Course Details

PROTEOMICS&METABOLOMICS

BENG619

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Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS Credits
1BENG619PROTEOMICS&METABOLOMICS3+0+037,5

Course Details
Language of Instruction English
Level of Course Unit Master's Degree
Department / Program BIOENGINEERING
Type of Program Formal Education
Type of Course Unit Elective
Course Delivery Method Face To Face
Objectives of the Course Identifying principles of the most common proteomics techniques
Explaining the mass spectrometry-based proteomics workflow.
Analyzing experimental design, sample preparation and enrichment of techniques.
Designing research project by proteomics and metabolomics techniques.
Course Content Introduction to proteome and proteomics technology. General workflow for bottom-up and top-down proteomic approaches. Exploration of differential protein expression, post-translational modifications and protein-protein interactions (PPI). Introduction to metabolome and metabolomics. Metabolite identification, pathway identification and pathway integration.
Course Methods and Techniques This course utilizes an integrative and research-driven instructional approach tailored to doctoral-level education. Core concepts such as proteomics and metabolomics workflows, post-translational modifications, and metabolite-pathway integration are taught through interactive lectures and expert-led seminars. Emphasis is placed on hands-on data interpretation and experimental design via computational workshops and case-based learning. Journal club sessions encourage critical evaluation of current research in protein expression analysis, protein-protein interactions (PPI), and metabolic profiling. Students are expected to actively engage in group discussions, lead presentations on recent scientific findings, and develop research proposals that incorporate omics technologies. These activities are designed to strengthen skills in experimental planning, bioinformatics analysis, and scientific communication within systems biology and functional proteomics/metabolomics.
Prerequisites and co-requisities None
Course Coordinator None
Name of Lecturers Asist Prof.Dr. Emel Başak Gencer Akçok emelbasak.gencerakcok@agu.edu.tr
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources Proteomics: From Protein Sequence to Function (2nd Edition) Author: S.R. Pennington and M.J. Dunn
Metabolomics: From Fundamentals to Clinical Applications Editors: Jens Nielsen and Michael C. Jewett
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Course Category
Science %100

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Yarıyıl İçi Çalışmalarının Başarı Notunun Katkısı 1 % 25
Proje/Çizim 1 % 20
Sunum/Seminer 1 % 20
Final examination 1 % 35
Total
4
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Sunum için Hazırlık 1 8 8
Sunum 1 2 2
Proje 1 18 18
Okuma 14 2 28
Araştırma 10 2 20
Kişisel Çalışma 14 3 42
Ders dışı çalışma 14 2 28
Yüz Yüze Ders 14 3 42
Final Sınavı 1 16 16
Total Work Load   Number of ECTS Credits 7,5 204

Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Describe modern strategies of proteomics and metabolomics.
2 Evaluate strengths and limitations of mass spectrometry-based proteomics workflows.
3 Plan a group discussion.
4 Modify a research proposal.


Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Introduction to Proteomics
2 Proteomics Technologies
3 Bottom-up and Top-down Proteomics
4 Quantitative Proteomics
5 Differential Protein Expression Analysis
6 Post-translational Modifications (PTMs)
7 Protein-Protein Interactions (PPI)
8 Introduction to Metabolomics
9 Metabolomics Technologies
10 Metabolite Identification and Annotation
11 Pathway Analysis and Integration
12 Multi-omics Integration
13 Applications in Disease, Drug Discovery, and Biotechnology
14 Emerging Trends AI in omics, single-cell proteomics/metabolomics


Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12
C1 5 5 3 4 4 5 4 4 4 4 3 5
C2 4 5 4 3 5 3 4 5 5 5 4 3
C3 5 5 5 4 4 3 4 3 5 5 5 4
C4 4 4 5 4 4 3 4 5 3 5 3 4

Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant


https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=78039&lang=en
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