INFORMATION TECHNOLOGIES (MASTER) (WITH THESIS) (ENGLISH)
Qualification Awarded Program Süresi Toplam Kredi (AKTS) Öğretim Şekli Yeterliliğin Düzeyi ve Öğrenme Alanı
2 120 FULL TIME TYÇ, TR-NQF-HE, EQF-LLL, ISCED (2011):Level 7
QF-EHEA:Second Cycle
TR-NQF-HE, ISCED (1997-2013): 44,46,48,52,72

Ders Genel Tanıtım Bilgileri

Course Code: 3024002002
Ders İsmi: Fundamentals of Genetics
Ders Yarıyılı: Fall
Ders Kredileri:
Theoretical Practical Labs Credit ECTS
3 0 0 3 6
Language of instruction: EN
Ders Koşulu:
Ders İş Deneyimini Gerektiriyor mu?: No
Other Recommended Topics for the Course:
Type of course: Department Elective
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 : Prof. Dr. Meliha Burcu IRMAK YAZICIOĞLU
Course Lecturer(s):
Course Assistants:

Dersin Amaç ve İçeriği

Course Objectives: Fundamentals of Genetics will provide students with a broad genetics background, and will cover topics ranging from understanding the flow of genetic information within single-celled organisms to how genes and gene products function within multicellular organisms.
Course Content: Introduction to genetics and basic genetic concepts: phenotype, genotype, chromosome, gen allel, chromosomes, karyotype, Mendelian genetics: Monohybrid cross, Dihybrid and trihybrid crosses, Cell divisions: Mitotic division, meiotic division, Extensions of Mendelian Genetics: ıncomplete dominance, codominance, multiple alleles and blood groups, lethal genes, epistasy, linkage and mapping, cytoplasmic inhetance, sex chromosomes, sex- linked inheritance, chromosomal mutations, Quantitative Genetics, Population Genetics.

Learning Outcomes

The students who have succeeded in this course;
Learning Outcomes
1 - Knowledge
Theoretical - Conceptual
1) Students will be able to define basic genetics terms, and use these terms to explain fundamental concepts in genetics related to: nucleic acid structure, the central dogma, gene regulation in eukaryotes and prokaryotes, transmission genetics, and molecular genetics.
2) Students will gain experience analyzing and interpreting data from genetics experiments, both from historical experiments and current genetics methods. In addition, students will be able to explain how model organisms are used to understand genetics principles, providing specific examples.
2 - Skills
Cognitive - Practical
1) Students will be able to describe specific examples of how advances in our understanding of genetics and molecular biology have impacted society
2) Students will be able to describe normal chromosome number, structure, and behaviour in cells, and understand the cause and effect of alterations in chromosome number and/or structure.
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Ders Akış Planı

Week Subject Related Preparation
1) Introduction Klug, W. S., Cummings, M. R., Spencer, C. A., & Palladino, M. A. (2014). Concepts of Genetics (11th ed.). Pearson.
2) DNA as the genetic material Urry, L. A., Cain, M. L., Wasserman, S. A., Minorsky, P. V., Reece, J. B., & Jackson, R. B. (2016). Campbell Biology (11th ed.). Pearson.
3) Structure of DNA and RNA Klug, W. S., Cummings, M. R., Spencer, C. A., & Palladino, M. A. (2014). Concepts of Genetics (11th ed.). Pearson.
4) DNA organization Urry, L. A., Cain, M. L., Wasserman, S. A., Minorsky, P. V., Reece, J. B., & Jackson, R. B. (2016). Campbell Biology (11th ed.). Pearson.
5) DNA replication, Polymerase chain reaction (PCR) and DNA sequencing; Klug, W. S., Cummings, M. R., Spencer, C. A., & Palladino, M. A. (2014). Concepts of Genetics (11th ed.). Pearson.
6) Chromosome Structure & Number Urry, L. A., Cain, M. L., Wasserman, S. A., Minorsky, P. V., Reece, J. B., & Jackson, R. B. (2016). Campbell Biology (11th ed.). Pearson.
7) Mendel’s Laws of Inheritance and Probability Klug, W. S., Cummings, M. R., Spencer, C. A., & Palladino, M. A. (2014). Concepts of Genetics (11th ed.). Pearson.
8) Midterm exam
9) Inheritance of sex chromosomes, Complex and Non-Mendelian Genetics Urry, L. A., Cain, M. L., Wasserman, S. A., Minorsky, P. V., Reece, J. B., & Jackson, R. B. (2016). Campbell Biology (11th ed.). Pearson.
10) Genetic Linkage & Mapping Klug, W. S., Cummings, M. R., Spencer, C. A., & Palladino, M. A. (2014). Concepts of Genetics (11th ed.). Pearson.
11) Central Dogma, Transcription: making RNA from DNA Alberts, B., Johnson, A., Lewis, J., Raff, M., Roberts, K., & Walter, P. (2014). Molecular Biology of the Cell (6th ed.). Garland Science.
12) Translation Klug, W. S., Cummings, M. R., Spencer, C. A., & Palladino, M. A. (2014). Concepts of Genetics (11th ed.). Pearson.
13) Gene regulation by non-coding RNAs & RNAi Klug, W. S., Cummings, M. R., Spencer, C. A., & Palladino, M. A. (2014). Concepts of Genetics (11th ed.). Pearson.
14) Introduction to Bioinformatics Alberts, B., Johnson, A., Lewis, J., Raff, M., Roberts, K., & Walter, P. (2014). Molecular Biology of the Cell (6th ed.). Garland Science.
15) DNA as digital data storage Alberts, B., Johnson, A., Lewis, J., Raff, M., Roberts, K., & Walter, P. (2014). Molecular Biology of the Cell (6th ed.). Garland Science.
16) Final

