Electives-By Track

Sample Bioinformatics-Genomics Track

Data Warehousing and Data Mining. CSE 591 (3 credit hours). Introduction to knowledge discovery and data mining; classification (ID3, NN); preparing data for mining (data selection, discretization, feature selection); clustering (numerical taxonomy, k-means, COBWEB); data mining applications; mining association rules from large databases; data warehousing: issues, solutions, implementation; database schema, mining issues related to the Web.

Computational Genomics. BIO 494 (3 credit hours). In this course, fundamentals of computational genomic analysis will be discussed. Understanding of the basic methodologies and techniques for comparative DNA and protein sequence analysis will be emphasized, and their use in studying longstanding problems in basic biomedicine and evolutionary genomics will be introduced. This course is intended to prepare senior undergraduate and graduate students to exploit new avenues in biological research opened by the availability of molecular sequence and genome map data from diverse species, genes, and genomes.

Molecular Genetics. BIO 543 (3 credit hours). Nature and function of the gene; emphasis on the molecular basis of inheritance and gene expression in procaryotes and eucaryotes.

Advanced Statistical Genomics. MAT 598. Probabilistic and statistical methods in DNA sequence alignment and construction of phylogenetic trees.

Statistical Methods in Molecular Evolutionary Genetics. BIO 594 (3 credit hours). This course introduces various advanced statistical methods and algorithms useful in molecular evolutionary and phylogenetic analysis of multi-species and multigene family datasets. Emphasis is placed on both theory and practice of the methods and algorithms introduced and there is extensive discussion about the pragmatic use of these methods in solving biological problems.

Functional Genomics. MCB 576 (2 credit hours). Functional relevance of genomic sequences from prokaryotes and eukaryotes; DNA arrays; proteomics; analysis of genomic information to understand the metabolic physiology of organisms. Instructor recommends a background in biochemistry (such as BCH 361) prior to taking this course.