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Proposal for An Undergraduate Bioinformatics Curriculum for
Computer Scientists
Travis E. Doom, Michael L. Raymer , Dan Krane
Department of Computer Science and Engineering
Department of Biological Sciences
Wright State University,
Dayton, OH 45435-0001
This research was supported in part by Wright State University under
grant #241656 and in part by the National Science Foundation under
grant #EIA-0122582.
Abstract
Bioinformatics is a new and rapidly evolving discipline that has
emerged from the fields of experimental molecular biology and
biochemistry, and from the artificial intelligence, database, and
algorithms disciplines of computer science. Largely because of the
inherently interdisciplinary nature of bioinformatics research,
academia has been slow to respond to strong industry and government
demands for trained scientists to develop and apply novel
bioinformatics techniques to the rapidly-growing, freely-available
repositories of genetic and proteomic data. While some institutions are
responding to this demand by establishing graduate programs in
bioinformatics, the entrance barriers for these programs are high,
largely due to the significant amount of prerequisite knowledge in the
disparate fields of biochemistry and computer science required to
author sophisticated new approaches to the analysis of bioinformatics
data. We present a proposal for an undergraduate-level bioinformatics
curriculum.
1. Introduction
Bioinformatics explores the functional relationships between the
composition of the genes within the context of the genome and the
structure and function of the proteins encoded by these genes. Because
the interaction of the proteins within an organism determines
metabolism, reproduction, form, and health, the implications of
bioinformatics studies are far reaching. Recent advances in the
experimental techniques of molecular biology have resulted in an
explosive growth in the availability of molecular data. As a result,
current bioinformatics research is generally focused on the
representation, analysis, annotation and mining of large databases of
genome sequence information. In the future, the focus will shift to a
functional analysis of the proteins produced by these genes.
Bioinformatics techniques promise to provide information that brings
enormous power in areas ranging from disease diagnosis and treatment to
evolution, agriculture and environmental science.
There is a high demand for professionals with a background in bioinformatics. The sequencing and analysis of the human genome is one of the most complex computational problems currently being studied on a world-wide scale. Computer scientists are needed to analyze, index, represent, model, display, process, mine, and search large biological databases. This need is already extensive and will continue to grow. The genomic information available at the National Center for Biotechnology Information (NCBI) currently doubles every 14 months. Industry analysts forecast that the market for genomic information alone (and the technology to use it) will reach an annual US $2 billion by 2005 [4]. In the January 2001 issue of The Scientist, it is reported that the National Institute of General Medical Sciences (NIGMS) is already having difficulty finding people from other disciplines to perform the kind of modeling and data analysis that researchers in the biological sciences now require.
The educational opportunities available to undergraduate students
wishing to participate in this exciting enterprise are currently
limited [3]. The development of an undergraduate curriculum in
bioinformatics is essential to meeting the future needs of the
nation. The development of a bioinformatics curriculum must be
initiated immediately so that students can be a part of the basic
research of this emerging field and immediately available to meet
the workforce needs of the nation.
2. Graduate program barriers
Graduate programs in bioinformatics are beginning to emerge at several
universities, including Wright State University. Entrance requirements
for such programs, however, require students with a specific
prerequisite program of undergraduate study that is rarely made
available to students as part of an organized program. Graduate
bioinformatics programs must currently accept students with
undergraduate degrees in either computer science or biology and have
sequences of remedial or prerequisite courses designed to complement
the knowledge already acquired by the students as undergraduates.
Students holding an undergraduate degree in computer science generally
need to spend the majority of their first year of graduate study taking
focused remedial courses in basic biochemistry, molecular biology, and
genetics. Students holding an undergraduate degree in biology generally
spend the majority of their first year of graduate study in coursework
covering introductory computer science programming and basic data st
sequence on contemporary algorithms and research techniques in
bioinformatics. It is unlikely that this amount of material can be
accommodated in a two-year course of study without significant
preparation at the undergraduate level.
3. An undergraduate program solution
Due to the demanding entrance requirements, graduate programs alone
may prove inadequate in providing the number of bioinformatics specialists
that industry will require, partly because of the amount of the
remedial course-work necessary. New undergraduate programs must
be developed that incorporate a more specific (and shorter) biology
sequence with a more focused computer science foundation. It may
be necessary to redesignate some of the traditional core courses
in CS, such as formal language theory, as electives to allow for
an increased base of knowledge in the contemporary areas of IT knowledge
(such as artificial intelligence, distributed problem solving, and
data-mining).
