Bioinformatics with Applications in Medicine

Course Information
TitleΒΙΟΠΛΗΡΟΦΟΡΙΚΗ ΜΕ ΕΦΑΡΜΟΓΕΣ ΣΤΗΝ ΙΑΤΡΙΚΗ / Bioinformatics with Applications in Medicine
CodeΙΑ0428
FacultyHealth Sciences
SchoolMedicine
Cycle / Level1st / Undergraduate
Teaching PeriodWinter
CoordinatorAntigoni Malousi
CommonNo
StatusActive
Course ID600015007
Class Information
Academic Year2020 – 2021
Class PeriodSpring
Faculty Instructors
Instructors from Other Categories
Weekly Hours2
Class ID
600172132
SectionInstructors
1. ΕΡΓΑΣΤΗΡΙΟ ΒΙΟΛΟΓΙΚΗΣ ΧΗΜΕΙΑΣ
Course Type 2011-2015
General Foundation
Mode of Delivery
  • Face to face
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
The course includes practical training of students in specific medical-oriented applications of bioinformatic tools and databases. The practice will take place during the course so students must have a computer with them.
Learning Outcomes
At the end of the course, the students will be able to: 1. Identify the type of problems that can be solved using Bioinformatics methods. 2. Select and appropriately use available databases and tools. 3. To develop and execute bioinformatics pipelines. 4. To understand the usage and importance of Bioinformatics in personalized diagnostics and therapeutics.
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Work autonomously
  • Work in teams
  • Work in an interdisciplinary team
  • Generate new research ideas
Course Content (Syllabus)
The course will cover the analysis of multiple -omics data at different scales, starting from introductory concepts and basic algorithms such as alignment, weight matrices etc. At each -omic level, e.g. genomics, transcriptomics, proteomics different approaches will be described and applied through medical-oriented hands-on exercises. The course will also introduce the main high-throughput sequencing technologies and example pipelines for the analysis and interpretation of huge datasets through user-friendly platforms.
Keywords
bioinformatics, algorithms, workflows, high-throughput data analysis, computational -omics
Educational Material Types
  • Notes
  • Slide presentations
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
Lectures150.6
Laboratory Work70.3
Written assigments100.4
Exams200.8
Total522
Student Assessment
Description
The evaluation includes optional assignments (individual or group based on the number of participants), which will add up to 2 points to the final mark, as well as the final written test in the form of closed and open questions.
Student Assessment methods
  • Written Exam with Multiple Choice Questions (Formative)
  • Written Exam with Short Answer Questions (Formative)
  • Written Assignment (Formative)
Bibliography
Additional bibliography for study
Αποθετήριο ηλεκτρονικών συγγραμμάτων “Κάλλιπος”: 1. Μπάγκος, Π., 2015. Βιοπληροφορική. [ηλεκτρ. βιβλ.] Αθήνα: Σύνδεσμος Ελληνικών Ακαδημαϊκών Βιβλιοθηκών. Διαθέσιμο δωρεάν στο: http://hdl.handle.net/11419/5016 2. Νικολάου, Χ., Χουβαρδάς, Π., 2015. Υπολογιστική βιολογία. [ηλεκτρ. βιβλ.] Αθήνα: Σύνδεσμος Ελληνικών Ακαδημαϊκών Βιβλιοθηκών. Διαθέσιμο δωρεάν στο: http://hdl.handle.net/11419/1577
Last Update
19-03-2021