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WebTycho Graduate School of Management & Technology – Programs
BIFS 613 Statistical Processes for Biotechnology (3) (Formerly BIOT 613)
Prerequisite: Knowledge of basic statistics.
A study of Bayesian statistics, Markov processes, and information
theory indices. These statistical tools can be used to analyze
sequence homology, the presence of motifs in sequences, gene
expression, and gene regulation. A number of concepts are
introduced, including information content, mutual information,
long-range correlation, repeats, and Fourier analysis. Linguistic
methods are evaluated.
BIFS 614 Data Structures and Algorithms (3) (Formerly CSMN 614)
An introduction to the definitions,
implementations, and applications of the most basic data structures
used in computer science, including the concept of abstract
data types. Also introduced are the basic formalism and concepts
used in the analysis of algorithms and in algorithm design.
The relative efficiency of the algorithms studied is estimated
by informal application of these ideas. The algorithms and data
structures discussed include those for sorting, searching, graph
problems, dynamic programming, combinatorial search, and others.
BIFS 617 Advanced Bioinformatics (3) (Formerly BIOT 617)
An overview of the basic programming tools for performing bioinformatic analyses in both the UNIX and MS DOS/Window environments. Focus is on the use of Perl and Bioperl as the basic programming tools. Basic programming skills are developed and practiced on such problems as codon usage/bias, open reading frame, CpG islands detection, and gene identification.
BIFS 618 Java for Biotechnology Applications (3)
A study of basic concepts in Java and object-oriented programming in bioinformatics application development. Emphasis is on Web-based, graphical, and database-driven application design. Review covers the function and design of some Java-based bioinformatics tools. Some commonly used libraries in the BioJava project are introduced, and developments of reusable modular application objects are examined. Basic problem-solving skills in the field of biotechnology using Java programming are developed through practical projects.
BIFS 619 Gene Expression Data Analysis (3)
A study of high-throughput technologies for transcriptome and genomic aberration profiling. Topics include statistical theories, algorithms and data analysis tools for microarray experiments, array comparative genome hybridization, SNP array experiments, and supervised and unsupervised machine learning technologies for class discovery and classifier identifications. Practice is provided in the preprocess of empirical gene expression profiling and the postprocess of microarray data analysis for identifying differentially regulated genes related to biological functions. Several legacy databases and data integration strategies in gene expression profiling are explored through data mining and functional annotation of interesting genes; statistical principles and theories are illustrated.