Energy and Information in Biological Modeling BINF 6101 (Dr. Gibas) Spring 2008 Prerequisites: Admission to graduate standing in Bioinformatics. This course covers: the major organic and inorganic chemical features of biological macromolecules, the physical forces that shape biological molecules, assemblies and cells, the chemical driving forces that govern living systems, the molecular roles of biological macromolecules and common metabolites, and the pathways of energy generation and storage. Each section of the course builds upon the relevant biology and chemistry to explain the most common mathematical and physical abstractions used in modeling in the relevant context. Credits: 3 Category: Fundamentals   Website

Bioinformatics Programming I BINF 6111 (Dr. Fodor) Fall 2007 Prerequisites: Admission to graduate standing in Bioinformatics. Students in this course will learn how to use object-oriented programming to solve common problems in bioinformatics. Topics covered will include creation and manipulation of relational databases and interfacing with standard bioinformatics programs such as CLUSTAL, BLAST and HMMer. Emphasis will be placed on the creation of memory and time efficient algorithms to handle the large data sets of post-genomic biology Credits: 3 Category: Fundamentals

Bioinformatics Programming II BINF 6112 (Dr. Fodor) Spring 2008 This is a continuation of Bioinformatics Programming I (BINF 6111). While the previous course emphasized fundamentals of Bioinformatics programming, this course emphasizes efficiency in speed, data structures and file size. Students will learn how to optimize code and databases so that the demanding analyses of modern biology can be performed in acceptable amounts of time while minimizing hardware requirements. Topics covered will include algorithm optimization, optimization of database queries and parallel processing to allow bioinformatics calculations to be performed on clusters. Credits: 3 Category: Fundamentals

Statistics for Bioinformatics BINF 6200 Spring 2008 The aim of this 3-credit course is to introduce students to statistical methods used in further more technical courses. Basic relevant concepts from probability, stochastic processes, information theory, statistitics and experimental design will be introduced and illustrated by examples from molecular biology, genomics and population genetics with an outline of algorithms and software. R is introduced as the programming language for homework. Credits: 3 Category: Core

Molecular Sequence Analysis BINF 6201 (Dr. Gibas) Fall 2007 Prerequisite: BINF 6100 or equivalent. Introduction to bioinformatics methods that apply to molecular sequence. Intro to biological databases online. Sequence databases, molecular sequence data formats, sequence data preparation and database submission. Local and global sequence alignment, multiple alignment, alignment scoring and alignment algorithms for protein and nucleic acids, genefinding and feature finding in sequence, models of molecular evolution, phylogenetic analysis, comparative modeling. Credits: 3 Category: Core

Computational Structural Biology BINF 6202 (Dr. Livesay) Spring 2008 This course will cover: (a) the fundamental concepts of structural biology (chemical building blocks, structure, superstructure, folding, etc.); (b) software for visualization, visualization styles, publication quality images; (c) the hierarchical nature of biomacromolecular structure classification; (d) computational methods to evaluate and compare biomacromolecular structure; (e) inferring structure/function relationships from structure; and (f) computational prediction of protein and nucleic acid structure from sequence. Credits: 3 Category: Core

Genomics, Transcriptomics & Proteomics BINF 6203 (Dr. Gibas) Fall 2008 This course surveys the application and interpretation of high-throughput molecular biology and analytical biochemistry methods used to produce the kinds of high-volume biological data most commonly encountered by bioinformaticians. The relationship between significant biological questions, modern biotechnology methods, and the bioinformatics solutions that enable interpretation of complex data is emphasized. Topics include: Genome sequencing and assembly, genome annotation, genome comparison. Genome evolution. Function prediction and gene ontologies. Microarray assay design, data acquisition, data analysis. Proteomics and methods and data analysis. Methods for identification of molecular interactions. Metabolic databases, pathways and models. Credits: 3 Category: Core

