1
BACKGROUND
The mission of the School of Computational Sciences (SCS) is to provide quality
graduate education, research and development in the sciences emphasizing the
central role of computational methodologies in the biological, physical, mathematical,
and data sciences. The educational and research programs of SCS are highly
interdisciplinary, with an emphasis on theoretical science, computer simulation, data
studies, and hardware design and development. The objective of the SCS is to
provide Virginia, and the nation as a whole, with world-class resources for attacking
the interdisciplinary research problems that characterize the challenges faced as we
move into the new millennium.
Recent advances in molecular biology have produced an avalanche of data,
including DNA sequences and genetic maps that cover thousands of genes whose
functions are poorly understood or completely unknown. These advances are
having profound effect on the biological sciences, and have resulted in the
development of the new discipline of bioinformatics.
Bioinformatics utilizes
computational approaches to create complex models of biological activity, including
attempts elucidate the functions of genes and their interactions in genetic pathways.
On a broader scale, major social benefits are expected from the exploitation of the
wealth of new knowledge becoming available concerning the genetic mechanisms of
life and related processes. For example, we expect major advances in medicine,
functional genomics, and environmental sciences, and we anticipate a general
increase in basic knowledge in all areas of biology. These benefits are increasingly
dependent on the application of information technology to the analysis of biological
information.
George Mason University was a pioneer in this area by creating in 1992 one of the
first Ph.D. programs with an emphasis in bioinformatics. Our current program has
already received international attention1. Since 1992, the field of bioinformatics has
evolved, both in scope and importance to modern biology2. To reflect the importance
that the field of bioinformatics has attained, the School of Computational Sciences
has recently received final approval for a stand-alone Ph.D. in Bioinformatics as a
formalization and extension of the existing bioinformatics track in the Computational
Sciences and Informatics Ph.D. program.
In 1999, SCS initiated an M.S. track in Bioinformatics under the University’s Masters
of New Professional Studies (MNPS) Program. There are 25 active students in the
MNPS program, and the initial class will graduate in 2002. Based on the success of
the MNPS program and the continued growth of the Ph.D. program in
Bioinformatics, we believe that the transition to a stand-alone M.S. in Bioinformatics
will address an important need for bioinformatics training and will significantly
strengthen GMU’s overall academic program in Bioinformatics.
1
2
Zauhar, H. (2001) Nature Biotech v19, p285
Hodgman, C. (1998) Bioinformatics v14, p892
2
DESCRIPTION OF PROPOSED PROGRAM
Program Mission
The innovative M.S. in Bioinformatics proposed here addresses the growing national
and regional demand for trained computational biologists. Local corporations
expected to hire graduates of the program include Celera, TIGR, Human Genome
Sciences, and Gene Logic, as well as many other firms in the region’s robust
biotechnology community. The proposed degree combines a solid foundation in
biotechnology with computational skills relevant to bioinformatics. The flexibility of
the degree structure permits students to custom-design their curriculum under an
advisor’s guidance, making the M.S. in Bioinformatics especially relevant for
students employed in today’s diverse Northern Virginia high-technology workplace.
The proposed M.S. degree is intended for:

Students seeking advancement in their current bioinformatics career.

Students with a background in biological science or computing who are planning
to enter the field of bioinformatics.

Students en route to the Bioinformatics Ph.D. degree.

Students in the Bioinformatics Ph.D. program whose career plans change, and
would benefit from the availability of a Master’s degree.
All courses are offered in the late afternoon or early evening to accommodate
students with full-time employment outside the university. Persons employed at area
biotechnology organizations may take up to six credits (out of 31) for bioinformatics
work done on the job under the guidance of a faculty member. This work-related
project may be applied either as a 3-credit research project or as a 6-credit master’s
thesis.
