2001-2002 University Catalog -- George Mason University 2000-2001 Catalog

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School of Computational Sciences



The School of Computational Sciences (SCS) results from the recent merger of the Institute for Computational Sciences and Informatics and the Institute for Biosciences, Bioinformatics, and Biotechnology. This new school serves as the primary academic unit providing scientific and applications content to George Mason's information technology focus. This content includes applications in the biological, physical, mathematical, and data sciences. Along with other units, SCS also contributes to the university's focus on educational and research programs related to the environment.

Through its interdisciplinary and multidisciplinary activities, SCS seeks to integrate computation in the sciences, mathematics, and engineering to produce new knowledge and to develop new approaches to the solution of complex problems. SCS maintains extensive facilities on both the Fairfax and Prince William Campuses.

Faculty

Barnes, Beall, Becker, Black, Blackwell, Blaisten-Barojas, Carr, Cebral, Ceperley, Chiu, Davis, Denning, Dworzecka, Ehrlich, El-Ghazawi, Ellsworth, Emerson, Evans, Foster, Gentle, Gillevet, Grefenstette, Guillory, Haack, Hanna, Hertz, Jamison, Jones, Kafatos, Kerschberg, Kinser, Lieb, Lin, Lohner, Manitius, McCormack, McKenney, Michalski, Miller, Mishin, Morowitz, Mushrush, Nash, Norris, Ozernoy, Papaconstantopoulos, Rine, Sachs, Sambruna, Saperstone, Satija, Sauer, Schopf, Seto, Shukla, Solka, Sood, Soyfer, Spikell, Struppa, Summers, Sutton, Vaisman, Walbridge, Wallin, Wang, Wechsler, Wegman, Willett, Williams, Wong, K. Wood, C. Yang, R. Yang, Zoltek

Course Work

The School of Computational Sciences offers all course work designated Computational Sciences and Informatics (CSI) or Molecular Biosciences and Informatics (MBI) in the "Course Descriptions" chapter of this catalog.

Graduate Programs

The School of Computational Sciences offers a Ph.D. in Computational Sciences and Informatics, a certificate in computational techniques and applications, an M.S. in New Professional Studies: Bioinformatics; an M.S. in New Professional Studies: Biotechnology; and an M.S. in New Professional Studies: Forensic Biosciences.

Admission Requirements

Applicants to either the doctoral program in computational sciences and informatics or the certificate program in computational techniques and applications should have academic backgrounds in material sciences, engineering, mathematics, computer science, or natural science. They should have undergraduate degrees from accredited institutions, with GPAs of at least 3.000 in their last 60 credits of study. In addition, each applicant seeking full admission to either the doctoral or certificate program should take at least one course in ordinary differential equations.

Applicants to the new professional studies program should have undergraduate or advanced science degrees in areas such as biochemistry, biology, chemistry, computer science, or molecular biology, with GPAs of at least 3.000 in their last 60 credits of study.

To apply, each prospective student should forward a completed George Mason graduate application, two transcripts from each college and graduate institution attended, a current resume, and an expanded goals statement to the Graduate Admissions Processing Center. Each doctoral or master's program applicant should also include three letters of recommendation. (Note: Transcripts originating from foreign countries must be evaluated by a U.S.-recognized agency.)

In addition, each doctoral program applicant should include scores from the GRE-GEN. The GRE-SUB is recommended if it is given in the student's undergraduate major. The GRE requirement for admission to the doctoral program is waived if the student holds a master's degree from a U.S. institution. TOEFL scores are required for all foreign applicants.

Fellowships and assistantships are generally available beginning in the fall semester. Those applying for fellowships and assistantships must submit completed applications by February 1 for fall admission; all other applications for fall admission are due by March 1. The CSI doctoral program accepts spring applications through November 1 of the preceding year.

Computational Sciences and Informatics, Ph.D.

