CE 405 | Course Introduction and Application Information

Course Name
Programming for Bioinformatics
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
CE 405
Fall/Spring
3
0
3
5

Prerequisites
None
Course Language
English
Course Type
Elective
Course Level
First Cycle
Course Coordinator
Course Lecturer(s) -
Assistant(s) -
Course Objectives Following the dissemination of the first results of the Human Genome Project in 2004 life sciences researchers have access to genome related information (DNA sequence, protein sequence etc.) that would revolutionize the clinical practice as we know it. However this information is kept in various databases and in various formats so that one has to employ special algorithms and tools for the analysis. This course aims to provide an introduction to the terminology, problems, algorithms and tools related to bioinformatics, which is one of the hottest research topics of computer science recently.
Learning Outcomes The students who succeeded in this course;
  • Be provided with the necessary basic biology knowledge to understand and define the bioinformatics problems.
  • Learn about the mostly utilized biological databases and bio-banks for the bioinformatics related research as well as the data formats.
  • Learn the thoratical foundations of the famous bioinformatics algorithms.
  • Become familiar with statistical analysis techniques for the analysis of genomic information.
  • Become famiiliar with programming languages used to solve bioinformatics problems and will gain hands-on programming skills with the provided assignments.
Course Content The course covers bioinformatics tools/software related with biological sequence (DNA, RNA, protein) analysis, molecular structure prediction, functional genomics, pharmacogenomics and proteomics, biological pathway analysis.

 



Course Category

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 Bioinformatics Lecturer notes
2 Basic biology information, Central dogma, DNA and RNA structure, gene, and proteins. Hairpins, loops, alpha helix and beta sheet. Bioinformatics for beginners, Genes, Genomes, Molecular Evolution, Databases and Analytical Tools. Supratim Choudhuri. Elservier, 2014 Chp. 1 N. C. Jones and P. A. Pevzner, An Introduction to Bioinformatics Algorithms, MIT press, 2004 Ch.3
3 Variables, data types, operators, return, if/else block. Importing modules, imported functions, declarations Bioinformatics Programming Using Python: Practical Programming for Biological Data, Mitchell L Model, O’Reilly, 2009. ISBN: 9781449382902. Chapter 1,2
4 Lists, dictionaries, tuples, interactive user input, comment blocks, for, while loops, break and continue, iterators, Time, sys, os modules, file reading and writing Bioinformatics Programming Using Python: Practical Programming for Biological Data, Mitchell L Model, O’Reilly, 2009. ISBN: 9781449382902. Chapter 3,4
5 Classes. Regular expressions and regex module. Biopython module, pairwise alignment. Accessing ncbi. FASTA and Genbank file formats Bioinformatics Programming Using Python: Practical Programming for Biological Data, Mitchell L Model, O’Reilly, 2009. ISBN: 9781449382902. Chapter 5
6 Ara sınav / Midterm
7 Finding k-mers in in DNA sequences Lecture Notes
8 Numpy, scipy and matplotlib modules. Matrices and sparse matrices. Lecture Notes
9 Needleman-Wunsch, Waterman-Smith-Bayer, and other sequence alignment algorithms Lecture Notes
10 Gotoh alignment and affine gap cost algorithm Lecture Notes
11 K-means clustering and Hierarchical clustering Python for Bioinformatics, Sebastian Bass, CRC Press, 2016. ISBN: 9781584889304. Chapter 10
12 Ara Sınav / Midterm II
13 Analysis of next generation data Lecture Notes
14 RNA folding and motif analysis Bioinformatics for beginners, Genes, Genomes, Molecular Evolution, Databases and Analytical Tools. Supratim Choudhuri. Elservier, 2014 Chapter 7
15 Multi sequence alignment and phylogenetic tree construction Python for Bioinformatics, Sebastian Bass, CRC Press, 2016. ISBN: 9781584889304. Chapter 23
16 Review of the Semester  

 

Course Textbooks

Suggested but not required text: (1) Bioinformatics for beginners, Genes, Genomes, Molecular Evolution, Databases and Analytical Tools. Supratim Choudhuri. Elservier, 2014 (2) N. C. Jones and P. A. Pevzner, An Introduction to Bioinformatics Algorithms, MIT press, 2004 (3) J. Xiong, Essential Bioinformatics, Cambridge University Press, 2006. (4) S. Bassi, Python for Bioinformatics, CRC Press , 2010.

References Related Research Papers

 

EVALUATION SYSTEM

Semester Requirements Number Percentage
Participation
1
10
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Homework / Assignments
4
10
Presentation / Jury
Project
1
30
Seminar / Workshop
Portfolios
Midterms / Oral Exams
2
30
Final / Oral Exam
1
20
Total

Contribution of Semester Work to Final Grade
8
80
Contribution of Final Work to Final Grade
1
20
Total

ECTS / WORKLOAD TABLE

Activities Number Duration (Hours) Workload
Course Hours
Including exam week: 16 x total hours
16
3
48
Laboratory / Application Hours
Including exam week: 16 x total hours
16
Study Hours Out of Class
16
1
Field Work
Quizzes / Studio Critiques
Homework / Assignments
4
2
Presentation / Jury
Project
1
25
Seminar / Workshop
Portfolios
Midterms / Oral Exams
2
17
Final / Oral Exam
1
19
    Total
150

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Qualifications / Outcomes
* Level of Contribution
1
2
3
4
5
1

To have sufficient background in Mathematics, Basic sciences and Biomedical Engineering areas and the skill to use this theoretical and practical background in the problems of the Biomedical Engineering.

2

To identify, formulate and solve Biomedical Engineering-related problems by using state-of-the-art methods, techniques and equipment; to select and apply appropriate analysis and modeling methods for this purpose.

3

To analyze a complex system, system components or process, and to design with realistic limitations to meet the requirements using modern design techniques; to apply modern design techniques for this purpose.

4

To choose and use the required modern techniques and tools for analysis and solution of complex problems in Biomedical Engineering applications; to skillfully use information technologies.

5

To design and do simulation and/or experiment, collect and analyze data and interpret results for studying complex engineering problems or research topics of the discipline. 

6

To efficiently participate in intradisciplinary and multidisciplinary teams; to work independently.

7

To communicate both in oral and written form in Turkish; to have knowledge of at least one foreign language; to have the skill to write and understand reports, prepare design and production reports, present, give and receive clear instructions.

8

To recognize the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.

9

To behave ethically, to be aware of professional and ethical responsibilities; to have knowledge about the standards in Biomedical Engineering applications.

10

To have information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development.

11

To have knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of Biomedical Engineering solutions.

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest