Course Descriptions

BIOL 5376 Applied Bioinformatics (3 semester hours) Genomic information content; database searches; pairwise and multiple sequence alignment; mutations and distance-based phylogenetic analysis; genomics and gene recognition; genetic polymorphisms and forensic applications; nucleic-acid and protein array analysis; structure prediction of biological macromolecules. Lectures are augmented with laboratory exercises and demonstrations.  Introductory statistics and 2 semesters of calculus required. (3-0) Y
CS 6325 Introduction to Bioinformatics (3 semester hours) This course aims to introduce graduate students to the new field of bioinformatics. This area has arisen from the needs of biologists to utilize and help interpret the vast amounts of data that are constantly being gathered in biomedical research. This course provides an overview of the basic concepts in molecular cell biology and molecular genetics, outlines the nature of the existing data, and describes the kind of computer algorithms and techniques that are necessary to understand biomedical data. Prerequite: CS5343 Data Structure or permission of instructor (3-0) Y
BIOL 5381 Genomics (3 semester hours) The fundamentals of how the human genome sequence was acquired and the impact of the human genome era on biomedical research, medical care and genetic testing will be explored.   New tools such as DNA microarray, realtime PCR, mass spectrometry and data mining using bioinformatics will be covered.  (3-0) Y
BIOL 6373 Proteomics (3 semester hours) Protein identification, sequencing, analysis of post-translational modifications, understanding protein interactions, and changes in content by mass spectrometry; and determination of function using protein chip microarrays. (3-0) Y
BIOL 6384 Biotechnology Laboratory (3 semester hours) Laboratory instruction in LC/MS/MS mass spectral analysis of protein sequence, ICAT (isotope coded affinity tag) reagents, and MS analysis of cellular proteomes, PCR and DNA Sequencing, and DNA microarray analysis; fluorescence and confocal microscopy and fluorescence activated cell sorting.   Instructor may require students to demonstrate adequate laboratory skills in order to enroll.  (1-2) Y


A sampling of electives available to students in the Biotechnology M.S. program follows:

BIOL 6V29 Topics in Molecular Biology (2-5 semester hours) May be repeated for credit to a maximum of 9 hours. ([2-5]-0) Y
BIOL 8V50 Internship in Biotechnology/Biomedicine (3-6 semester hours). Provides faculty supervision for a students internship. Internships must be in an area relevant to the students coursework for the MS in Biotechnology. ([1-6] - 0) R
CS 5343 Algorithm Analysis & Data Structures (3 semester hours) Formal specifications and representation of lists, arrays, trees, graphs, multilinked structures, strings and recursive pattern structures. Analysis of associated algorithms. Sorting and searching, file structures. Relational data models. Prerequisites: CS 5303, CS 5333. (3-0) S
CS 6360 Database Design (3 semester hours) Methods, principles, and concepts that are relevant to the practice of database software design. Database system architecture; conceptual database models; relational and object-oriented databases; database system implementation; query processing and optimization; transaction processing concepts, concurrency, and recovery; security. Prerequisite: CS 5343. (3-0) S
CS 6363 Design and Analysis of Computer Algorithms (3 semester hours) The study of efficient algorithms for various computational problems. Algorithm design techniques. Sorting, manipulation of data structures, graphs, matrix multiplication, and pattern matching. Complexity of algorithms, lower bounds, NP completeness. Prerequisite: CS 5343 (3-0) S
CS 6372 Biological Database Systems and Datamining (3 semester hours) This course emphasizes the concepts of database, data warehouse, data mining and their applications in biological science. Topics include relational data models, data warehouse, OLAP, data pre-processing, association rule mining from data, classification and prediction, clustering, graph mining, time-series data mining, and network analysis. Applications in biological science will be focused on Biological data warehouse design, association rule mining from biological data, classification and prediction from microarray data, clustering analysis of genomic and proteomic data, mining time-series gene expression data, biological network (including protein-protein interaction network, metabolic network) mining. Prerequisite: CS 6325 Introduction to Bioinformatics or BIOL 5376 Applied Bioinformatics (3-0) Y.
ENTP 6370 Entrepreneurship (3 semester hours)This course is designed to provide an introduction to entrepreneurship for management and non-management students. There are no prerequisites for the course.  The course emphasizes the development of new ventures including technology-based ventures, addressing opportunity identification and evaluation, market assessment, startup strategies, business plan development, venture financing, and startup management. Case studies and guest lectures by practicing entrepreneurs and investors provide a real-world perspective. The major deliverable of this course is business plan (including an early stage feasibility analysis) of a venture of the student's choosing. This course is available to all graduate students enrolled at UTD (3-0 credit hours). S
FIN 6301 Financial Management (3 semester hours) Theoretical and procedural considerations in the administration of the finance function in the individual business firm; planning, fundraising, controlling of firm finances; working capital management, capital budgeting and cost of capital. Co-requisites: STAT 5311 or OPRE 6301 and AIM 6201, or consent of instructor. (3-0) S
MATH 6345 Mathematical Methods in Medicine and Biology (3 semester hours) Introduction to the use of mathematical techniques in solving biologically important problems. Some examples of topics that might be covered are biochemical reactions, ion channels, cellular signaling mechanisms, kidney function, nerve impulse propagation. Prerequisities: MATH 1471, MATH 1472, (MATH 2420 recommended) Y
STAT 5351 Probability and Statistics I (3 semester hours) A mathematical treatment of probability theory. Random variables, distributions, conditioning, expectations, special distributions and the central limit theorem. The theory is illustrated by numerous examples. This is a basic course in probability and uses calculus extensively. Prerequisite: Multivariable calculus (MATH 2451). (3-0) T
STAT 5352 Probability and Statistics II (3 semester hours) Theory and methods of statistical inference. Sampling, estimation, confidence intervals, hypothesis testing, analysis of variance, and regression with applications. Prerequisite: STAT 5351. (3-0) T
SCI 5V06/POEC 7329/HMGT 6326 Special Topics - Biomedical Ventures in the DFW Region. This course explores the industrial and commercial opportunities at the intersection of biomedical/bioengineering research and clinical activity and North Texas' industrial strengths in information and communication technologies (ICT).  The course is organized around guest presenters representing key sectors, technologies and organizations in the emerging DFW bio-economy.  Students will study how to assess the potential payoffs, measured in terms of expanded economic activity and improved patient outcomes, of adding ICT-enhanced "precision" biomedical/health services delivery to its existing industrial strengths. Students may enroll either for graduate course credit or certificate credit. (3-0) Y