MBG2004 Computation for Biological Sciences IIBahçeşehir UniversityDegree Programs NURSING (ENGLISH)General Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
NURSING (ENGLISH)
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
MBG2004 Computation for Biological Sciences II Fall 2 2 3 7
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
Course Objectives: This class intended to provide advanced information to computational tools for biology.

Learning Outcomes

The students who have succeeded in this course;
1. Learn important biological data sources.
2. Evaluate the results of biological analysis statistically and mathematically.
3. Learns how to use various tools to evaluate genome sequencing data.
4. Learn basic level Matlab.

Course Content

Sequence data, searching and alignment, structural data, genome sequencing, genome analysis, genetic variation, gene and protein expression, and biological networks and pathways.

Weekly Detailed Course Contents

Week Subject Related Preparation
1) Advanced sequencing data analysis
2) Genome alignment I
3) Genome alignment II
4) Structural data
5) Genome sequencing
6) Genome analysis I
7) Genome analysis II
8) Advanced genetic variation analysis I
9) Advanced genetic variation analysis II
10) Biological networks I
11) Biological networks II
12) Biological pathways I
13) Biological pathways II
14) Biological pathways III

Sources

Course Notes / Textbooks: Ders notları haftalık olarak verilecektir.
Course material will be provided weekly.
References: Computational Biology Series Editors: Dress, A., Linial, M., Troyanskaya, O., Vingron, M. ISSN: 1568-2684

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Attendance 10 % 10
Presentation 1 % 15
Midterms 1 % 25
Final 1 % 50
Total % 100
PERCENTAGE OF SEMESTER WORK % 50
PERCENTAGE OF FINAL WORK % 50
Total % 100

ECTS / Workload Table

Activities Number of Activities Duration (Hours) Workload
Course Hours 14 4 56
Study Hours Out of Class 14 7 98
Presentations / Seminar 5 4 20
Midterms 1 2 2
Final 1 2 2
Total Workload 178

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) "To plan and assess nursing care within a holistic approach, in accordance with theoretical and evidence-based practices. "
2) To act in accordance with ethical principles and values in Nursing practices.
3) To use life-long learning, problem-solving and critical thinking skills.
4) To use Nursing models/theories in health promotion, protection and care.
5) To take part in research, projects and activities within sense of social responsibility and interdisciplinary approach.
6) "To have skills for training and consulting according to health education needs of individual, family and the community. "
7) "To be sensitive to health problems of the community and and to able to offer solutions. "
8) "To be able to use interpersonal and intercultural communication skills effectively in Nursing pratices. "
9) "To be able to use healthcare/information technologies in Nursing practice and research. "
10) To be able to search for literature in health sciences databases and information sources to access to information and use the information effectively.
11) To be able to monitor occupational information using at least one foreign language, to collaborate and communicate with colleagues at international level.
12) To take responsibility and lead in events in order to contribute to health services and Nursing profession.