A NEW BACHELOR'S DEGREE PROGRAM IN BIOINFORMATICS

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BACHELOR OF SCIENCE


IN


BIOINFORMATICS



A Proposal for a New Interdisciplinary Major

Submitted by the

Department of Biology

Department of Computer Science

Department of Chemistry

Department of Mathematics and Statistics


March, 2004


Committee members:

Howard Laten (Biology), Ken Olsen (Chemistry), Timothy
O’Brien (Mathematics and Statistics), and
Chandra N. Sekharan

(Computer
Science), Chairperson








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BACKGROUND

The world is becoming increasingly more globalized and interconnected through
the use of
computer technology, which is pivotal to the research of numerous academic
disciplines and has been responsible for many recent advances in healthcare, finance,
medicine, commerce, and the basic sciences. Domains of scientific inquiry that depend
heavily
on computer technology will continue to grow dramatically in the next decade,
especially those domains that are most synergistic and interdisciplinary. Computer
technology has encouraged the cross
-
fertilization of ideas across traditionally disparate
areas

of learning, resulting in the formation of new fields of exploration and application.
For example, the field of computing has become a focal point for interdisciplinary
pursuits in widely diverse areas such as, business in computing, communications and
co
mputing (Loyola University’s ICT minor is an example), healthcare informatics,
computational chemistry, and computational finance. Most notably, in the previous two
decades, computer scientists, biologists, chemists, and mathematicians have launched the
di
scipline of Bioinformatics, an innovative and rich area of scientific discovery that has
the potential to dramatically change people’s lives. This proposal describes a plan to
implement a Bioinformatics major in Loyola University Chicago’s (LUC) College of

Arts and Science (CAS). The proposed major would be located at LUC’s Water Tower
Campus (WTC).

Also known as computational biology and computational genomics,
Bioinformatics is the study of mathematical, statistical, and computing methods that are
des
igned to solve biological problems by analyzing DNA, amino acid sequences, and
related genetic information.

The Human Genome Project and its ancillaries (e.g.,
proteomics, the study of the life
-
creating proteins encoded by genes) are creating
immense datab
ases of genetic information; analyses of these databases are
revolutionizing the field of biology.


Participation in this revolution requires knowledge
of the life sciences and sophisticated computer skills such as, reading large databases,
creating new so
ftware, and developing new computer code.

Experts in Bioinformatics (i.e., bioinformaticians) will be critical in conducting
such analyses and in generating new knowledge that will transform the practice of
medicine and the treatment of disease, thereby e
nhancing our prospects for longer and

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healthier lives. For example, bioinformaticians will help scientists make informed
predictions about the locations and functions of genes on a particular strand of DNA.
This information could someday be translated into

direct medical applications if disease
-
causing genes can be altered before they cause their pernicious effects.

We are proposing an interdisciplinary Bachelor of Science (BS) major in
Bioinformatics.

The CAS is uniquely qualified to offer this propo
sed interdisciplinary
major based on the expertise of its faculty and the curricular strengths of its majors in the
departments of Biology, Computer Science, Chemistry, and Mathematics and Statistics,
which are the principal contributors to the proposed Bi
oinformatics major.


These
departments already have extensive course offerings that will support the proposed major.
Bioinformatics will tie those courses together in a pedagogically rigorous and exciting
learning opportunity for LUC undergraduates. The in
terdisciplinary curriculum of the
proposed major will provide the educational experiences needed for positions in the
pharmaceutical and biotechnology industries and for future graduate studies in
Bioinformatics and other emerging areas of computer science
, biology, biochemistry, and
biostatistics.

The CAS has significant experience with undergraduate interdisciplinary
programs in the life sciences, including an Environmental Sciences major and a
Neuroscience minor. Therefore, the college is prepared to mov
e forward with the
successful implementation of a proposed major in Bioinformatics.

Across the

country
,
universities are responding to the need for Bioinformatics
professionals by initiating a variety of specialized degree programs.

In the Chicago
metrop
olitan area, however, where knowledgeable Bioinformatics professionals are
sorely needed, few educational programs are available, especially at the undergraduate
level. In contrast, elsewhere in the country, undergraduate majors in Bioinformatics are
being

offered at a number of educational institutions such as, Canisius College, Wellesley
University, California State University, the University of California at Santa Cruz, the
University of California at San Diego, Brigham Young University, Wright State
Uni
versity, and the Rochester Institute of Technology.

