student learning objectives - abpg
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Student Learning Objectives (SLO's)
BIPG6400/8400 Application of Bioinformatics (3cr)
The following course-specific SLO鈥檚 map back to the BPG program-specific SLO鈥檚.
Graduating students WILL BE ABLE TO:
1)听听听听听听听听听听听 Describe mammalian and nonmammalian genome structure and function, including
(for
听听听听听听听听听听听听听听 example):
a.听听听听听听听听听听听 Coding/non-coding sequence distribution
b.听听听听听听听听听听听 Isochore structure
c.听听听听听听听听听听听听 Repeated element distribution
d.听听听听听听听听听听听 Intron/exon structure and distribution
e.听听听听听听听听听听听 Transcription factor binding sites (for long- and short-range factors)
2)听听听听听听听听听听听 Discuss the processes of genome evolution, including (for example):
a.听听听听听听听听听听听 Mechanisms of mutation
b.听听听听听听听听听听听 Consequences and exploitation of SNPs
c.听听听听听听听听听听听听 Phylogenetics
d.听听听听听听听听听听听 Major theories for the origin of novel genes
e.听听听听听听听听听听听 Nature and basis of codon bias
3)听听听听听听听听听听听 Describe and use analytic tools associated with systems/bioinformatic
approaches, including (for
听听听听听听听听听听听听听听 example):
a.听听听听听听听听听听听 Transcriptomics 鈥� microarray analysis vs. deep sequencing
b.听听听听听听听听听听听 Determining statistical significance in large bioinformatic datasets
c.听听听听听听听听听听听听 Determination and structure of interaction networks
d.听听听听听听听听听听听 Functional network maps
4)听听听听听听听听听听听 Carry out appropriate statistical analysis of sequence information,
including (for example):
a.听听听听听听听听听听听 Probabilistic methods
b.听听听听听听听听听听听 Deterministic methods
c.听听听听听听听听听听听听 Machine learning methods, including Support Vector Machines (SVMs)
d.听听听听听听听听听听听 Cluster analysis
5)听听听听听听听听听听听 Demonstrate competent use of existing bioinformatic and statistical
software, including (for
听听听听听听听听听听听听听听 example):
a.听听听听听听听听听听听 Phylogenetic analyses
6)听听听听听听听听听听听 Communicate competently both in writing and orally
a.听听听听听听听听听听听 With fellow team members in research projects