Syllabus ( BENG 458 )
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Basic information
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Course title: |
Bioinformatics and Systems Biology Laboratory |
Course code: |
BENG 458 |
Lecturer: |
Prof. Dr. Tunahan ÇAKIR
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ECTS credits: |
5 |
GTU credits: |
3 () |
Year, Semester: |
4/1, Fall and Spring |
Level of course: |
First Cycle (Undergraduate) |
Type of course: |
Elective
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Language of instruction: |
English
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Mode of delivery: |
Face to face , Group study , Lab work
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Pre- and co-requisites: |
none |
Professional practice: |
No |
Purpose of the course: |
The course aims to provide the students with hands-on experience on the computational systems biology and bioinformatics field. |
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Learning outcomes
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Upon successful completion of this course, students will be able to:
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analyze biological data using computational tools
Contribution to Program Outcomes
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Acquire knowledge on biological, chemical, physical and mathematical principles which constitute the basis of bioengineering applications
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Combine, Interpret, and analyze different subfields of bioengineering
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Work effectively in multi-disciplinary research teams
Method of assessment
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Written exam
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Laboratory exercise/exam
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identify associated molecular pathways and interactions or retrieve such data from databases for a given gene/protein list
Contribution to Program Outcomes
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Conduct and develop bioengineering applications for relevant sectors such as health and agricultural industry.
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Design processes for the investigation of bioengineering problems, collect data, analyze and interpret the results.
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Work effectively in multi-disciplinary research teams
Method of assessment
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Written exam
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Laboratory exercise/exam
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construct mathematical models from biological data
Contribution to Program Outcomes
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Apply mathematical analysis and modeling methods for bioengineering design and production processes.
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Work effectively in multi-disciplinary research teams
Method of assessment
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Written exam
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Laboratory exercise/exam
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Contents
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Week 1: |
Introduction to Biological Data Analysis |
Week 2: |
Gene Expression Omnibus and analysis of transcriptome data |
Week 3: |
Gene Ontology & Pathway enrichment analysis: g:profiler and EnrichR |
Week 4: |
Clustering (heatmap) and Principal Component Analysis using iGeak or ClustVis |
Week 5: |
Analysis of TCGA (The Cancer Genome Atlas) data using TCGABioLinks |
Week 6: |
Analysis of Metabolome Data using MetaboAnalyst |
Week 7: |
Analysis of single-cell RNA sequencing data using ALONA |
Week 8: |
Overview of data based approaches MidTerm Exam |
Week 9: |
Protein-protein interaction networks and STRING database |
Week 10: |
Using Cytoscape to draw and analyze biological networks |
Week 11: |
Gene-regulatory networks and DREM (Dynamic Regulatory Events Miner) |
Week 12: |
Kinetic modelling using COPASI |
Week 13: |
BioMet Toolbox and genome-scale metabolic models |
Week 14: |
Overview of network and modeling approaches
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Week 15*: |
- |
Week 16*: |
Final Exam |
Textbooks and materials: |
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Recommended readings: |
1. Edda Klipp, Ralf Herwig, Axel Kowald, Cristoph Wierling. “Systems Biology: A Textbook”, Wiley-Blackwell, 2016. 2. Analyzing Network Data in Biology and Medicine: An Interdisciplinary Textbook for Biological, Medical and Computational Scientists,Eds. Natasa Przulj, Cambridge University Press, 2019.
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* Between 15th and 16th weeks is there a free week for students to prepare for final exam.
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Assessment
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Method of assessment |
Week number |
Weight (%) |
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Mid-terms: |
8 |
15 |
Other in-term studies: |
2-13 |
70 |
Project: |
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0 |
Homework: |
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0 |
Quiz: |
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0 |
Final exam: |
16 |
15 |
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Total weight: |
(%) |
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Workload
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Activity |
Duration (Hours per week) |
Total number of weeks |
Total hours in term |
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Courses (Face-to-face teaching): |
3 |
14 |
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Own studies outside class: |
4 |
14 |
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Practice, Recitation: |
0 |
0 |
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Homework: |
0 |
0 |
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Term project: |
0 |
0 |
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Term project presentation: |
0 |
0 |
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Quiz: |
0 |
0 |
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Own study for mid-term exam: |
8 |
1 |
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Mid-term: |
1 |
1 |
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Personal studies for final exam: |
10 |
1 |
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Final exam: |
2 |
1 |
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Total workload: |
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Total ECTS credits: |
* |
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* ECTS credit is calculated by dividing total workload by 25. (1 ECTS = 25 work hours)
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