The Bioinformatics major at Brigham Young University, for example, was started
in 2003 and requires 62 hours of coursework: 17 hours in Biology, 10 hours in
Chemistry, 18 hours in Computer Science, and 1
7 hours in Mathematics and Statistics.

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Sample courses from the major include, Molecular Biology, Genetics,

Genomics,
Computational Biology, Bioethics, Bioinformatics, General College Chemistry,
Introduction to Computer Programming, Data Structures, Advance
d Programming
Concepts, Calculus, Statistical Theory, and Organic Chemistry. To date, the major has
accepted 41 students; it has an enrollment capacity of 50 students. (Source: Dr. Keith
Crandall, Director of Bioinformatics Program.)


The Bioinformatics ma
jor at Wellesley College requires 57 hours of coursework,
including
Introduction to Organismal Biology with Lab, Computer Programming and
Problem Solving, Introductory Chemistry with Lab, Calculus,
BioInformatics Proteomics
of Eucaryotic Cells with Lab, Da
ta Structures, Fundamental Algorithms, BioInformatics,
Organic Chemistry, Probability and Elementary Statistics
, and
Molecular Biology with
Lab. The college’s Bioinformatics major was started in 2002
-
2003 and has approximately
35 students. (Source: Dr.
Takis Metaxas, Chairperson of Computer Science.)

Baylor
University started its Bioinformatics major in 1999 and currently has 100 students. The
major requires 86 hours of coursework: 35 hours in Computer Science, 23 hours in
Biology, and 28 hours in Mathem
atics and Chemistry. (Source: Dr. Don Gaitros,
Chairperson of Computer Science.) Finally, at Canisius College, the Bioinformatics
major requires 80
-
88 hours. The major started accepting students in Fall 2002 and
currently has 10 students. (Source: Dr. Deb
ra Burhans, Director of the Bioinformatics
Program.)

MARKET AND ENROLLMENT PROJECTIONS

The Bioinformatics major will appeal to students with strong interests in biology
and computers; will add depth overall to LUC’s impressive natural science curriculum;

and will complement the university’s current course offerings in Biology, Computer
Science, Chemistry, Mathematics and Statistics.


Although a Bioinformatics major will
primarily attract new students to LUC, the curriculum also provides opportunities for
current students to pursue a cutting
-
edge educational program. Current and future career
pursuits for Bioinformatics majors are numerous, especially in healthcare firms and in
pharmaceutical and biotechnology companies. According to Dr. Martina Newell
-
Mc
G
loughlin, who chairs the life sciences informatics program for all the University of
California schools, many universities are now creating programs in Bioinformatics to

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meet the growing need for professionals in the area. Furthermore, government agencies
are providing increasing numbers of funding opportunities for research and training in the
field of Bioinformatics. Dr. Leena Peltonern, chairperson of the Department of Human
Genetics at UCLA, noted that, “there is a crying need for experts in Bioinformat
ics, and
this is not something that will just fade away.” Similarly, Dr. Barry Hamory, a partner in
the recruiting firm, SciTech, stated that “Bioinformatics is one the biggest areas of our
recruiting business,” and job candidates in the field can command
high salaries from
computer companies because of their combined skills in computer science and biology.
Hence, the field of Bioinformatics has excellent growth prospects, and its graduates will
have a wide variety of career choices. The graduates of underg
raduate Bioinformatics
programs, who are seeking advanced degrees, also will be broadly qualified for graduate
programs in biology, biochemistry, or computer science.


According to employment experts, “Bioinformatics will grow by leaps and
bounds both as a

science and as an industry in coming decades, carving out new
opportunities for businesses, drug discovery, and health care.” The job titles of persons
working in the field include: Bioinformatics Programmer, Associate Bioinformatics
Scientist, Research
Assistant in Bioinformatics, Bioinformatics Software Analyst,
Scientific Applications Manager, Bioinformatics Specialist, Genome Analyst, and
Bioinformatics Analyst. We project 25 new LUC students, each year, will be recruited
into the Bioinformatics major
.

IMPLEMENTATION PLAN

Bioinformatics will be led by a faculty director from one of the departments that
constitute the proposed major and will be administered by the CAS under the auspices of
the Dean of the CAS. The director is expected to have overarchin
g interests in sciences
and informatics and the vision required for successfully establishing and growing the
proposed major. Two additional positions for the major are sought at the rank of
Assistant Professor. One of these positions will be filled by an

individual with expertise
in Computer Science and Biology, the other with expertise in Computer Science and
Chemistry. The new faculty persons will hold joint appointments in the departments of
Computer Science, Biology, and Chemistry. The proposed major

will also be advised by
a coordinating committee consisting of the proposed major’s director, the two new

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faculty persons, and additional faculty members from each of the major’s participating
departments.

