research, to apply software technologies, to evaluate and interpret the results.

Course Content

Bioinformatics is a rapidly developing field that integrates molecular biology, biophysics, statistics and computer science. The course provides an overview of bioinformatics that also uses information tools to solve biological problems. Topics: database search, sequence alignment, gene prediction, RNA and protein structure prediction, creation of phylogenetic trees, comparative and functional genomics.

Learning Outcomes

Adequate knowledge in mathematics, physical sciences and the engineering subjects of individual branches; the ability to implement theoretical and practical knowledge in the respective areas to modeling and solving engineering problems.
Ability to identify, define, formulate and solve complex engineering problems; ability to select and implement the appropriate analysis and modeling methods in this respect.
Ability to design and conduct experiments for analyzing engineering problems or research subjects specific to the discipline, to collect data, to analyze and interpret the results.
Ability to use, choose and develop modern techniques and means required for engineering applications; ability to use information technologies effectively.
An ability to design and conduct experiments, collect data, analyze and interpret results for the study of complex engineering problems or discipline-specific research topics.
Awareness of the necessity of lifelong learning; ability to reach information, follow the latest developments in science and technology; ability to ensure self-renewal perpetually.
Acting in line with ethical principles, sense of professional and ethical responsibility; knowledge on the standards of engineering applications.
Ability to work effectively in interdisciplinary and multi-disciplinary teams and individual works.
Information about the effects of engineering applications on health, environment and safety in terms of universal and social aspects and information about the problems of the era; awareness about the legal results of engineering solutions.
Ability to communicate efficiently both in oral and written ways in Turkish; knowledge of at least one foreign language; ability to effectively prepare reports and understand written reports, prepare design and production reports, effective presentation, giving and receiving clear and understandable instructions.
Knowledge of business practices such as project management, risk management and change management; awareness of entrepreneurship, innovation; information about sustainable development.

Weekly Course Subjects

1	Introduction. Definition of bioinformatics, importance of bioinformatics.
2	An overview of molecular biology. Cells, chromosomes, DNA, RNA, Amino acids, Proteins, Genome, Transcriptome, Proteome.
3	Python / Perl as software tool, installation and programming.
4	Alignment of the two sequences. The relationships between sequences
5	Alignment methods (Visual, Brute Force, Dynamic programming, Word-based). Alignment methods (Visual, Brute Force, Dynamic programming, Word based).
6	Dot plot, Global alignment, Local alignment.
7	Score matrices, measure of alignment.
8	Midterm
9	Database systems, web technologies and R
10	Prediction of protein structure and maintenance, comparative genomics
11	Multiple sequence alignment. Spherical multiple sequence alignment, progressive spherical alignment, iterative methods. Global multiple alignment based on locally preserved patterns
12	Local multiple alignment, profile analysis, block analysis. Pattern search or statistical methods.
13	Phlogenetic tree structure, character-based phylogenies. Analysis of DNA microarrays
14	Final

Resources

Introduction to Bioinformatics. Arthur M. Lesk

Python for Bioinformatics , Jason Kinser

Beginning Perl for Bioinformatics. James Tisdall

Fundamental Concepts of Bioinformatics. Dan E. Krane, Michael L. Raymer

Bioinformatics: Sequence and Genome Analysis. David W. Mount

Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins. Andreas D. Baxevanis

CLASS 1

CLASS 2

CLASS 3

CLASS 4

Lesson Information

Purpose and Content

Learning Outcomes

Weekly Course Subjects

Resources

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