
BMB511: Introduction to Computational Biology
Comment
Entry requirements
Academic preconditions
- Have a basic knowledge of concepts in molecular biology and biochemical processes. This includes the central dogma, nucleic acid and protein structure.
- Have a basic knowledge of protein chemistry (BMB533 or similar is expected to be known)
- Be able to use the Internet and standard computer programs, including having a basic understanding of using R.
Course introduction
To give the student insight into the use of computational biology, bioinformatics and biological data science, and the significance and background of biological databases and programs in biology and biomedicine. Through practical exercises, the student will obtain knowledge of computational biology and the underlying biological phenomena and learn to relate to the analysis and results.
The course will take the student behind the software to see, how researchers use their knowledge of biology to construct bioinformatic tools driving modern computational biology. In addition, the student will be trained in practically applying such tools for analyzing and interpreting experimental data (both qualitative and quantitative), and in critically evaluating the limitations of the tools. In the course, theoretical and practical ethical problems within the subject as well as the function of the subject in society, will be discussed and reflected upon.
Students who follow this course are expected to have basic knowledge of concepts in molecular biology and biochemical processes, including the central dogma, nucleic acid, and protein structure. In addition, the students are expected to have basic knowledge of programming in R.
The course requires active participation. The functions of the SDU e-learning system will be used extensively in the course, and thus the student is required to master these functions and accept the associated deadlines.
In relation to the competence profile of the degree it is the explicit focus of the course to contribute to the following competencies:
- Knowledge of theories and experimental methods within the fields of molecular biology and biochemistry
- Knowledge of the scientific terminology used in the fields of molecular biology and biomedicine
- Knowledge of the importance of biological databases in modern biomedicine and molecular biology
- Understanding of how scientific knowledge is obtained through the interplay between theory and experiment
- The ability to acquire new knowledge effectively and independently, and to use that knowledge reflectively
- The understanding that the approach to the topics of the field is independent of national borders
- Be able to apply one or more theories and methods from the fields of biochemistry and molecular biology
- Be able to investigate concrete biochemical and molecular biological phenomena theoretically and or experimentally
- Be able to implement the use of bioinformatics
Expected learning outcome
- Know the most important data formats and concepts, which are used to analyze DNA, RNA, and protein data.
- Find, extract and use the information from the most relevant biological databases (e.g., UniProt.org), and understand the structure and most important characteristics of these.
- Know and use bioinformatics tools to characterize and compare nucleic acid sequences
- Know and use bioinformatics tools to investigate and compare protein sequence, structure and function.
- Understand the key concepts in analyzing and visualizing quantitative data from omics experiments, including transcriptomics and proteomics.
- Understand the principles behind gene ontology and its use in molecular networks
- Know the concepts of systems biology
- Understand the importance of open source code and open data policies and the accompanying ethical considerations
- Analyze digital images obtained by optical spectroscopy of biological samples, and extract information about the cellular processes from the images.
Content
The following main topics are contained in the course:
- Bioinformatics data and databases
- Qualitative analysis of biomolecules
- Quantitative analysis of biomolecules
- Bioinformatic image analysis
- Open data and ethics in bioinformatics
Literature
- Lecture presentations
- Handed notes, articles, videos and assignments.
The study material will be made available on the SDU e-learning system.
Examination regulations
Prerequisites for participating in the exam a)
Timing
Tests
Mandatory assignments
EKA
Assessment
Grading
Identification
Language
Examination aids
ECTS value
Additional information
The prerequisite examination is a prerequisite for participation in exam element a)
Exam element a)
Timing
Prerequisites
Type | Prerequisite name | Prerequisite course |
---|---|---|
Examination part | Prerequisites for participating in the exam a) | N200048101, BMB511: Introduction to Computational Biology |
Tests
Written exam
EKA
Assessment
Grading
Identification
Language
Duration
Examination aids
ECTS value
Additional information
Indicative number of lessons
Teaching Method
- Intro phase: 20 hours
- Skills training phase: 22 hours, hereof: Laboratory exercises: 22 hours
- Assignments
- Reading papers
Teacher responsible
Name | Department | |
---|---|---|
Jesper Grud Skat Madsen | jgsm@bmb.sdu.dk | Institut for Biokemi og Molekylær Biologi |
Additional teachers
Name | Department | City | |
---|---|---|---|
Daniel Wüstner | wuestner@bmb.sdu.dk | Institut for Biokemi og Molekylær Biologi | |
Ole Nørregaard Jensen | jenseno@bmb.sdu.dk | Institut for Biokemi og Molekylær Biologi | |
Thøger Jensen Krogh | thjk@bmb.sdu.dk | Administration og Service | |
Veit Schwämmle | veits@bmb.sdu.dk | Institut for Biokemi og Molekylær Biologi |