Bioinformatics
Course content
Learn how to extract relevant data from most essential databases
and how to use the methods for molecular sequence and functional
analysis within Bioinformatics.
Continuing education for medical doctors, academics within the
health care system, research environments, medicinal industries and
organisations working with personalised medicine.
The objective of the course is to provide you with a knowledge of
the most essential databases and methods for molecular sequence and
functional analysis.
These years, computer based methods play a crucial role in
molecular biology, microbiology, and personalised medicine. Huge
international databases of sequence and functional contain
information, which in some cases can entirely replace experimental
work, and in other cases can be used to optimize the benefit of
experimental resources.
Introduction to Bioinformatics is a practically oriented course
with focus on using the methods rather than deriving them
mathematically. Bioinformatics is presented as a biological
discipline rooted in evolutionary theory. A large part of the
course consists of computer-based exercises, where the
computational tools are applied based on the participants’
biological prior knowledge.
This course is offered as part of the Master in Personalised
Medicine.
The master's program is continuing education for health
professionals.
The Master of Personal Medicine has been developed in close
collaboration between the four faculties of health sciences at
University of Copenhagen, Aarhus University, Aalborg University and
the University of Southern Denmark as well as the Technical
University of Denmark. In this way, we ensure that you are taught
by national experts from internationally recognized research
environments in Denmark.
Read more about the programme on the
website: www.personligmedicin.ku.dk
Once you have met the objectives of the course, you will
be able to:
Knowledge
- Rationally apply bioinformatics tool to answer biological questions relevant to applied personalised medicine
- Explain how patient stratification is done based on genomics, transcriptomics, and proteomics data in practice using basic clustering and classification
Skills
- Explain how the information in biological macromolecules, such as DNA and protein can be represented in a digital format.
- Explain how processing of NGS data is done with bioinformatics tools
- Search for sequence data from the publicly available databases, such as GenBank and UniProt, and relevant disease omics data such as the cancer genome atlas (TCGA)
Competencies
- Use programs to perform basic clustering of patient samples, based on critical feature selection
- Search the clinvar and COSMIC databases of disease related mutations
The course consists of:
-Lectures and teamwork at DTU campus.
-Online teaching, group work with assignments, and presentations
from the students.
-Project work and report writing: The course ends with an
interdisciplinary group work based on a case.
The readings will be available to the students on the online course platform.
Read more about application requirements on the programme homepage. To find more information, please go to 'Sign Up' below.
Read more about application requirements on the
programme homepage. Please
note that the master in Personalised Medicine is a Danish
master programme.
This module can be taken as a single course to external
participants who meet the admission requirements. Read more
about the admission criteria and apply via
the course homepage.
- ECTS
- 5 ECTS
- Type of assessment
-
Written assignmentOral examination
- Type of assessment details
- The course ends with an interdisciplinary group work based on a case.
- Aid
- All aids allowed
- Marking scale
- passed/not passed
- Censorship form
- No external censorship
More than one internal examiner
- Exam period
-
See information about exam time in the exam plan. The exam plan is published on this website: https://sund.ku.dk/uddannelse/studieinformation/eksamensplaner/
- Re-exam
-
A re-examination will be possible if the student fails the first examination.
A new assignment/examination will be provided and in the same format as in the initial examination.
See information about re-exam time in the exam plan. The exam plan is published on this website: https://sund.ku.dk/uddannelse/studieinformation/eksamensplaner/
Criteria for exam assessment
In order to achieve the grade 12, the student must be able to:
Knowledge
- Rationally apply bioinformatics tool to answer biological questions relevant to applied personalised medicine
- Explain how patient stratification is done based on genomics, transcriptomics, and proteomics data in practice using basic clustering and classification
Skills
- Explain how the information in biological macromolecules, such as DNA and protein can be represented in a digital format.
- Explain how processing of NGS data is done with bioinformatics tools
- Search for sequence data from the publicly available databases, such as GenBank and UniProt, and relevant disease omics data such as the cancer genome atlas (TCGA)
Competencies
- Use programs to perform basic clustering of patient samples, based on critical feature selection
- Search the clinvar and COSMIC databases of disease related mutations
Part time Master and Diploma courses
- Category
- Hours
- Lectures
- 6
- Class Instruction
- 10
- Preparation
- 80
- E-Learning
- 12
- Project work
- 20
- Exam
- 10
- English
- 138
Kursusinformation
- Language
- English
- Course number
- SPMM21006U
- ECTS
- 5 ECTS
- Programme level
- Part Time Master
- Duration
-
1 semester
- Placement
- Spring
- Schedulegroup
-
- 4 days on campus
- 2 days online teaching
- individual preparation
- group work - Capacity
- 30
- Studyboard
- Study Board for the Professionel Master´s Degree Programmes at The Faculty og Health and Medical Science
Contracting department
- Department of Clinical Medicine
Contracting faculty
- Faculty of Health and Medical Sciences
Course Coordinator
- Carolina Mercedes Barra Quaglia (7-676576737069784468787932686f)
Teacher
Course director:
Carolina Barra Quaglia
Associate Professor, Group leader of Protein Immunoinformatics,
Department of Health Technology, Technical University of
Denmark.
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Kursusinformation for indskrevne studerende