It falls to four-year institutions to provide opportunities and direction to students to meet the market demand for bioinformatics professionals and to better prepare students for entrance into graduate-level bioinformatics programs. Implementing an academic program of study for bioinformatics is, unfortunately, complicated by its inherently inter-disciplinary nature. Programs accredited by the Computer Science Accrediation Board (CSAB) are required to include at least a two year (24 quarter hour) sequence of fundemental "core" computer science material as well as at least one year of math and one year of a laboratory science (typically physics) [2]. Biology programs typically require at least one year of study in basic chemistry. These sophomore-level courses are usually only taken after a year of study in inorganic chemistry. While an appreciation of basic chemistry concepts such as valency and electro-negativity are useful in the study of bioinformatics, we believe that an accelerated training in chemistry is sufficient and would be more accommodating to the demands of an integrated computer sciences and biology curriculum. At the same time, a streamlined exposure to introductory programming, calculus, and biology (in addition to core freshman course work) in the first two years of study is also appropriate. As bioinformaticians must be equally versed in the languages of biology and computer science, this effort will require a fundamentally interdisciplinary approach. Furthermore, basic research in the field of bioinformatics is progressing rapidly. Professionals in fields such as bioinformatics must possess not only a strong grasp of computer science fundamentals, but must also be equally comfortable in the fundamentals of biology and biochemistry to recognize and appreciate the results of their analyses.
3.1 Integration of computer science core material
Classically, computer science has focused on the study of computer
hardware and software. A more contemporary view of information
technology, however, must recognize that storage, transmission, and
presentation of data make up a significant portion of the future
demand on the discipline and on future computer professionals. This
mandates a program of study emphasizing contemporary topics in
databases and networking.
From the discipline of computer science, a bioinformatics
professional should have knowledge of: introductory programming,
data structures, AI algorithms (search, optimization, list
processing, pattern recognition, etc.), databases, formal and
comparative languages (complexity, and specialized algorithm topics
such as those explained in [1]), modeling, and simulation,
probability and statics, the WWW, visualization, and human-computer
interaction (HCI) issues.
3.2 Integration of biology core material
From the discipline of biology, a bioinformatics professional should
have working knowledge of at least one of several life sciences
fields, including genome analysis, environmental modeling, and
protein structure and function, among others. Of these many
possibilities, we propose to focus on the area of molecular
bioinformatics. A professional in this field of study should
understand genetics, molecular and cellular biology, chemical and
physical aspects of flow of genetic information from DNA to
proteins, gene expression, replication, recombination, repair, and
the experimental tools of molecular biology.
The amount of practical laboratory experience that should be
possessed by an undergraduate bioinformatician is a point of debate.
The results of DNA sequencing technology (and other in vitro and in
vivo laboratory technologies) are published, annotated, and made
available for analysis world-wide. The real problem is in extracting
meaning from the glut of available data. Computationally generated
results (in silico technologies) are becoming more prevalent in the
field.
4. A bioinformatics curriculum
We now present a curriculum proposal which is in accordance with
CSAB standards [2], yet incorporates specific (and short) sequences
in chemistry and biology with a more focused computer science
foundation. In order to meet our objectives, it was necessary to
remove several traditional, but non-essential, topics from the
computer science curriculum for this option. Knowledge of
calculus-based physics, for instance, is not as important for
students preparing for careers in bioinformatics as it is for those
interested in digital signal processing. Furthermore, many of the
traditional focuses of computer science (such as formal language
theory) that are not required CSAB standards have been made optional
to allow for an increased base of knowledge in the contemporary
areas of IT knowledge.
