UF Interdisciplinary Bioinformatics Initiative
Academic Subgroup
Academic Models
The following programs emerged as good models of bioinformatics / biomedical informatics programs:
George Mason University
• MS in Biology, Bioinformatics and Computational Biology Concentration
http://www.gmu.edu/departments/Biology/bioinformatics.htm
Housed in the department of Biology, College of Liberal Arts and Sciences
"The M.S. degree with a concentration in Bioinformatics and Computational Biology encompasses a study of the role of computation
in science, mathematics and engineering. 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 by experiments, modeling, database search, and instrumentation. Faculty from the departments of Biology, Chemistry,
Physics, Mathematics, the School of Information Technology and Engineering, the Institute for Computational Sciences and
Informatics (CSI), and the Institute for Biosciences, Bioinformatics, and Biotechnology contribute to instructional and research
components of the specialization
"Admissions Requirements: Students applying to the M.S. degree with a concentration in Bioinformatics and Computational Biology
should have a bachelor's degree in some field of the natural sciences, mathematics, engineering, or computer science with a GPA of
3.0 or higher in the last 60 hours of study. Students are expected to have competency in the biological sciences or in computational
sciences. Computational skills and biological knowledge will be evaluated during the admissions procedure. Any deficiency in these
areas will be addressed in the completion of the degree requirements.
"Degree Requirements:An advisory committee and the student will work together to develop a program of study that best meets the
student's background and interests. At least one member of the committee will be from the Biology Dept. The student must complete a
minimum of 35 graduate credits for the M.S. degree. The student must submit a program of study to the program coordinator for
approval within the first 12 credits of course work.
"Courses will be taken from the following categories:
Category 1 - Computational Sciences: A minimum of seven credits including CSI 601, 602, 603, 604 and INFS 614.
Category 2 - Bioinformatics: A minimum of nine credits including CSI 650, 651, and 652.
Category 3 - Biotechnology: A minimum of seven credits including BIOL 668 and CSI 739.
Category 4 - Individual Program Focus: A minimum of 12 credits including three credits of seminar (including BIOL 690), and six
credits of research thesis (BIOL
799) or three credits of a project (BIOL 798)."
• MS in Bioinformatics
http://www.ib3.gmu.edu/academics/mnps/bioinfo.html
One of the degree programs in the Masters of New Professional Studies program, School of Computational Sciences Price William,
which is a consortium of George Mason University, the Commonwealth of Virginia, Prince William County, and the American Type
Culture Collection (ATCC). The ATCC is the world's largest collection of living biological cultures.
"MNPS Track in Bioinformatics Course:
The MNPS with the Bioinformatics track requires 33 credits:
New Professionalism Component (12 credits)
- MNPS 700: New Professionalism: Theory and Practice (3 credits)
- MNPS 702: New Professional as a Reflective Practitioner (3 credits)
- MNPS 703: Technology and Learning in the New Professions (3 credits)
- MNPS 704: Research Methodologies in the New Professionalism (3 credits)
Lab Component (6 credits)
- MBI 533: Biotechnology I(3 credits)
- MBI 536: Biotechnology IV (3 credits)
Bioinformatics Component (9 credits)
- MBI 530: Bioinformatics Methods I (3 credits)
- MBI 531: Bioinformatics Methods II (3 credits)
- MBI 532: Bioinformatics Methods III (3 credits)
Electives (6 credits)
- CSI 601: Computational Science Tools I (1 credit)
- CSI 602: Computational Science Tools II (1 credit)
- CSI 603: Scientific Programming I: C (1 credit)
- CSI 604: Scientific Programming II: C++ (1 credit)
- CSI 605: Software Construction Tools for Scientists (1 credit)
- CSI 606: Scientific Graphics and Visualization Tools I (1 credit)
- CSI 607: Database Tools for Scientists (1 credit)"
• MS in Biotechnology, School of Computational Sciences Price William
http://www.ib3.gmu.edu/academics/mnps/biotech.html
"MNPS Track in Biotechnology
The MNPS with the Biotechnology track requires 33 credits:
New Professionalism Component (12 credits)
- MNPS 700: New Professionalism: Theory and Practice (3 credits)
- MNPS 702: New Professional as a Reflective Practitioner (3 credits)
- MNPS 703: Technology and Learning in the New Professions (3 credits)
- MNPS 704: Research Methodologies in the New Professionalism (3 credits)
Lab Component (12 credits)
- MBI 533: Biotechnology I (3 credits)
- MBI 534: Biotechnology II (3 Credits)
- MBI 535: Biotechnology III(3 Credits)
- MBI 536: Biotechnology IV (3 Credits)
Bioinformatics Component (9 credits)
- MBI 530: Bioinformatics Methods I (3 credits)
- MBI 531: Bioinformatics Methods II (3 credits)
- MBI 532: Bioinformatics Methods III (3 credits)"
• PhD in Computational Science and Informatics
http://www.scs.gmu.edu/Academics/PHD.html
"The CSI doctoral program provides research opportunities in many areas of concentration, including atmospheric transport and
dispersion; bioinformatics, computational biology, and computational neuroscience; climate dynamics and global change;
computational chemistry; computational fluid dynamics; computational mathematics; computational physics; computational statistics;
computer design of materials; earth observing and remote sensing; high-performance computing; and space sciences and
computational astrophysics. Students in the CSI doctoral program use computationally intensive methods to solve current problems in
these scientific areas.