Additional Bioinformatics staff will include a ne
w computer system
administrator and a half
-
time administrative assistant. After its first six years of
implementation, the proposed major will be formally evaluated for further support and
expansion. The Bioinformatics major’s resource needs and timeline f
or implementation
are presented in the last section of the current proposal.

The Bioinformatics major will be administered at LUC’s WTC where
Bioinformatics students will take the majority of their classes. Other new majors, under
current consideration at
LUC, are planned for WTC. Therefore, we anticipate that a full
complement of CAS’s core curriculum classes will be offered at WTC as these majors are
approved. Bioinformatics students will be advised to take their CAS core courses at
WTC. In addition, the
Computer Science Major will also be located at WTC in Fall 2004,
which will facilitate and support the implementation of the Bioinformatics major.

LEARNING OUTCOMES ANDASSESSMENT

Graduates with B.S. Degrees in Bioinformatics expected to:



exhibit technica
l skills at the interface of biology, computer science, chemistry,
and mathematics;



use capably basic laboratory techniques in biology and chemistry, and
programming and exploratory techniques in computer laboratories;



demonstrate competency and problem
-
solving abilities in the computational
components of biology and chemistry;



employ basic mathematical and statistical techniques to analyze results obtained
from laboratory experiments;



understand key problems and solutions proposed during the last two dec
ades in
the bioinformatics field; and



manifest literacy for effective and ethical decision
-
making abilities in facing
issues relating to human and animal lives.

The assessment process will determine the usefulness of the Bioinformatics major
in shaping the

careers of students. The participating departments will critically assess
their course modules and laboratory exercises at the end of each academic year by
examining students’ evaluations of courses and their experiences in the major.

The

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impact of Bioinf
ormatics education will be gauged by tracking the careers of students
and the jobs that are available in the field. For example, we will collect employment
data from Bioinformatics employers (e.g. pharmaceutical and agricultural companies)
nationally, and

particularly, from those in the upper Midwest.


We will also survey
faculty persons at other institutions where our former students are continuing their
graduate studies.

The Bioinformatics coordinating committee will integrate all these
data and use them

in setting the future direction of the major.

PROPOSED CURRICULUM

Biology


1.

BIOL 101: (3 credits)

2.

BIOL 282: Genetics (3 credits)

3.

BIOL 283: Genetics Lab (2 credits)

4.

BIOL 390: Molecular Biology Lab and Lecture (4 credits)

5.

BIOL 387: Genomics new course (3 c
redits)

6.

BIOL 388: Bioinformatics (3 hours)

7.

BIOL 394: Ethical Issues in Bioinformatics (1 hour)

19 credits


Computer Science


1.

COMP 170 Intro. Programming (3 credits)

2.

COMP 271 Data Structures (3 credits)

3.

COMP 211 Discrete Structures (3 credits)

4.

COMP 363 Des
ign and Analysis of Algorithms (3 credits)

5.

COMP 171 Scripting Languages: Lab Practicum new course(1 credit)

6.

COMP 251: Database Design (3 credits)

7.

COMP 38
3 Computational Bioinformatics new course (3 credits)

19 credits


Chemistry


1.

CHEM 101: General Chem
istry (3 credits)

2.

CHEM 102: General Chemistry (3 credits)

3.

CHEM 223: Organic Chemistry (3 credits)

4.

CHEM 224: Organic Chemistry (3 credits)

5.

CHEM 111,112,225,226: Laboratories (4 credits)

6.

CHEM 361: Biochemistry (3 credits)

7.

CHEM 365: Proteomics new course (
3 credits)

22 credits


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Mathematics and Statistics


1.

MATH 131 Calculus I (3 credits) **

2.

MATH 132 Calculus II (3 credits) **

3.

STAT 335 Introduction to Biostatistics (4 credits)

4.

STAT 337 Quantitative Methods in Bioinformatics new course (4 credits)

14 c
redits


Total: 74 credits


** MATH 161, MATH 162 can be substituted for these courses.


Proposed New Courses


The following new courses are being developed for the proposed major. A syllabus
and new course form have been prepared for each and submitted
to the curriculum
committee of academic council.

1.