GMU has already developed a thriving, interdisciplinary doctoral program in
Bioinformatics as a concentration within the Computational Science and Informatics
(CSI) degree. The proposed new Masters degree is based upon a similar set of
academic principles. The new M.S. program includes a core of fundamental
bioinformatics classes as well as a flexible set of elective courses covering a wide
range of topics in molecular biology, computational biology and software
development. The majority of these classes are offered by SCS. Thus, the new
degree utilizes an extensive base of existing coursework associated with the SCS
bioinformatics graduate program.
3
Program Objectives
Bioinformatics refers to the application of information technology to the storage,
retrieval and analysis of information about biological sequences, structures and
functions. As such, bioinformatics is an inherently multidisciplinary specialty that
requires a background in both biology and computing. The M.S. in Bioinformatics is
designed to meet the challenge of preparing students with diverse backgrounds for
the field of bioinformatics. At the time of completion, students should be able to:

Evaluate quantitatively the performance of bioinformatics algorithms and tools.

Analyze, visualize, and interpret biological data.

Design and implement new computational methods to solve problems in
bioinformatics.

Work collaboratively in interdisciplinary groups.
Admission Criteria
To be considered for admission to the M.S. program in Bioinformatics, each
applicant should have the following:
1. A baccalaureate degree in biology, computer science, or related science.
2. A grade average of B or better during the last 60 hours of the undergraduate
program.
3. Three letters of recommendation, preferably from academic references or from
references in industry or government who hold advanced degrees and are
familiar with the applicant’s professional accomplishments.
4. A detailed statement of career goals and aspirations.
5. For a student whose native language is not English, a minimum score of 575 on
the TOEFL. (A minimum score of 600 is required for applicants who wish to be
considered for a graduate teaching assistantship.)
6. Submission of scores from the Graduate Record Examination (GEN).
Candidates for admission are expected to have completed undergraduate courses in
molecular biology, computer programming, probability and statistics, and calculus.
Students with deficiencies in one or more of these areas may be advised to take
additional courses from the undergraduate curriculum, according to their intended
areas of emphasis and specific backgrounds.
4
Satisfaction of the entrance requirements will be determined by the SCS Graduate
Program Coordinator in consultation with the M.S. Faculty Oversight Committee
described below.
Program Structure
The general academic requirements for completion of the M.S. in Bioinformatics are
organized into several areas:




Bioinformatics Core Courses -- foundational courses in modern biotechnology,
tools and method for bioinformatics analysis, and methods for creating
customized bioinformatics tools.
Electives -- advanced courses in biotechnology, computational science, and
bioinformatics.
Seminar/Colloquium -- 1 credit hour.
Thesis or Work-related project.
All students will undertake either a master’s thesis or a research project that allows
them to gain more extensive experience in the development of large-scale
bioinformatics systems. The research project may be based on a work-related
project performed under the supervision of a faculty member. The research project is
one of the innovative features of the proposed degree program that is likely to be
attractive to many students in the local high-technology workplace. We provide a
more detailed summary of the curriculum requirements for the proposed degree
below.