"The list of research concentrations tells only part of the story, because the greatest strength of the CSI doctoral program lies in its
ability to foster and promote truly interdisciplinary research that crosses traditional domain boundaries. In the CSI doctoral program,
each student is presented with an exciting opportunity to create a new area of interdisciplinary inquiry that would not fit into a
traditional Ph.D. program.
"The doctoral program combines three intellectual elements:
1.core computational science topics;
2.computational intensive courses in specific scientific areas;
3.research leading to the dissertation."
Georgia Institute of Technology
• Masters of Science in Bioinformatics
http://www.biology.gatech.edu/bioinformatics/
"Georgia Tech has established a professional Masters of Science in Bioinformatics program which started in Fall 1999 with an
enrollment of 14 students.
"The degree program has been made possible through a close collaboration among the School of Biology, the School of Mathematics,
the School of Chemistry and Biochemistry, and the College of Computing. The program provides students with the practical skills and
the theoretical understanding they need to become experts in Bioinformatics.
"Students apply to the Masters Program in Bioinformatics through the School of Biology. Applicants may be admitted to the program
with undergraduate backgrounds and a BS or BA in Science or Engineering.
"Course of Study:
The Masters in Bioinformatics is a three-semester program of 37 semester hours. The course work spans the areas of Biology,
Biochemistry, Mathematics and Computer Science.
Prerequisites
- Principles of Biology (an introductory course)
- Computer Programming (at least one semester, equivalent to CS 1301)
- Organic Chemistry (an introductory course)
- Calculus (one year, equivalent to MATH 1501, 1502)
- Physics (one year)
Recommended sequence of courses:
Semester I Semester II
Course Course
Prokaryotic Molecular Genetics (BIOL 6608) Eukaryotic Molecular Genetics (BIOL
7668)
3 hours 3 hours
Biochemistry I (CHEM 6501) Biochemistry II (CHEM 6502)
3 hours 3 hours
Modeling and Dynamics (MATH 6705) Introduction to Probability and Statistics
(MATH 3215)
3 hours 3 hours
Introduction to Computing Concepts in Applications of Artificial Intelligence (CS
Bioinformatics (CS 4710) 6705)
4 hours 3 hours
Semester III Other Recommended Courses
Course Course
Bioinformatics (BIOL 7021) Bacterial and Viral Genetics (BIOL 4220)
3 hours Molecular Biology (BIOL 4469)
Molecular Biochemistry (CHEM 6573)
Applied Combinatorics (MATH 3012)
Numerical Analysis (MATH 4640)
Introduction to Algorithms (CS 6500)
Computer Graphics (CS 4451)
High Performance Parallel Computing:
Biophysics (BIOL 4178/PHYS 4251) or Tools and Applications (CS 6230)
Introduction to Graph Theory (MATH 4022) Legal Issues in Biomedical Engineering
(BMED 6788)
3 hours Technology Transfer in Biomedical
Engineering (BMED 6789)
Introduction to Database Systems (CS 4400) or
Visualization Methods for Science and Engineering (CS 6485)
3 hours
Macromolecular Structure (CHEM 6572) or
Drug Design and Discovery (CHEM 6583)
3 hours
Rennselaer Polytechnic Institute
• Bioinformatics and Molecular Biology
Undergraduate, Masters, and PhD program
http://www.rpi.edu/dept/bio/info/bioinformatics.html
"This program offers training and research opportunities in computational biology and genetic engineering. The program consists of 8
members of the Biology faculty, 5 members of the Chemistry faculty, 4 members of Computer Science and 3 members of
Mathematical Sciences. Areas of active research include computational methods for alignment, sequence analysis, protein structure
prediction, homology-based modelling, and database mining. There is also ongoing research in protein folding and design, drug
discovery, computational chemistry, enzymology and functional genomics."
