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Principles of Bioinformatics - Period 3
OVERVIEW
CEA CAPA Partner Institution: Vrije Universiteit Amsterdam
Location: Amsterdam, Netherlands
Primary Subject Area: Computer Sciences
Instruction in: English
Course Code: X_401094
Transcript Source: Partner Institution
Course Details: Level 300
Recommended Semester Credits: 3
Contact Hours: 84
Prerequisites: Programming in Python, Molecular Biology
DESCRIPTION
The following topics are covered:
- Evolutionairy profiles
- Data resources in for the Life Sciences, including the Gene Ontology Database (GO)
- Homology Searching ( BLAST / PSI-BLAST )
- Genomics, Massively Parallel Sequencing (MPS) and analysis
- Benchmarking
- Computational Analysis of Genome Sequencing (Genome Assembly)
- Differential gene expression
- Clustering, machine learning and pattern recognition
There are practical sessions that aim to show you both existing solutions within the field of Bioinformatics. In the practicals you will use existing databases and (web-server) solutions to solve biological problems. You will also use python scripts to automate queries to databases and web servers to investigate the value of current
Bioinformatics Algorithms.
Vrije Universiteit Amsterdam (VU Amsterdam) awards credits based on the ECTS system. Contact hours listed under a course description may vary due to the combination of lecture-based and independent work required for each course therefore, CEA's recommended credits are based on the ECTS credits assigned by VU Amsterdam. 1 ECTS equals 28 contact hours assigned by VU Amsterdam.
- Evolutionairy profiles
- Data resources in for the Life Sciences, including the Gene Ontology Database (GO)
- Homology Searching ( BLAST / PSI-BLAST )
- Genomics, Massively Parallel Sequencing (MPS) and analysis
- Benchmarking
- Computational Analysis of Genome Sequencing (Genome Assembly)
- Differential gene expression
- Clustering, machine learning and pattern recognition
There are practical sessions that aim to show you both existing solutions within the field of Bioinformatics. In the practicals you will use existing databases and (web-server) solutions to solve biological problems. You will also use python scripts to automate queries to databases and web servers to investigate the value of current
Bioinformatics Algorithms.
Vrije Universiteit Amsterdam (VU Amsterdam) awards credits based on the ECTS system. Contact hours listed under a course description may vary due to the combination of lecture-based and independent work required for each course therefore, CEA's recommended credits are based on the ECTS credits assigned by VU Amsterdam. 1 ECTS equals 28 contact hours assigned by VU Amsterdam.
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