Curriculum Requirements
Candidates for the M.S. degree in Bioinformatics must successfully complete 31
credit hours as follows:
1. 12 credit hours of Bioinformatics Core Courses as follows:
•
•
•
•
MBI 533 Biotechnology I (3:1:6)
BINF 630 / MBI 530 Bioinformatics Methods (3:3:0)
BINF 634 Bioinformatics Programming (3:3:0) (new course)
BINF 734 Advanced Bioinformatics Programming (3:3:0) (new course)
2. 12-15 credit hours selected from three areas: (i) Bioinformatics and
Computational Biology, and (ii) Biology and Biotechnology, and (iii) Computational
Science, with least three credits from advanced courses in Bioinformatics and
Computational Biology. Electives may be chosen from the following lists, or from
other courses as approved by advisor:
5
Bioinformatics and Computational Biology (at least 3 credits)
•
•
•
•
•
•
•
BINF 730 Biological Sequence Analysis (3:3:0)
BINF 731 Protein Structure Analysis (3:3:0)
BINF 732 Genomics (3:3:0)
BINF 733 Gene Expression Analysis (3:3:0)
BINF 739 Topics in Bioinformatics (3:3:0)
CSI 734 Computational Neurobiology (3:3:0)
CSI 735 Computational Neuroscience Systems (3:3:0)
Bioscience and Biotechnology
•
•
•
•
•
•
•
•
•
•
•
•
•
BINF 701 Biochemical Systematics (3:3:0)
BIOL 568 Advanced Topics in Molecular Genetics (3:3:0)
BIOL 574 Population Genetics (3:3:0)
BIOL 575 Selected Topics in Genetics (3:3:0)
BIOL 579 Molecular Evolution and Conservation Genetics (3:3:0)
BIOL 680 Experimental Design and Analysis for the Life Sciences (4:3:3)
MBI 534 Biotechnology II (3:1:6)
MBI 535 Biotechnology III (3:1:6)
MBI 536 Biotechnology IV (3:1:6)
MBI 537 Forensic DNA Science I (3:1:6)
MBI 538 Forensic DNA Science II (3:1:6)
MBI 539 Forensic DNA Science III (3:1:6)
MNPS 700 The New Professionalism in Bioinformatics: Bioethics (3:3:0)
Computational Science
•
•
•
•
•
•
•
•
•
•
•
CSI 672 / STAT 652 Statistical Inference (3:3:0)
CSI 678 / STAT 658 Time Series Analysis and Forecasting (3:3:0)
CSI 700 / MATH 685 Numerical Methods (3:3:0)
CSI 703 Scientific and Statistical Visualization (3:3:0)
CSI 709 Data Mining and Knowledge Discovery (3:3:0)
CSI 710 Scientific Databases (3:3:0)
CSI 773 / STAT 663 Statistical Graphics and Data Exploration (3:3:0)
INFS 614 Database Management (3:3:0)
STAT 554 Applied Statistics (3:3:0).
STAT 662 Multivariate Statistical Methods (3:3:0)
STAT 664/SYST 664 Bayesian Inference and Decision Analysis (3:3:0)
3. Either 3 credits of BINF 798 Research Project or 6 credits of BINF 799 Master’s
Thesis. If the student chooses the Research Project, then the requirement for
Electives (category 2 above) is increased to 15 credits.
4. 1 credit hour of Seminar or Colloquium in Bioinformatics:
• BINF 704 Seminar in Bioinformatics (1:1:0)
6
• CSI 898 Research Colloquium in Bioinformatics (1:1:0)
Sample Course Schedules
Students enrolled in the interdisciplinary M.S. program in Bioinformatics will be
presented with many options as they work with their advisor to design an appropriate
curriculum, based on their background and interests. We present below a few
possible sample course schedules based on different student’s interests.
Example 1: Student Interested in Computational Biology Research
Fall Year 1:
• MBI 533 Biotechnology I
• BINF 630 Bioinformatics Methods
• BINF 634 Bioinformatics Programming
3 credits
3 credits
3 credits
Spring Year 1:
• BINF 732 Genomics
• BINF 734 Advanced Bioinformatics Programming
• BIOL 568 Advanced Topics in Molecular Genetics
3 credits
3 credits
3 credits
Fall Year 2:
• BINF 704 Seminar in Bioinformatics
• BINF 730 Biological Sequence Analysis
• CSI 703 Scientific and Statistical Visualization
1 credit
3 credits
3 credits
Spring Year 2:
• BINF 799 Master’s Thesis
6 credits
Total:
31 credits
Example 2: Student Interested in Bioinformatics Database Design
(Project Option)
Fall Year 1:
• MBI 533 Biotechnology I
• BINF 630 Bioinformatics Methods
• BINF 634 Bioinformatics Programming
Spring Year 1:
3 credits
3 credits
3 credits
7
• BINF 732 Genomics
• BINF 734 Advanced Bioinformatics Programming
• INFS 614 Database Management
3 credits
3 credits
3 credits
Fall Year 2:
• BINF 730 Biological Sequence Analysis
• CSI 709 Data Mining and Knowledge Discovery
• BINF 704 Seminar in Bioinformatics
3 credits
3 credits
1 credit
Spring Year 2:
• CSI 810 Scientific Databases
• BINF 798 Research Project
3 credits
3 credits
Total:
31 credits
Example 3: Student Interested in Forensics Biosciences Applications
Fall Year 1:
• BINF 630 Bioinformatics Methods
• BINF 634 Bioinformatics Programming
• MBI 533 Biotechnology I
3 credits
3 credits
3 credits
Spring Year 1:
• BINF 704 Seminar in Bioinformatics
• MBI 537 Forensic DNA Science I
• STAT 662 Multivariate Statistical Methods
1 credit
3 credits
3 credits
Fall Year 2:
• BINF 730 Biological Sequence Analysis
• BINF 734 Advanced Bioinformatics Programming
• MBI 538 Forensic DNA Science II
3 credits
3 credits
3 credits
Spring Year 2:
• BINF 799 Master’s Thesis
6 credits
Total:
31 credits
Relation to Other GMU Programs
The proposed program complements current GMU graduate programs related to
Bioinformatics.
