BINF 500 DNA & PROTEIN SEQUENCE ANALYSIS (3)
Three hours lecture per week
Prerequisite: BIOL 400 or consent of the instructor
This course will introduce the computational aspects of biological inference from nucleic acid and protein sequences. Pairwise sequence comparison and multiple sequence alignment will be studied in detail. Additional topics include: RNA structure prediction, conserved sequence pattern recognition (sequence profile analysis), phylogenetic analysis algorithms, sequence data as a means to study molecular evolution, models and algorithms for genetic regulation, contig assembly, PAM and BLOSUM matrices, protein three dimensional structure prediction.
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BINF 501 BIOLOGICAL INFORMATICS (3) [top]
Three hours lecture per week
Prerequisite: BIOL 431 or consent of the instructor
This course describes relational data models and database management systems with an emphasis on answering biologically important questions; teaches the theories and techniques of constructing relational databases to store various biological data, including sequences, structures, genetic linkages and maps, and signal pathways. Topics include: relational database query language SQL and the ORACLE database management system, summary of currently existing biological databases, web based programming tools, data integration and security, future directions for biological database development.
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BINF 510 DATABASE SYSTEMS FOR BIOINFORMATICS (3) [top]
Three hours lecture per week
Prerequisite: BINF 501 and COMP 420, or consent of the instructor
This course is an applied, hands-on sequel to BINF 501, designed for students with interests in careers as professional programmers, analysts, designers, and managers involved in design or implementation of large bioinformatic systems. Covers concepts and methods for the design, creation, query and management of large enterprise databases, functions and characteristics of the leading database management systems. Topics include: object oriented database systems, distributed database systems, advanced database management topics, web application design and development, data warehouse systems, database mining.
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BINF 511 COMPUTATIONAL GENOMICS (3) [top]
Three hours lecture per week
Prerequisite: BINF 500 or consent of the instructor
This course applies the theories and algorithms taught in BINF 500 to real-life genomic data sets, with an emphasis on practical applications, hands-on analysis, integrated approaches and collaboration. Lecture and laboratory will explore the computational and engineering tools for analyzing genomic data. The relationships between sequence, structure, and function in complex biological networks will be studied using quantitative modeling.
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BINF 512 ALGORITHMS FOR BIOINFORMATICS (3) [top]
Three hours lecture per week
Prerequisite: BINF 500 or consent of the instructor
This course will cover advanced theory in the area of biological informatics and will build on concepts introduced in BINF 500. Topics include: methods to support construction and application of combinatorial biochemical libraries, applications of algorithmic information theory, string matching, dynamic programming, prediction of three-dimensional protein structure from peptide sequence.
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BINF 513 PROGRAMMING FOR BIOINFORMATICS (3) [top]
Three hours lecture per week
Prerequisite: BINF 501 and COMP 462 or equivalent, or consent of the instructor
This course will provide theory and practical training in the development of programming tools and data processing systems for use in genomic/sequence analysis. There will be a strong emphasis on the development of fully-functional web-based applications under the client/server model. Students will be required to complete a term project which will involve the development of a complete client/server application directed toward a relevant bioinformatics task.
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BINF 514 STATISTICAL METHODS IN COMPUTATIONAL BIOLOGY (3) [top]
Three hours lecture per week
Prerequisite: BIOL 202, MATH 151 or consent of the instructor
Techniques in statistical inference and stochastic modeling required for the interpretation and utilization of genomic data, including biological sequence alignment and analysis, sequence structure and function prediction, database searching, gene expression profiling, statistical genetics, phylogenetic inference and genetic epidemiology.
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