CEN410 Computational Biology and Advanced Topics

6 ECTS - 3-0 Duration (T+A)- 8. Semester- 3 National Credit

Information

Code CEN410
Name Computational Biology and Advanced Topics
Term 2022-2023 Academic Year
Semester 8. Semester
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 6 ECTS
National Credit 3 National Credit
Teaching Language İngilizce
Level Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Yılmaz ATAY
Course Instructor
1


Course Goal / Objective

Analysis of protein sequences and other complex biological systems by computer based methods

Course Content

Basics of Biology, Sequence Assembly, Sequence Alignment, Motif Finding, Dynamic Programming for Alignment, Molecular Computers, Introduction to Complex Biological Systems

Course Precondition

Resources

Notes



Course Learning Outcomes

Order Course Learning Outcomes
LO01 Understanding the protein sequence
LO02 Understanding the methods requred to analyze sequences
LO03 Finding the patterns in the sequences
LO04 Understanding the methods required for analysis of complex biological systems


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal Has capability in the fields of mathematics, science and computer that form the foundations of engineering 1
PLO02 Bilgi - Kuramsal, Olgusal Identifies, formulates, and solves engineering problems, selects and applies appropriate analytical methods and modeling techniques, 1
PLO03 Bilgi - Kuramsal, Olgusal Analyzes a system, its component, or process and designs under realistic constraints to meet the desired requirements,gains the ability to apply the methods of modern design accordingly. 1
PLO04 Bilgi - Kuramsal, Olgusal Ability to use modern techniques and tools necessary for engineering practice and information technologies effectively. 1
PLO05 Bilgi - Kuramsal, Olgusal Ability to design and to conduct experiments, to collect data, to analyze and to interpret results 1
PLO06 Bilgi - Kuramsal, Olgusal Has ability to work effectively as an individual and in multi-disciplinary teams, take sresponsibility and builds self-confidence 1
PLO07 Beceriler - Bilişsel, Uygulamalı Can access information,gains the ability to do resource research and uses information resources 1
PLO08 Beceriler - Bilişsel, Uygulamalı Awareness of the requirement of lifelong learning, to follow developments in science and technology and continuous self-renewal ability 1
PLO09 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Ability to communicate effectively orally and in writing, and to read and understand technical publications in at least one foreign language 1
PLO10 Yetkinlikler - Öğrenme Yetkinliği Professional and ethical responsibility, 1
PLO11 Yetkinlikler - Öğrenme Yetkinliği Awareness about project management, workplace practices, employee health, environmental and occupational safety, and the legal implications of engineering applications, 1
PLO12 Yetkinlikler - Öğrenme Yetkinliği Becomes aware of universal and social effects of engineering solutions and applications, entrepreneurship and innovation, and knowledge of contemporary issues 1


Week Plan

Week Topic Preparation Methods
1 History of Computational Biology Reading related chapter
2 Basics of Biology Reading related chapter
3 Alignment and Statistics Reading related chapter
4 Protein Alignment Reading related chapter
5 Markov and Hidden Markov Models for Protein Features Reading related chapter
6 Protein Structure Reading related chapter
7 Methods for obtaining patterns Reading related chapter
8 Mid-Term Exam Review of lecture notes
9 Predicting protein structure Reading related chapter
10 Protein Interactions Reading related chapter
11 Regulatory Networks Reading related chapter
12 Gene Regulatory Networks Reading related chapter
13 Comparative analysis of gene regulation Reading related chapter
14 Synthetic Biology Reading related chapter
15 Human Genetics Reading related chapter
16 Term Exams Review of lecture notes
17 Term Exams Review of lecture notes


Student Workload - ECTS

Works Number Time (Hour) Workload (Hour)
Course Related Works
Class Time (Exam weeks are excluded) 14 3 42
Out of Class Study (Preliminary Work, Practice) 14 5 70
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 15 15
Final Exam 1 30 30
Total Workload (Hour) 157
Total Workload / 25 (h) 6,28
ECTS 6 ECTS

Update Time: 14.11.2022 10:33