Stanford University
• Stanford Biomedical Informatics Program (M.S./Ph.D.)
http://smi.stanford.edu/academics/
"Stanford University's Biomedical Informatics (BMI) training program is an interdepartmental program offering instruction and
research opportunities leading to an M.S. or a Ph.D. degree in Biomedical Informatics. The program is administratively based in the
School of Medicine. It is overseen by the Graduate Studies Committee of Stanford University, and is viewed by the Graduate Division
as a free-standing department for purposes of granting degrees. The faculty of the program, which numbers over 30 participants, is
drawn broadly from throughout the medical school, from other parts of the university, and from collaborators at the University of
California in San Francisco. Areas of investigation include diverse topics, such as decision-support systems, integrated workstations,
knowledge acquisition, electronic medical records, computational biology, knowledge representation, bioinformatics, biological
sequence analysis, biological 3D structure representation, genomics, collaborative technologies, network-based representation and
retrieval of biomedical information and literature, medical imaging, reasoning under uncertainty, medical terminology, technology
assessment, and health-services research.
"Before entering the training program, students will find it essential to have a background in integral and differential calculus, as well
as computer programming. Students with a diversity of backgrounds are encouraged to apply; for example, they might be:
- Medical students who wish to combine M.D. training with formal degree work and research experience in biomedical informatics.
- Individuals with a background in biological sciences who wish to pursue graduate training in computational biology or
bioinformatics
- Physicians who wish to obtain formal training in biomedical informatics after earning their M.D. degree or completing their
residency, perhaps in conjunction with a clinical fellowship at Stanford Medical Center
- Other health professionals (for example, nurses, dentists, pharmacists, veterinarians, medical librarians) who wish to combine
biomedical informatics with their initial area of professional expertise
- Recent B.A. or B.S. graduates who want to pursue a career applying computer science to the biomedical world
- Recent Ph.D. graduates who want formal postdoctoral training leading to a degree in BMI to complement their primary field of
training.
All students are required to complete the core curriculum listed below, and also elect additional courses
applying medical informatics methods to clinical informatics, bioinformatics, or imaging informatics.
Biomedical Informatics - 15 credits required
BMI 200 Medical Informatics Colloquia
BMI 201 Medical Informatics Student Seminar
BMI 210a (CS 270a) Introduction to Medical Informatics (first quarter)
BMI 210b (CS 270b) Introduction to Medical Informatics (second quarter)
BMI 212 (CS 271) Medical Informatics Project Course
BMI 302 Introduction to Current Research
Computer Science - 9 credits required
CS 121 Introduction to Artificial Intelligence
CS 161 Design and Analysis of Algorithms
CS 110 (or) Introduction to Computer Systems and Assembly Language Programming
CS 193* (or) series of Programming courses
EE 182 Computer Organization and Design
Decision Science and Statistics - 9 credits required
EES & OR 152 (or) Introduction to Decision Analysis
EES & OR 221(or) Introduction to Stochastic Processes and Models
STAT 116 Theory of Probability
STAT 200 (or) Introduction to Statistical Methods
STAT 201 (or) Statistical Methods
BMI 233 Intermediate Biostatistics
EES & OR 152 (or) Introduction to Decision Analysis
EES & OR 252 (or) Decision Analysis I
BMI 432 Cost-Benefit Analysis in Health Care
Biomedical Domain Knowledge - 7 credits required
BMI 205 Introduction to Biomedical Environments
BMI 204 (or) Physiology for Informaticians
Physiology 200-204 (at Physiology: Cardiovascular, Endocrine, Gastrointestinal, Renal,
least 6 credits) (or) Respiratory
BCH 200 (or) Biochemical Structure, Metabolism, and Energetics
BCH 203 (or) Molecular Biology
Surgery 101 Human Structure
Social and Ethical Issues - 6 credits required
BMI 250 (HRP 205) Health and Society
BMI 256 Economics of Health and Medical Care
BMI 432 Cost-Benefit Analysis in Health Care
CS 201 Computers, Ethics, and Social Responsibility
HRP 390 Quality in Healthcare
HRP 391 Political Economy of Health Care in the United States
HRP 392 Cost-Benefit Analysis in Health Care
• Stanford Clinical and Bioinformatics Short Courses
http://scpd.stanford.edu/smiseries.html
• Stanford Bioinformatics Certificate Program
http://scpd.stanford.edu/ce/ndp/certificate/bioinformatics.html
Yale University
http://www.yale.edu/bioinfo/