生物信息学概论-Introduction to Bioinformatics
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Pre-requisites
Biology I
Intended Learning Outcomes
The anticipated knowledge, skills and attitude to be developed by the student are:
1. Skills to perform simple alignment, assembly, and annotation algorithms for data sets
Syllabus ofBiotechnologyat Haide College
Introduction to Bioinformatics
Description
This course teaches analysis of these data sets, and interpretation of the significance o provides an understanding of the specific considerations of different sequencing technologies, as well as an understanding of the algorithms used to align, assemble, and annotate sequence data. While DNA sequencing is useful for sequencing genomes, it also has widespread applications in methods used to understand interactions, whether they be within a cell or organism (signalling, regulation, protein function).
5. Demonstrate understanding of common methods and applications for analysis of gene expression.
Learning Schedule
Content to bedecidedby the University of Adelaide
4. Discuss the contents of prokaryotic and eukaryotic genomes, the general function and origin of the main components, and considerations and difficulties in genome sequencing associated with these.
2. Formulate and justify appropriate choices in technology, strategy, and analysis for a range of projects involving DNA, RNA, or protein sequence data.
3. Employ command line sequence analysis tools to analyze biological sequence data sets, and demonstrate familiarity with the syntax and options required to generate meaningful interpretations.
Biology I
Intended Learning Outcomes
The anticipated knowledge, skills and attitude to be developed by the student are:
1. Skills to perform simple alignment, assembly, and annotation algorithms for data sets
Syllabus ofBiotechnologyat Haide College
Introduction to Bioinformatics
Description
This course teaches analysis of these data sets, and interpretation of the significance o provides an understanding of the specific considerations of different sequencing technologies, as well as an understanding of the algorithms used to align, assemble, and annotate sequence data. While DNA sequencing is useful for sequencing genomes, it also has widespread applications in methods used to understand interactions, whether they be within a cell or organism (signalling, regulation, protein function).
5. Demonstrate understanding of common methods and applications for analysis of gene expression.
Learning Schedule
Content to bedecidedby the University of Adelaide
4. Discuss the contents of prokaryotic and eukaryotic genomes, the general function and origin of the main components, and considerations and difficulties in genome sequencing associated with these.
2. Formulate and justify appropriate choices in technology, strategy, and analysis for a range of projects involving DNA, RNA, or protein sequence data.
3. Employ command line sequence analysis tools to analyze biological sequence data sets, and demonstrate familiarity with the syntax and options required to generate meaningful interpretations.