The computational sciences and informatics (CSI) doctoral program addresses the role of computation in science, mathematics, and engineering, and is designed around a core of advanced computer technology courses. "Computational sciences" is defined as the systematic development and application of computing systems and computational solution techniques to models of scientific and engineering phenomena. "Informatics" is defined as the systematic development and application of computing systems and computational solution techniques for analyzing data obtained through experiments, modeling, database searches, and instrumentation. Computing is now part of a triad, along with theory and experimentation, that serves as a means of investigation, and it provides insight and leads to understanding that, in many cases, theory or experimentation cannot. The close
relationship of the CSI doctoral program to the research and development activities in federal laboratories, scientific institutions, and high-technology firms affords students opportunities for continuing or new employment. To be eligible for full admission into the CSI doctoral program, prospective students should take at least one course in ordinary differential equations, and should have knowledge of a programming language.

Each student completing the CSI doctoral program receives extensive training in a selected area of scientific concentration along with a broad background in modern computational techniques. Graduates from this program are qualified to pursue careers in academia, private industry, and many government laboratories and agencies. The CSI doctoral program provides interdisciplinary research opportunities spanning, but not limited to, the following specialty areas: atmospheric transport and dispersion; bioinformatics and computational biology; climate dynamics and global change; computational chemistry; computational finance; computational fluid dynamics; computational intelligence and knowledge mining; computational mathematics; computational neuroscience; computational physics; computational statistics; computer design of materials; earth observing and remote sensing; and space sciences and computational astrophysics.

DEGREE REQUIREMENTS

The program emphasizes three intellectual elements: common computational science topics; computationally intensive courses in specific areas of interest; and doctoral research. The course work is divided as follows:

  • The common computational core courses: CSI 700, 801, 803, and 810

  • The scientific core courses in one of the areas of concentration

  • Scientific electives from specialty courses in the area of concentration, or individualized study based on professional experience and research

  • General electives

  • Three credits of colloquia or seminars, with at least one credit of CSI 899

The program requires 72 credits beyond the baccalaureate degree, with a minimum of 48 credits in course work, and 24 credits of dissertation research. For those holding master's degrees, the 72 required credits may be reduced by up to 24 credits, depending on graduate courses completed. Scheduled courses and sequences accommodate part-time students, with courses offered in the late afternoon or early evening four nights per week.

Applicants are encouraged to apply their knowledge to a broad range of natural science problems using computational skills and techniques missing from the more traditional degree programs in science and mathematics. Note that research opportunities are not limited to the listed areas. Students are presented with the opportunity to create new areas of interdisciplinary research that would be difficult to accommodate within a traditional doctoral program. Students are to consult with their advisors to prepare their specific plans of study. Complete information regarding the curriculum requirements (including electives) for each of the areas of concentration is available at the School of Computational Sciences web site through the university's main page at www.gmu.edu. In addition to the common core of CSI 700, 801, 803, and 810, required scientific core courses for the specific areas of concentration are indicated in the following list.

Atmospheric Transport and Dispersion: CSI 655 and 755

Bioinformatics and Computational Biology: CSI 730, 731, and 732

Climate Dynamics and Global Change: CSI 751; CSI 752 or 756; CSI 755; and CSI 852

Computational Chemistry: CSI 711, 713, 782, and 783

Computational Finance: STAT 652 and 656; CSI 771 and 776; and two courses in finance

Computational Fluid Dynamics: CSI 721; CSI 722; CSI 780; CSI 783 or 784; and CSI 785 or PHYS 513

Computational Intelligence and Knowledge Mining: CSI 771, 773, SYST 781, and IT 811

Computational Mathematics: CSI 740, and MATH 677 or 678

Computational Neuroscience: CSI 630, 631, 734, and 735

Computational Physics: CSI 780; CSI 783 or 784; CSI 785 or PHYS 513; and one of CSI 782, 783, 784, 888, or PHYS 705

Computational Statistics: CSI 771 or 773; CSI 778; CSI 876 or 877; CSI 972; and CSI 973

Computer Design of Materials: CSI 687; CSI 780; CSI 782; CSI 783; CSI 785 or 986; and CSI 786

Earth Observing and Remote Sensing: CSI 750, 753, 754, and 757

High-Performance Computing: CSI 709, 909, and one of CSI 721, 754, 761, or 788

Space Sciences and Computational Astrophysics: CSI 661; CSI 780; CSI 783 or 784; CSI 785 or PHYS 513; and one of CSI 721, 761, or 788

New Professional Studies, M.S.

