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The Master of Science in Bioinformatics is a Professional Science Master’s (PSM) degree designed with the concept of training science professionals as part of the national effort in developing PSM degrees to enhance our future economy through promoting innovations in science and technology. Bioinformatics is an interdisciplinary science that offers unique opportunities for individuals with diverse backgrounds to learn and collaborate with others. There is an increasing demand for well-trained bioinformatics professionals capable of developing computational tools integrated with experimentation for solving complex biological problems. In addition to required coursework, students attend the weekly bioinformatics colloquium series, with research seminars and professional training workshops, and complete an internship at a bioinformatics company or research institution. Training areas include genomics data analysis, molecular modeling, and online database development, preparing graduates for various technical fields in agriculture, biodiversity and environmental science, cancer research, drug design, genetic and infectious diseases, and health data management.

Requirements for Admission

The following documents are required in the online application for admission to the Bioinformatics M.S. Program:

1.       A completed Graduate School Application form;

2.       Official copies of transcripts and GRE/TOEFL scores;

3.       A statement of purpose summarizing professional goals; and

4.       At least two letters of recommendation.

Prior to making a recommendation on acceptance to the Graduate School, the Bioinformatics Admissions Committee will review the academic preparation of applicants. Unconditional admission requires a completed bachelor’s degree that includes satisfactory undergraduate coursework experiences in Biology, Chemistry, Computer Science, Mathematics, and Statistics. This foundation is represented by the following UTEP courses and their several underlying prerequisites (or by the equivalent experience at other institutions):

BIOL 3314Molecular Cell Biology3
CHEM 2324Organic Chemistry3
CS 2401Elem. Data Struct./Algorithms4
MATH 2300Discrete Mathematics3
STAT 2480Elementary Statistical Methods4

Course descriptions and prerequisites of these courses are provided in the UTEP Undergraduate Catalog. Because this suite of foundation courses is seldom met by traditional undergraduate curricula, potential applicants should make early inquiry of the Program Director for consultation on its expeditious completion.

Degree Requirements

The Master of Science degree in Bioinformatics consists of 40-41 graduate hours comprised of required courses and electives drawn from a restricted menu. The program of study is intended to be a course-intensive experience requiring two years of full-time academic work, including a summer internship in the public or private sector between the first and second years. The internship is required of all students in the program and it can be counted as a three-credit-hour elective course. A thesis is an option but not a requirement for this degree.

I. Internship

The student is responsible for securing an internship offer from an academic, industry, or government institution that is a current or potential employer of bioinformatics professionals. For the internship to count towards the Master of Science degree in Bioinformatics, the student must obtain pre-approval from the Bioinformatics Program Committee before the start of the internship. An evaluation form will be sent to the employer at the end of the internship and the student must receive a grade of “Satisfactory” or better in order to fulfill the internship requirement of this degree.

II. Courses

Thesis courses. Six (6) hours of thesis courses BINF 5398 and BINF 5399 can be taken in place of regular elective course  to count towards the MS in Bioinformatics degree. All University requirements for master’s theses apply.

A maximum of up to six (6) credit hours of approved advanced undergraduate courses in Biology, Chemistry, Computer Science, Mathematics, or Statistics. Only undergraduate courses which are listed as applicable towards graduate degrees by the Graduate School can be counted towards the MS in Bioinformatics degree (see Graduate Catalog listings under individual departments). Approval from the Graduate Advisor is required.

With the approval of the Bioinformatics Program Committee and the Graduate School, up to six (6) semester hours of graduate work can be transferred from another accredited institution to replace equivalent courses. Only credit hours that have not been counted towards a previously awarded degree are allowed to be transferred.

Degree Plan

Required Credits: 41

MS in Bioinformatics (All courses require a grade of C or better)
BINF 5110Biology Seminar/Bioinformatics1
BINF 5111Chem. Sem. for Bioinformatics1
BINF 5112CS Seminar for Bioinformatics1
BINF 5113Math Sem. for Bioinformatics1
Required Courses:
BINF 5341Anal./Model of Bio Structures3
BINF 5351Intro. Bioinformatics I3
BINF 5352Intro. Bioinformatics II3
BINF 5354Post-Genomic Analysis3
BIOL 5340Structure/Funct Macromolecules3
CS 4342Data Base Management3
STAT 5329Statistical Programming3
STAT 5428Intro to Statistical Analysis4
BINF 5353Internship in Bioinformatics3
Select three courses from the following:
BINF 5398Thesis3
BINF 5399Thesis3
BIOL 5302Resrch Biological Science3
BIOL 5316Biosystematics3
BIOL 5326Advances Immunological Concept3
BIOL 5329Physiology of Bacterial Cell3
BIOL 5342Synthesis/Degrad Macromolecule3
BIOL 5343Mechanisms-Cellular Toxicity3
BIOL 5344Molecular Pathogenesis3
CHEM 5329Contem Topics Organic Chemistr3
CHEM 5339Contemp Topics in Biochemistry3
CHEM 5396Graduate Research in Chemistry3
CS 5334Parallel & Concurrent Program3
CS 5341Advanced Computer Architecture3
CS 5350Advanced Algorithms3
CS 5351Interval Computations3
CS 5353Topics/Emerg.Comput Paradigms3
CS 5391Individual Studies3
CS 5396Graduate Projects3
CS 5397Graduate Projects3
MATH 5330Comp Methods of Linear Algebra3
MATH 5335Techniques in Optimization3
MATH 5396Graduate Research3
STAT 5336Categorical Data Analysis3
STAT 5386Stochastic Processes3
STAT 5388Multivariate Data Analysis3
STAT 5390Nonparametric Statistics3
STAT 5391Time Series Analysis3
STAT 5392Statistical Computing3
STAT 5396Graduate Research3
Total Hours 41



Ming-Ying Leung 
Contact Information:; 915-747-6836 
Education: BS, University of Hong Kong; MPhil, University of Hong Kong; MS, Stanford University; Ph D, Stanford University