8
Ph.D. in Bioinformatics: The proposed M.S. program will serve as a direct entry
point for the proposed Ph.D. in Bioinformatics program. We therefore expect an
increase in student enrollment at both the Masters and Ph.D. level, since many
students taking the M.S. in Bioinformatics can be expected to continue their studies
toward the Ph.D. at GMU.
The two new courses, BINF 634 Bioinformatics Programming
Advanced Bioinformatics Programming, will serve as additional
Bioinformatics Ph.D. program. The two existing courses required
BINF 630 Bioinformatics Methods and MBI 533 Biotechnology
toward the 48-hour course total for the Bioinformatics Ph.D.
and BINF 734
electives in the
in this program,
I will not apply
MNPS in Bioinformatics: The proposed M.S. in Bioinformatics is a natural
evolution of the successful Bioinformatics track currently offered under the
University-wide Masters of New Professional Studies (MNPS) program. The
proposed M.S. program consolidates the current MNPS Bioinformatics track with
other courses offered through in the Ph.D. program, providing a more
comprehensive combination of biotechnology and information technology courses,
as well as additional course electives in biology and computational science. Upon
state approval of this program, no more students will be admitted into the MNPS
Bioinformatics track.
Ph.D. in Biosciences: The courses offered through the M.S. in Bioinformatics
program will support of the recently approved Biosciences Ph.D. program’s
requirements for introductory bioinformatics courses.
M.S. in Biology: The proposed M.S. program will expand the range of graduate
courses available to students in the Biology M.S. program, while providing a distinct
educational experience to students seeking an advanced degree in Bioinformatics.
The proposed program differs from the Biology M.S. by its primary focus on the
computational methods of bioinformatics, including software development methods
and the in-depth study of algorithms that support bioinformatics applications.
Comparison with Other Programs in Virginia
No other Virginia institution of higher learning currently offers the M.S. degree in
Bioinformatics. Virginia Tech is planning to develop a graduate program in
Bioinformatics. Currently, Virginia Tech offers Bioinformatics degree options in
Bioinformatics in conjunction with existing Masters degree programs within several
academic departments.
Comparison with Other Programs in Washington, D.C. Region
George Washington University has recently announced a M.S. degree in Genomics
and Bioinformatics. The GWU program combines a set of biology courses and
computer sciences courses, but does not offer the specific bioinformatics courses
9
available through our program. Johns Hopkins University offers a Master of Science
in Computer Science with an option in bioinformatics or an Advanced Certificate for
Post-Master’s Study in computer science with a concentration in bioinformatics. In
both cases, the JHU program augments a traditional Computer Science program
with optional courses in computational biology. In contrast to both of these
programs, the proposed M.S. in Bioinformatics at GMU is intended to serve students
whose primary professional interest is in the area of biological applications of
computational analysis. As such, our proposed program includes more depth and a
broader range of bioinformatics analysis courses than the GWU or the JHU
programs.
