BIOINFORMATICS II - DIGITAL BIOLOGY

Course Information
TitleΒΙΟΠΛΗΡΟΦΟΡΙΚΗ II - ΨΗΦΙΑΚΗ ΒΙΟΛΟΓΙΑ / BIOINFORMATICS II - DIGITAL BIOLOGY
CodeNNA-07-10
FacultySciences
SchoolInformatics
Cycle / Level1st / Undergraduate
Teaching PeriodWinter
CoordinatorChristos Ouzounis
CommonNo
StatusActive
Course ID600020400

Programme of Study: PPS-Tmīma Plīroforikīs (2019-sīmera)

Registered students: 70
OrientationAttendance TypeSemesterYearECTS
GENIKĪ KATEUTHYNSĪElective Courses745
Class Information
Academic Year2025 – 2026
Class PeriodWinter
Faculty Instructors
Weekly Hours3
Total Hours39
Class ID
600279986
Course Type 2021
Specific Foundation
Course Type 2016-2020
  • Scientific Area
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
  • Face to face
  • Distance learning
Digital Course Content
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
  • Greek (Instruction, Examination)
  • English (Instruction, Examination)
Prerequisites
General Prerequisites
informatics, programming
Learning Outcomes
Knowledge: Training of students on knowledge of systems biology. Next-generation data production technologies. Data resources and integration, visualization. Interaction models, graphs, static and dynamic models. Accuracy and quality control. Motif detection algorithms in big data and simulation systems. Intelligent systems for the representation of biological complexity. Synthetic biology, bio-inspired technologies and life technologies. Computational challenges and future perspectives. Skills: Acquiring the ability to identify and select resources and tools for systems biology. Solving questions, reproducibility, searching for bibliographic and systems-biology information. Presentation of their work (communication ability, correct use of presentation techniques, familiarization with questions from the public).
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Make decisions
  • Work autonomously
  • Work in teams
  • Work in an interdisciplinary team
  • Generate new research ideas
  • Design and manage projects
  • Be critical and self-critical
  • Advance free, creative and causative thinking
Keywords
systems biology, bio-inspired technologies, synthetic biology
Educational Material Types
  • Notes
  • Slide presentations
  • Video lectures
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Laboratory Teaching
  • Use of ICT in Communication with Students
  • Use of ICT in Student Assessment
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures50
Laboratory Work20
Written assigments25
Exams
Other / Others5
Total100
Student Assessment
Description
Description The course is evaluated in the following ways: • Written examination that contributes 40% of the grade, • Laboratory exercises will be 30% of the total grade, • Simulation of research work will be 30% of the total grade.
Student Assessment methods
  • Written Exam with Multiple Choice Questions (Formative)
  • Written Exam with Short Answer Questions (Formative)
  • Written Exam with Extended Answer Questions (Formative)
  • Written Assignment (Formative)
  • Written Exam with Problem Solving (Formative)
Bibliography
Course Bibliography (Eudoxus)
Συνθετική Βιολογία : Βασικές Αρχές, by Geoff Baldwin et al. publisher: UTOPIA (2017) Language: Ελληνικά Paperback: 160 ISBN: 978-618-5173-26-5 Εύδοξος: 68403717 An Introduction to Systems Biology : Design Principles of Biological Circuits, by Uri Alon publisher: Chapman & Hall; 2nd edition (2019) Language: English Paperback: 324 pages ISBN-10: 1439837171 ISBN-13: 978-1439837177 https://www.weizmann.ac.il/mcb/UriAlon/introduction-systems-biology-design-principles- biological-circuits
Additional bibliography for study
Systems Biology: Introduction to Pathway Modeling, by Herbert M. Sauro publisher: Ambrosius Publishing & Future Skill Softrware; new edition 1.2 (2020) Language: English Paperback: 480 pages ISBN-13: 978-0982477373 Automated Reasoning for Systems Biology and Medicine, Pietro Liò & Paolo Zuliani (eds) publisher: Springer (2019) Language: English Paperback: 470 pages ISBN: 978-3-030-17299-2 eBook: EPUB, PDF ISBN: 978-3-030-17297-8 https://www.springer.com/gp/book/9783030172961 Bio-inspired artificial intelligence, by Dario Floreano & Claudio Mattiussi publisher: MIT Press (2008) Language: English Hardcover: 674 pages ISBN: 978-0262062718 https://mitpress.mit.edu/books/bio-inspired-artificial-intelligence
Last Update
29-03-2023