Systems Biology / Biomolecular Kinetics & Cellular Dynamics

Course Information
TitleΒιολογία Συστημάτων / Systems Biology / Biomolecular Kinetics & Cellular Dynamics
SchoolChemical Engineering
Cycle / Level2nd / Postgraduate
Teaching PeriodSpring
Course ID600015530

Programme of Study: GSP CHEMICAL AND BIOMOLECULAR ENGINEERING (2018-until now)

Registered students: 4
OrientationAttendance TypeSemesterYearECTS
Health-FoodCompulsory Course belonging to the selected specialization (Compulsory Specialization Course)217

Class Information
Academic Year2018 – 2019
Class PeriodSpring
Faculty Instructors
Weekly Hours3
Total Hours39
Class ID
Type of the Course
  • Scientific Area
Course Category
Knowledge Deepening / Consolidation
Mode of Delivery
  • Face to face
Digital Course Content
The course is also offered to exchange programme students.
Language of Instruction
  • Greek (Instruction, Examination)
  • English (Instruction, Examination)
  • French (Instruction, Examination)
  • German (Instruction, Examination)
  • Italian (Instruction, Examination)
  • SPANISH (Instruction, Examination)
Learning Outcomes
On successful completion of this course students should be able to: • Demonstrate an understanding of the basic principles of Systems Biology approaches in biological systems. • Demonstrate an understanding of the way the whole of a biological systems exceeds the sum of the parts. • Demonstrate knowledge of the basic mathematical and computational modelling tools. • Demonstrate cutting-edge computational and experimental techniques relevant to systems biology. • Analyze biological systems in vivo using sensors, imaging techniques, and biomarker measurements. • Apply systems approaches to the analysis of biological systems. • Demonstrate knowledge of the gene, protein and metabolic systems. • Demonstrate knowledge of bioinformatics analysis and simulation of biological systems.
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Adapt to new situations
  • Make decisions
  • Work autonomously
  • Work in teams
  • Work in an interdisciplinary team
  • Be critical and self-critical
  • Advance free, creative and causative thinking
Course Content (Syllabus)
Systems Biology is the mathematical and computational modeling of complex biological systems. It has been developed as a result of convergence and synergy of three scientific areas: 1) Rapid accumulation of detailed biological information in the submolecular, molecular, cellular and physiological level. 2) Technological development that allowed us to analyze biological systems in vivo using sensors, imaging techniques, and biomarker measurements. 3) Combined development of more powerful mathematical, physical, and computational techniques available to a greater part of the scientific community. It is an interdisciplinary scientific field that focuses on complex interactions within biological systems using a holistic approach to biological research. Course contents: • Biological systems • Introduction to mathematical modeling • Static network models • The mathematics of biological systems • Cellular reaction models • Parameter Estimation - Model Configuration • Gene systems • Protein systems • Metabolic systems • Structural analysis of metabolic networks • Dynamic analysis of metabolic network flows • Signaling systems • Population systems • Multi-dimensional biological analysis - integrated data analysis • Gene expression, protein and metabolite analysis • Physiology-based models • Systemic biology in medicine and drug development • Systemic biology in personalized prevention • New horizons in systemic biology -From neurons in the brain -Multi-step models of cancer development - Multifactorial diseases, inflammation and trauma -Interaction between environment and health The course includes lectures by the instructor responsible, seminars by • invited professors and internationally renowned researchers, and laboratory exercises for • Bioinformatics analysis and simulation of biological systems
Computational modeling of complex biological systems; Biological systems; Gene systems/protein systems; bioinformatics; Gene expression
Educational Material Types
  • Notes
  • Slide presentations
  • Scientific articles
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Communication with Students
  • Use of ICT in Student Assessment
Lectures with powerpoint presentations Digital training material Email communication with the Professors
Course Organization
Reading Assigment50
Student Assessment
Students will be examined on the basis of laboratory exercises and related reports and upon completion of the essay delivered at the end of the course.
Student Assessment methods
  • Written Assignment (Formative, Summative)
  • Report (Formative, Summative)
  • Labortatory Assignment (Formative, Summative)
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