Relevance of Proposed Degree for Northern VA
The Commonwealth of Virginia has a significant interest in increasing the number of
skilled workers in bioinformatics in order to attract additional biotechnology
companies to Virginia. Recent examples include the American Type Culture
Collection (ATCC), which moved to Prince William County in 1997, and the Howard
Hughes Medical Institute, which is building a computational biology center in
Loudoun County that is expected to employ up to 300 scientists. Such companies
depend on the availability of highly skilled employees, as well as the availability of
continued professional education opportunities at all levels.
The Fairfax County Economic Development Authority (FCEDA) plans to open an
8,500-square foot bioinformatics incubator in early 2002, with the goal of
accelerating the growth of start-up companies involved in bioinformatics. The
incubator will be a catalyst for growth of the bioinformatics and biotechnology
industry in Fairfax County and Northern Virginia and further diversify the Fairfax
County economic base. According to the president of the FCEDA, “ [B]ioinformatics
in the Fairfax County of 2010 [will] be the same economic force that
telecommunications and the Internet have been for the last decade, and the
Springfield incubator will be central to that vision".3 The proposed M.S. program will
directly support such economic growth in Northern Virginia.
Faculty
Currently, there are 10 SCS faculty members who teach in the Bioinformatics
doctoral and MNPS programs, in addition to several affiliate faculty from other
academic units and outside organizations. Since these faculty members are actively
participating in a doctoral program, they are fully qualified to advise and instruct
Master’s level students. Additional details for the core faculty are provided in
Appendix C. Consolidating current faculty resources associated with the existing
MNPS and Ph.D. programs in Bioinformatics will provide adequate faculty to
address the needs of the new M.S. students.
"FCEDA Selects ANGLE Technology LLC to Develop Area’s First Bioinformatics
Incubator", http://www.fairfaxcountyeda.org/oct18-01.htm.
3
10
M.S. Faculty Oversight Committee
A three-member Faculty Oversight Committee will review the progress of students
towards the M.S. degree in Bioinformatics. They will also assist the Graduate
Coordinator in the review of applicants to the program. An individual master’s degree
advisor will be assigned to each student at the time of acceptance into the program
based on the scientific interest the student indicates on the application.
EVALUATION OF PROGRAM EFFECTIVENSS
Student achievement in the existing Ph.D. program is measured in a number of
ways, as is the overall quality of the program. Many of the same assessment tools
would be used in relation to the proposed M.S. degree in Bioinformatics. Existing
assessment measures, along with their frequency of implementation and relevant
benchmarks, include:
•
Annual reviews of students’ academic progress. This includes both
coursework relative to requirements and review of thesis if the student has selected
that option.
•
Annual review of graduates’ academic outcomes.
•
Annual exit interviews with graduates to assess satisfaction with the program.
This will be analyzed in conjunction with data collected during entrance interviews to
gain additional insight into student satisfaction relative to expectations.
•
Annual monitoring of rate of acceptance to Ph.D. programs.
•
Annual data collection regarding success in obtaining or enhancing
employment.
•
Annual alumni satisfaction surveys (at least 85% satisfied or very satisfied).
•
Meeting enrollment targets (maintaining minimum of 60 students, beginning in
the third year).
The CSI Ph.D. program routinely reviews feedback from its program assessment
tools and revises policies, curriculum, and recruitment efforts accordingly. This
practice would continue with the M.S. degree in Bioinformatics. All data would be
made available for incorporation into departmental and university-wide assessment
documents.
JUSTIFICATION FOR PROPOSED PROGRAM
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Student Demand
There is evidence indicating strong student demand for the proposed degree. The
current Bioinformatics track under the MNPS program has generated a high level of
interest from potential students. In the last two years, over 250 inquiries have been
received about the MNPS Bioinformatics track. We expect that the M.S. in
Bioinformatics will attract an even larger set of potential students, because it will be
more closely associated with the Ph.D. program in Bioinformatics.