Mathematical Systems Biology BINF 6204 (Dr. Su) Fall 2008 Introduction to concepts and common methods in systems biology. The class emphasizes molecular networks, models and applications, and covers the following topics: complexity and robustness of cellular systems; hierarchy and modularity of molecular interaction networks; biologically data acquisition for system level modeling; introduction to systems biology markup language (SBML); Bayesian inference of biological systems; stoichiometric and constraint-based modeling; modeling molecular interaction networks with nonlinear ordinary differential equations; quantitative approaches to the analysis of genetic regulatory networks; stochastic modeling of intracellular kinetics; multilevel modeling. Credits: 3 Category: Core

Numerical Methods in Bioinformatics BINF 6210 N/A N/A This course will focus on mathematically complex problems and show students how to implement efficient numerical methods to solve those problems. The focus on the class will depend on instructor expertise but may include: applying linear models and principal component analysis to analysis of microrarrays, application of ordinary and partial differential equations to modeling cellular pathways, applying Markov Chains to gene finding and gene predictions algorithms and application of stochastic models and Monte Carlo simulations to molecular dynamics and protein folding. Credits: 3 Category: Core

Design and Implementation of Bioinformatics Databases BINF 6211 (Dr. Weller) Spring 2008 Students will acquire skills needed to exploit public biological databases and establish and maintain personal databases that support their own research; such skills include learning underlying data models and the basics of DBMS, and SQL. Particular topics will include formats and schemas in important bioinformatics databases (Genbank, EMBL, PDB), XML schema and XML exchange methods, using CGI for the query interface, using generic database tools to browse and manage databases (Tomcat and Pgadmin), relevant database applications of SOAP and CORBA, the types of models used in designing databases, and how ontologies (such as GO) affect database design and queries. Credits: 3 Category: Core

Analysis of Microarray Data BINF 6310 (Dr. Fodor) Spring 2008 This course focuses on recent literature concerning algorithms for analysis of microarray data. The course will start with a review of normal statistics (t-test, ANOVA, etc.) and their non-parametric, robust equivalents. We then turn to primary literature for a survey of the techniques of analyzing microarray data: background subtraction, normalization across samples, assignment of p-values, evaluation of algorithms on control data sets, clustering algorithms, self organizing maps, bootstrap estimations of significance and over-representation of gene ontology terms. Special attention will be given to the problem of appropriate correction of significance for multiple measurements. Students should have fluency in a high-level programming language (PERL, Java, C# or equivalent) and will be expected in assignments to manipulate and analyze large public data sets. The course will utilize the R statistical package with the bioconductor extension. Credits: 3 Category: Elective

Biophysical Modeling BINF 6311 (Dr. Livesay) Fall 2008 This course will cover: (a) overview of mechanical force fields; (b) energy minimization; (c) dynamics simulations (molecular and coarse-grained); (d) Monte-Carlo methods; (e) systematic conformational analysis (grid searches); (f) classical representations of electrostatics (Poisson-Boltzmann, Generalized Born and Colombic); (g) free energy decomposition schemes; and (h) hybrid quantum/classical (QM/MM) methods. Credits: 3 Category: Elective

Internship Project BINF 6400 (Staff) N/A 2007 Project chosen and completed under the guidance of an industry partner, which results in an acceptable technical report Credits: 3 Category: Research

Seminar BINF 6600 (Dr. Fodor) Fall 2007 Departmental seminar. Weekly seminars will be given by bioinformatics researchers from within UNCC and across the world. Credits: 1 Category: Seminar

Journal Club BINF 6601 (Staff) Spring 2008 Each week, a student in the class is assigned to choose and present a paper from the primary bioinformatics literature. Credits: 1 Category: Seminar

Masters Thesis BINF 6900 (Staff) N/A 2007 Project chosen and completed under the guidance of a graduate faculty member, which results in an acceptable master's thesis and oral defense. Credits: 3 Category: Research