Computer Science - Bachelor of Science
Wright State University (Total Quarter Credit Hours: 200)
I General Education Courses (42 hours)
Area One: Communication and Mathematical Skills (8 hours)
- ENG 101-4 Composition I
- ENG 102-4 Composition II (also see required math/stat below)
Area Two: The Western Experience (15 hours)
- HST 101-3 Ancient and Medieval Eras
- HST 102-3 Western World in Transition
- HST 103-3 Modern Western World
- One Great Books of the Western World Course
- One Fine and Performing Arts Courses
Area Three: The Non-Western World (6 hours)
- One Comparative Studies Course
- One Regional Studies Course
Area Four: Understanding the Contemporary World (13 hours)
- PSY 105-4 Psychology: Studies of Behavior
- SOC 200-3 Social Life
- PLS 200-3 Political Life
- EC 200-3 Economic Life (also see required biology and chemistry below)
II Departmental Requirements (86 hours)
A. Required Computer Science and Engineering Courses (47 hours)
- CS 240-4 Computer Science I
- CS 241-4 Computer Science II
- CS 242-4 Computer Science III
- CEG 260-4 Digital Computer Hardware
- CEG 320-4 Computer Organization
- CEG 360-4 Digital Systems Design
- CS 400-4 Data Structures and Software Design
- CS 405-4 Intro to Database Management Systems
- CS 409-4 Principles of Artificial Intelligence
- CS 415-3 Social Implications of Computing
- CEG 433-4 Operating Systems
- CS 480-4 Comparative Languages
B. Required Biology Courses (28 hours)
- BIO 112-4 Principles of Biology: Cell Biology and Genetics
- BIO 114-4 Organismic Biology
- BIO 115-4 Principles of Biology: Diversity and Ecology
- BIO 210-4 Molecular Biology I
- BIO 211-4 Molecular Genetics I
- BIO 302-4 Genetics and Change
- BIO 410-4 Cell-Molecular Biology Laboratory
C. Required Bioinformatics Courses (8 hours)
- BIO/CS 2xx-4 Intro to Bioinformatics
- BIO/CS 4xx-4 Computational Molecular Biology
D. Technical Communications (3 hours)
Choose one:
- EGR 335-3 Technical Communications
- BIO 310-3 Issues in Science
III Required Supporting Courses (56 hours)
Area A: Chemistry (33 hours)
- CHM 121-5 Submicroscopic Chemistry
- CHM 122-5 Macroscopic Chemistry
- CHM 123-5 Reaction Dynamics
- CHM 211/215-6 Organic Chemistry I
- CHM 212/216-6 Organic Chemistry II
- CHM 213/217-6 Organic Chemistry III
Area B: Mathematics (23 hours)
- MTH 229-5 Calculus I
- MTH 230-5 Calculus II
- MTH 253-3 Elementary Matrix Algebra
- MTH 257-3 Discrete Mathematics for Computing
- HFE 301-4 Statistics I
- MTH 407-3 Optimization Techniques
IV CS/Bio/MTH Electives (16 hours, at least 8 of which must be 400-level CS/CEG)
Choose from:
- BIO 212-4 Cell Biology I
- BIO 252-5 Microbiology
- BIO 403-5 Developmental Biology
- BIO 406-3 Evolutionary Biology
- BIO 426-4 Human Genetics
- BIO 437-6 Recombinant DNA Methods
- BIO 461-3 Molecular Evolution
- BIO 469-3 Population Genetics
- BMB 421-4 Biochemistry I
- BMB 423-4 Biochemistry II
- BMB 427-4 Biochemistry III
- CEG 255-4 Intro to the Design of Information Tech. Systems
- CEG 416-4 Matrix Computations
- CEG 434-4 Concurrent Software Design
- CEG 465-4 Interactive Systems Modeling, Analysis, and Design
- CEG 466-4 Formal Languages
- CEG 476-4 Computer Graphics I
- CEG 477-4 Computer Graphics II
- CS 470-4 Systems Simulation
- CS 458-3 Applied Graph Theory
- CS 459-3 Combinatorial Tools for Computer Science
5. Conclusion
Computer science is a path to understanding genomes just as biology
helps us in understanding living organisms. It is hard to imagine a
more significant area where we must hone our methods of questioning
than bioinformatics. The competitive pressure and rewards for
progress in bioinformatics are high, and students can use them to
prepare themselves to join this sought-after work-force. The
creation of an undergraduate bioinformatics option in computer
science and engineering is of utmost importance for global health,
the economic development of those nations undertaking this path,
and the success of our students.
The central argument that we present for an undergraduate
bioinformatics option within a Computer Science BS degree can be
summarized as follows: (1) The number and chain of prerequisites
that must be satisfied in either case requires about two years of
course-work because course dependencies are such that they cannot
be taken in parallel. (2) This being the case, an assumption of two
years of prerequisites, in addition to the two years to obtain the
MS degree, implies that it could take eight years of preparation
for a student to obtain an MS degree in bioinformatics. (3) The
alternative that we propose would lead to a BS degree in four years
and an MS degree in the standard six year time frame. Our proposed
curriculum includes, in addition to traditional computer science,
biochemistry, and molecular biology components, several courses
tailored specifically to meet the needs of an integrated
interdisciplinary program. One such course is an undergraduate
introduction to bioinformatics algorithms and methods. As this
course will serve as a unifying element for the rest of the
bioinformatics program, Drs. Krane and Raymer have formalized the
proposed course content and are currently preparing and
undergraduate bioinformatics textbook to be published by
Benjamin-Cummings in December, 2002.
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