In Spring 2002, a survey was conducted of current SCS students and of people who
had requested information from the Bioinformatics web site regarding their level of
interest in a possible M.S. degree in Computational Science. Asked if they would be
interested in applying for admission into the new degree program, 71% said they
were very interested, 4% said they were somewhat interested, and 25% indicated
that they were not currently interested (mostly current Ph.D. students). The students
surveyed also indicated that they know of approximately 78 prospective students
(not currently in any SCS program) who would be interested in the new degree if it
were offered.
We are projecting an initial enrollment of approximately 15 students in the program’s
first full year (2002-2003), 29 students in the second year, 39 students in the third
year and 47 student in the fourth and subsequent years. These figures are based on
an assumed mix of 30% full-time students and 70% part-time students. We also
assume a retention rate of 95%. Details of the calculation are provided in Appendix
A, which contains the Summary of Projected Enrollments in Proposed Program.
This estimate is based on a number of factors, including the benchmark provided by
the rate of enrollment of students into the current MNPS track in Bioinformatics
(approximately 12 per year), and the pent-up regional demand for the new master’s
degree. It is also anticipated that many students currently enrolled in the
Computational Techniques and Applications certificate program offered by SCS will
find the new M.S. degree an attractive academic goal to pursue upon completion of
the certificate. The proposed degree would also serve as a terminal degree for
Bioinformatics doctoral students who do not complete the Ph.D. program (note,
however, that this may require the student to take some additional courses).
Many of the new students (as opposed to current SCS students) enrolling in the
M.S. program will be members of the local workforce who are interested in career
advancement, but are perhaps not inclined to make the commitment to a Ph.D.
program at this time.
New GMU graduates with bachelor’s degrees in undergraduate majors such as
computer science and biology, or those with an undergraduate minor in
bioinformatics (within CAS), may also be potentially interested in the degree
proposed here due to its interdisciplinary nature. We expect a significant number of
these students to apply to the new program.
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Students will be recruited via the SCS website, and via a radio campaign to begin in
April on WETA. SCS will also place advertisements in journals and newspapers.
Brochures will be prepared and sent to local biotechnology firms, including Celera,
TIGR, Human Genome Sciences, GeneLogic, SAIC, and others. Brochures will also
be sent to federal government laboratories and agencies including NIH, USDA, EPA,
and FBI. Students will also be recruited at Open House events held at GMU.
Demand for Graduates
The post-genome biology will be dominated by computational approaches to
handling data as well as to computing new relationships within the data. It is
anticipated that the computer will become the single most important piece of
equipment in the biology lab, and the next generation of biology researchers will
need to be trained in basic bioinformatic approaches.
A study for the National Academy of Science found that between 1996 and 1997 the
number of distinct bioinformatics positions advertised nationally rose 68.6 percent,
while the number of qualified graduates from formal or informal bioinformatics
training programs were sufficient to fill only 15 percent of those vacancies The
difficulties associated with filling bioinformatics positions is reflected in the salaries:
For the same time period the starting salary for bioinformatics M.S. averaged over
$65,000 while the average for the life sciences was about half that figure. The
demand continues to grow, with some projections suggesting that the bioinformatics
industry might be $2.5 billion by 2005, a 12-fold increase from today's level, requiring
as many as 20,000 additional trained workers4.
These conclusions are supported by several additional reports, including one from
the National Research Council, which states that the employment market for
bioinformatics and information technology in general is “tight and likely to remain so
for the immediate future", with "specialists in bioinformatics in great demand relative
to supply5.” In 1999, the number of people working in the biotechnology industry in
the U.S. was estimated to be 153,000, a 9 percent increase over the previous year.
A joint report from the National Institutes of Health and the National Science
Foundation states that “students who are not trained in integrated, multidisciplinary
research are at a disadvantage6.” The NIH has recognized the critical need for
4
Capitalizing on New Needs and New Opportunities: Government-Industry
Partnerships in Biotechnology and Information Technologies", National Academy of
Sciences, C. W. Wesner (Ed.) , 2001.
