This is the OER material for lecture and lab for the first part of BIO3352 (Fall 2019).
This course is a continuation of Bioinformatics I. Topics include gene expression, microarrays, next- generation sequencing methods, RNA-seq, large genomic projects, protein structure and stability, protein folding, and computational structure prediction of proteins; proteomics; and protein-nucleic acid interactions. The lab component includes R-based statistical data analysis on large datasets, introduction to big data analysis tools, protein visualization software, internet-based tools and high-level programming languages.
Prerequisites: BIO 3350 and (MAT 1372 or MAT 2572)
Upon completion of the course, the students will be able to:
- Use well-established and widely used bioinformatics tools and platforms (e.g., ClustalW, R, GSEA, Gene Ontology).
- Use basic programming languages (e.g., Unix bash commands, AWK) to perform straightforward computational tasks.
- Understand the theory and statistical background of commonly available bioinformatics tools, so that they are able to judge the validity of the results provided by these tools.
- Navigate through internet-based biological databases and genomic browsers.
- Use online resources to search for scientific literature in the field of bioinformatics.
- Comprehend specific methodologies and results described in current bioinformatics literature.