Sources

Course Notes / Textbooks: Klug, W. S., Cummings, M. R., Spencer, C. A., & Palladino, M. A. (2014). Concepts of Genetics (11th ed.). Pearson.
Alberts, B., Johnson, A., Lewis, J., Raff, M., Roberts, K., & Walter, P. (2014). Molecular Biology of the Cell (6th ed.). Garland Science.
Urry, L. A., Cain, M. L., Wasserman, S. A., Minorsky, P. V., Reece, J. B., & Jackson, R. B. (2016). Campbell Biology (11th ed.). Pearson.
References: Klug, W. S., Cummings, M. R., Spencer, C. A., & Palladino, M. A. (2014). Concepts of Genetics (11th ed.). Pearson.
Alberts, B., Johnson, A., Lewis, J., Raff, M., Roberts, K., & Walter, P. (2014). Molecular Biology of the Cell (6th ed.). Garland Science.
Urry, L. A., Cain, M. L., Wasserman, S. A., Minorsky, P. V., Reece, J. B., & Jackson, R. B. (2016). Campbell Biology (11th ed.). Pearson.

Ders - Program Öğrenme Kazanım İlişkisi

Ders Öğrenme Kazanımları

1

3

2

4
Program Outcomes
1) Ability to use and apply current technical concepts and practices in the information technologies of engineering, data management and computer security.
2) Understanding user needs, analyzing them, and using them in the selection, evaluation, and management of computer-based systems.
3) Ability to use data structures and develop algorithms.
4) Ability to analyze and interpret complex big data systems.
5) Ability to interpret and apply concepts and algorithms in machine learning.
6) Understanding of the mathematical foundations of deep learning in the field of data analysis and the ability to apply the theory.
7) Ability to solve complex data structures, develop and apply deep learning models, and interpret artificial intelligence-focused research on these topics.
8) Ability to apply deep learning techniques and interpret real-world datasets and projects to solve problems in image analysis, natural language processing, and recommendation systems.
9) Ability to transfer the basic principles and mathematical infrastructure of digital signal processing to practical applications.
10) Gaining knowledge about the tools and technologies used via the Internet and the different technologies used for server coding languages and tools.
11) Ability to understand of how genes function in multicellular species, the flow of genetic information in single-cell organisms, and the ability to interpret and apply biotechnology applications.
12) Being aware of ethical values and understanding the need to conduct research and practice within the framework of these values.

Ders - Öğrenme Kazanımı İlişkisi

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Ability to use and apply current technical concepts and practices in the information technologies of engineering, data management and computer security.
2) Understanding user needs, analyzing them, and using them in the selection, evaluation, and management of computer-based systems.
3) Ability to use data structures and develop algorithms.
4) Ability to analyze and interpret complex big data systems.
5) Ability to interpret and apply concepts and algorithms in machine learning.
6) Understanding of the mathematical foundations of deep learning in the field of data analysis and the ability to apply the theory.
7) Ability to solve complex data structures, develop and apply deep learning models, and interpret artificial intelligence-focused research on these topics.
8) Ability to apply deep learning techniques and interpret real-world datasets and projects to solve problems in image analysis, natural language processing, and recommendation systems.
9) Ability to transfer the basic principles and mathematical infrastructure of digital signal processing to practical applications.
10) Gaining knowledge about the tools and technologies used via the Internet and the different technologies used for server coding languages and tools.
11) Ability to understand of how genes function in multicellular species, the flow of genetic information in single-cell organisms, and the ability to interpret and apply biotechnology applications.
12) Being aware of ethical values and understanding the need to conduct research and practice within the framework of these values.

Öğrenme Etkinliği ve Öğretme Yöntemleri

Akran Değerlendirmesi
Course
Okuma
Homework
Soru cevap/ Tartışma

Ölçme ve Değerlendirme Yöntemleri ve Kriterleri

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

Assessment & Grading

Semester Requirements Number of Activities Level of Contribution
Midterms 1 % 40
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 2 30
Application 15 2 30
Study Hours Out of Class 15 5 75
Midterms 1 2 2
Final 1 2 2
Total Workload 139