5 "Building a Workforce for the Information Economy", Committee on Workforce
Needs in Information Technology, National Research Council, 2001.
http://books.nap.edu/catalog/9830.html?onpi_newsdoc102400
6 "Assessing Bioengineering and Bioinformatics Research Training, Education and
Career Development", Joint Report from the NIH and the NSF.
http://grants.nih.gov/grants/bistic/NSFNIHFinalReport824.pdf
training in bioinformatics
biotechnology7.
to
support
the
continued
explosive
growth
13
in
Regionally, the demand for this degree is quite high. GMU is close to the NIH, the
USDA, and the EPA, and each agency is represented by students in the current
graduate program. Additionally, the Northern Virginia and Washington, D.C.
metropolitan areas host one of the largest concentrations of biotechnology
companies in the USA. And, as mentioned above, the Fairfax County Economic
Development Authority (FCEDA) plans to open an 8,500-square foot bioinformatics
incubator in early 2002, with the goal of accelerating the growth of start-up
companies involved in bioinformatics. All of these activities create a strong regional
demand for workes with advanced training in Bioinformatics.
Our belief is that the proposed M.S. program in Bioinformatics addresses these
needs, and will prove to be a highly competitive and demanded program.
CONCLUSION
Establishment of the proposed M.S. in Bioinformatics degree program would be
advantageous to George Mason University, the Commonwealth of Virginia, and to
the Washington, D.C. region. This program represents a consolidation of current
resources devoted to the MNPS track in Bioinformatics and the Ph.D. program in
Bioinformatics. As such, George Mason has the resources in place to support this
innovative, interdisciplinary degree, including faculty, library facilities, computer labs,
networking, and general technology support. The proposed degree program is
unique in Virginia and would complement the range of academic offerings in
Bioinformatics at GMU.
It is anticipated that the M.S. in Bioinformatics will also enhance enrollments in the
already highly successful Bioinformatics Ph.D. program by providing students with a
significant intermediate step below the doctoral level. There is substantial evidence
suggesting strong student demand for this new degree program. Sources of
applicants will include graduates of Mason’s undergraduate programs in computer
science, biology, and the new minor in bioinformatics. Graduates from other area
schools with one of these majors may also find the M.S. degree in Bioinformatics an
attractive degree in a region dominated by biotechnology-related industries and
government facilities. Graduates from the proposed M.S. program will have many
opportunities to seek or continue employment in the biotechnology field in the
Northern Virginia region. As the only school in the state to offer this innovative
degree, George Mason is well-positioned to enjoy significant student demand and in
so doing to prepare students for challenging and exciting careers.
“The Biomedical Information Science and Technology Initiative”, NIH,
http://www.nih.gov/about/director/060399.htm.
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APPENDIX A
Summary of Projected Enrollments in Proposed Program
Institution: George Mason University
CIP code:
26.0614
Initiation date:
Degree level:
Fall 2002
Associate Professor
M.S.
Enrollment target date: Fall 2005
Name of person completing this form:
Title:
Program title: Bioinformatics .
John J. Grefenstette
Phone #:
703-993-8398
.
.
.
.
Instructions:
“Target Year” refers to the year the institution anticipates the program will have achieved its
full enrollment. The Council will review for possible closure any program that has not met its own
goals within five years of program initiation. Programs that do not anticipate producing at least an
average of ten A.S., A.A., or A.A.&S. degrees, seven A.A.S. degrees, five bachelor’s degrees, three
master’s degrees, or two doctoral degrees annually after a start-up period should not be proposed.
Put the appropriate dates at the top of each column.
Provide a fall headcount and an annual FTE. Round the FTE to the nearest whole number.
Part 1: Projected enrollment:
Target Year
2002-2003
2003 - 2004
2004 - 2005
2005 - 2006
HDCT FTES
HDCT FTES
HDCT FTES
HDCT FTES
29
39
15
7
14
19
The assumptions used in determining the above figures are as follows:
95% rate of retention
30% full-time students and 70% part-time students
full-time students take 9 credit hours per semester
part-time students take an average of 4.5 credit hours per semester
full-time students graduate in two years
47
23