NUTRITION AND DIETETICS (MASTER) (WITHOUT THESIS)
Master TR-NQF-HE: Level 7 QF-EHEA: Second Cycle EQF-LLL: Level 7

Ders Genel Tanıtım Bilgileri

Course Code: 3000002009
Ders İsmi: Bioinformatic
Ders Yarıyılı: Fall
Ders Kredileri:
Theoretical Practical Credit ECTS
3 0 3 6
Language of instruction:
Ders Koşulu:
Ders İş Deneyimini Gerektiriyor mu?: No
Type of course: Anabilim Dalı/Lisansüstü Seçmeli
Course Level:
Master TR-NQF-HE:7. Master`s Degree QF-EHEA:Second Cycle EQF-LLL:7. Master`s Degree
Mode of Delivery: Face to face
Course Coordinator : Dr.Öğr.Üyesi Banu TAKTAK KARACA
Course Lecturer(s):
Course Assistants:

Dersin Amaç ve İçeriği

Course Objectives: Learn about bioinformatics which is a multidisciplinary field at the cross section of molecular biology and computer science. Become knowledgeable about the storage, retrieval, sharing and use of biological data, information, and various tools. Gain familiarity with algorithms used in bioinformatics.
Course Content: Overview of bioinformatics, Access to Sequence Data and Literature Information, Pairwise Sequence Alignment, Basic Global and Local Alignment Search Tool (BLAST), Advanced BLAST Searching, Multiple Sequence Alignment, PSI-BLAST and Hidden Markov Model (HMM), Phylogeny.

Learning Outcomes

The students who have succeeded in this course;
Learning Outcomes
1 - Knowledge
Theoretical - Conceptual
1) Students will learn the usage of bioinformatics.
2 - Skills
Cognitive - Practical
3 - Competences
Communication and Social Competence
Learning Competence
1) Students will understand the collection and processing data.
2) Students will be able to use biological databases.
Field Specific Competence
Competence to Work Independently and Take Responsibility

Ders Akış Planı

Week Subject Related Preparation
1) Introduction to computational biology Textbook
2) Protein sequence analysis Textbook
3) Nucleic acid sequence analysis Textbook
4) Phylogenetic analysis Textbook
5) Binding motifs, Hidden Markov models, 3D structure estimations and modeling Textbook
6) An overvıew of emerging fields; expression analysis, digital image processing, modeling of the cellular signalling pathways Textbook
7) Biomedical information technology; design of the modern information systems related with the biological and medical data Textbook
8) Ara sınav / Midterm
9) Data exchange protocols and computer modeling architecture Textbook
10) Computational neutobiology;; introduction to the nerve system, physiology of the nerve and muscle cells, delivery of signal through synapses and the perception at muscle cells Textbook
11) Advanced biological modeling: The arrangement and analysis of real mathematic models describing biological and engineering processes Textbook
12) Computer algebra systems
13) Methods of disorder, introduction to the optimization
14) Presentation of projects
15) Final Exam

Sources

Course Notes / Textbooks: Bioinformatics: Sequence and Genome Analysis, by D.Mount, 2004
Structural Bioinformatics, Bourne PE and Weissig H, John Wiley & Sons, 2003
Bioinformatics: Sequence Alignment and Markov Models, by K.R.Sharma, McGraw Hill 2009.
Computational Text Analysis for Functional Genomics and Bioinformatics, RayChaudhuri S, Oxford U Press, 2006
References: Bioinformatics: Sequence and Genome Analysis, by D.Mount, 2004
Structural Bioinformatics, Bourne PE and Weissig H, John Wiley & Sons, 2003
Bioinformatics: Sequence Alignment and Markov Models, by K.R.Sharma, McGraw Hill 2009.
Computational Text Analysis for Functional Genomics and Bioinformatics, RayChaudhuri S, Oxford U Press, 2006

Ders - Program Öğrenme Kazanım İlişkisi

Ders Öğrenme Kazanımları

1

2

3

Program Outcomes
1) Gains up-to-date evidence-based knowledge about nutrition and dietetics.
2) Gains information about technological tools by accessing up-to-date information.
3) She/He synthesizes and analyzes the scientific knowledge she has acquired using technology, develops comments, reports and solution suggestions, communicates with colleagues from different disciplines and in line with ethical principles and shares her knowledge.
4) When faced with problems related to her field, she/he takes responsibility, sets an example for the society, offers solutions, uses information and communication technologies by working as a team.
5) She/ He updates itself by adopting lifelong learning principles, evaluates, discusses and interprets scientific articles with a critical approach and statistical evidence-based practices in line with ethical principles.
6) She/He collects and interprets scientific information in line with ethical principles, contributes to studies that will guide national and international nutrition plans and policies, taking into account the individual and society, conducts, manages and evaluates.

Ders - Öğrenme Kazanımı İlişkisi

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Gains up-to-date evidence-based knowledge about nutrition and dietetics.
2) Gains information about technological tools by accessing up-to-date information.
3) She/He synthesizes and analyzes the scientific knowledge she has acquired using technology, develops comments, reports and solution suggestions, communicates with colleagues from different disciplines and in line with ethical principles and shares her knowledge.
4) When faced with problems related to her field, she/he takes responsibility, sets an example for the society, offers solutions, uses information and communication technologies by working as a team.
5) She/ He updates itself by adopting lifelong learning principles, evaluates, discusses and interprets scientific articles with a critical approach and statistical evidence-based practices in line with ethical principles.
6) She/He collects and interprets scientific information in line with ethical principles, contributes to studies that will guide national and international nutrition plans and policies, taking into account the individual and society, conducts, manages and evaluates.

Öğrenme Etkinliği ve Öğretme Yöntemleri

Anlatım
Course
Homework
Seminar

Ölçme ve Değerlendirme Yöntemleri ve Kriterleri

Yazılı Sınav (Açık uçlu sorular, çoktan seçmeli, doğru yanlış, eşleştirme, boşluk doldurma, sıralama)
Homework
Uygulama
Sunum

Assessment & Grading

Semester Requirements Number of Activities Level of Contribution
Homework Assignments 7 % 10
Midterms 1 % 30
Semester Final Exam 1 % 60
total % 100
PERCENTAGE OF SEMESTER WORK % 40
PERCENTAGE OF FINAL WORK % 60
total % 100

İş Yükü ve AKTS Kredisi Hesaplaması

Activities Number of Activities Duration (Hours) Workload
Course Hours 15 3 45
Study Hours Out of Class 15 5 75
Homework Assignments 10 4 40
Midterms 1 3 3
Final 1 3 3
Total Workload 166