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