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
Electives
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