SCS offers three tracks in the new professional studies program: forensic biosciences, bioinformatics, and biotechnology. The master's degree provides graduate education for professionals working at the interface of information technology and the biological sciences. As such, the program content is geared toward persons employed in science-based organizations that require bioinformatic and bioscience skills and expertise.

The degree incorporates action-oriented group learning as a way to integrate theory and practice. Grouped into teams, candidates are immersed in the practical problems of organizations while engaging with each other through collaborative technologies. By dealing with practical organizational issues, participants gain deeper insight into how complex organizations work and how to affect them. The program produces a tightly integrated learning experience and focuses on building a learning community.

DEGREE REQUIREMENTS

Each of the three tracks requires a minimum of 33 credits. Four core courses (MNPS 700, 702, 703, 704) are required of all tracks. In addition to the minimum 33 credits, all students are required to take or to have met the requirements of CHEM 663-664 Biochemistry (6 credits). In addition to the core courses, the following courses are required for each track:

Forensic Biosciences: MBI 530, 531, 533, 534, 537, 538, and 539

Bioinformatics: MBI 530, 531, 532, 533, 536, and six credits from CSI 601-607

Biotechnology: MBI 530, 531, 532, 533, 534, 535, and 536

Certificate in Computational Techniques and Applications

SCS offers a graduate certificate program in computational techniques and applications, which provides students an opportunity to improve their basic computational skills. The certificate is independent of the doctoral program and is designed primarily for professionals in technical fields who may wish to upgrade their computer expertise, but it is also available as an option for prospective and currently enrolled doctoral students. To be eligible for full admission into the certificate program, prospective students should take at least one course in ordinary differential equations and one course in computer science. The certificate program is composed of 15 credits of course work designed to provide an accelerated introduction to concepts in modern computation. Topics include operating systems, environments, languages, graphics, databases, and applications.

Nondegree status is available for professionals who are interested in taking a limited number of courses.

Facilities

Computation is recognized as a central feature of the instructional and research programs of SCS. The school, therefore, continues to establish world-class computational facilities. In addition, high-speed Internet connections permit interactive distance learning and access to remote databases.

The Fairfax Campus offers instruction in all areas of the SCS curriculum, and provides state-of-the-art computational laboratories and electronic classrooms for research and interactive instruction. The SCS Graduate Instructional Computational Facility houses 24 Silicon Graphics workstations clustered with a 100 GB RAIDS system. These machines are configured with state-of-the-art software for symbolic manipulation, modeling, simulation, data analysis, database management, and data visualization. Other advanced computing platforms within SCS include a high-performance parallel PC cluster with 134 processors, an SGI Origin 2000 workstation with 16 processors, an SGI Origin 200, an SGI Onyx with infinite reality graphics engine, and an Octane visualization workstation. SCS students are issued computer accounts and access to the SCS instructional facilities. Other computing platforms are available for research by graduate students.

SCS facilities on the Prince William Campus are partially shared with the American Type Culture Collection, the world's largest collection of living biological cultures. Facilities include molecular biology and biochemistry labs, computer labs, cold rooms, and instrument rooms, as well as faculty offices. Available computer facilities include more than 60 SGI workstations, including a four-processor Onyx, 18 Octanes, and more than 40 O2s. An SGI Origin 200 provides more than 65 GB of high-availability RAID disk storage. Other computational resources include SUN SparcStations, Macs, and PCs. All computers are connected via a high-speed (100 MB/sec) Ethernet LAN. Teaching facilities include three computer classrooms equipped with SGI workstations configured with advanced bioinformatics, visualization, and data-mining software. Three wet labs for teaching and training are supported by adjacent computer labs, lecture rooms, prep labs, and equipment labs, including three ABI 377 and two ABI 310 automated DNA analyzers.


George Mason University: 2001-2002 University Catalog: Catalog Index: School of Computational Sciences