BIOL 394: Ethical Issues in Bioinformatics (1 credit):

The collection and
analyses of genetic information are forging unprecedented inroads into the areas
of DNA identification and manipulation, and revolut
ionizing several fields such
as, reproductive biology, health care, criminal justice, personal security, and
agriculture. Applications of knowledge in most of these areas have ethical
implications, the serious consideration of which lags far behind technol
ogical
advances in the field. This course addresses issues that must be carefully
examined in order to make ethical decisions regarding the management and
application of bioinformational data.

2.

BIOL 388: Bioinformatics (3 credits):

(already approved by
the Academic
Council) This course examines the tools of Bioinformatics and applies them to
the same kinds of problems that are presently being tackled by molecular,
medical, agricultural, developmental, and evolutionary biologists. Students will
search da
tabases and recover genes, dissect gene structures, and analyze gene
relationships within families and among taxa. The lectures will focus on genetic
concepts and tools that are essential for the competent use of computer
applications and the prudent inte
rpretation of data outputs. Additional lectures
will

discuss the nature of the computer algorithms used in the design of computer

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software in Bioinformatics and how these computer rules reflect genetic
observations.

3.

BIOL 387: Genomics (3 credits):

Genomic
s
is the study of the genome and its
actions. The term genome refers to the DNA contained in a cell including both the
chromosomes in the nucleus and the DNA in the mitochondria. Genomics
examines the inner workings of genes and their inter
-
relationships i
n order to
identify their combined influence on the growth and development of the
organism. This course introduces students to genetic mapping and
how genomes
are sequenced using computer techniques. Other topics include DNA microarrays
and genomic circui
ts.

4.

COMP 171 Introduction to Scripting Languages : Lab Practicum (1 credit):

This
course will teach students how to program computers for Bioinformatics
packages. Scripting languages are, in general, interpreted and offer an easier
alternative to de novo

programming by using feature
-
rich, traditional
programming languages. This course will cover Perl and Python, the scripting
languages of choice for bioinformatics applications.

5.

COMP 38
3 Computational Bioinformatics (3 credits):

This course will featur
e
the latest advances in computational biology and computational chemistry via
algorithms and software packages. New foundational topics are covered in graph
theory and discrete mathematics along with applications in biology and chemistry.
Some of the t
opics include: gene sequencing, pattern matching, map assembly,
gene prediction, and computational proteomics.

6.

CHEM 365 Proteomics (3 credits):

Proteomics describes and deciphers the
protein structures that are the result of biochemical interactions enco
ded in a
genome. This course will teach students how to characterize functional protein
networks and examine their dynamic alteration during physiological and
pathological processes. To understand these processes, proteins have to be
identified, sequenced,

categorized, and classified with respect to their function
and interaction in a protein network. Students will be taught a combination of
high
-
resolution protein separation techniques with mass spectrometry and modern
sequence database mining tools.


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7.

STAT
337 Quantitative Methods in Bioinformatics (4 credits):

Introductory
courses in statistics or biostatistics prepare students and researchers to perform
basic statistical analysis such as, simple linear regression or correlation, paired or
two
-
sample t
-
test
s, one
-

or two
-
way ANOVA, and analysis of covariance.


However, practitioners are often faced with other types of data for which these
methods are invalid.


Basic statistical analyses have been adapted and generalized
to categorical data techniques, genera
lized and nonlinear regression, multivariate
methods and repeated
-
measures techniques, survival analysis, cluster and tree
-
based methods, and spatial statistics. These methods are the focus of this course
and each will be illustrated with real
-
life example
s of databases and
problems.

The course will concentrate on applications, and, as such, theory will
not be emphasized. This course also covers the fundaments of experimental
design and analysis, simple and multiple linear regression, generalized linear and

nonlinear regression, multivariate analysis, including MANOVA, repeated
measures, survival analysis (e.g., Cox proportional odds, log
-
rank tests, Kaplan
-
Meier estimation), clustering techniques (e.g., Bioinformatics) and spatial
statistics.


Students will

be required to analyze real
-
life data sets using statistical
packages such as, Minitab, SAS and SPSS.

EQUIPMENT

Bioinformatics courses will use high
-
speed computer/servers with relevant
software, a server/workstation, a local area network of computers, da
tabase files, and
high
-
speed Internet connections, including Internet 2.


These features will allow students
to pursue, in a curricular context, the following activities: (a) combining overlapping raw
DNA sequences to form "contigs" and to align and compar
e related DNA or protein
sequences, (b) searching databases for sequences similar to a known sequence; (c)
recognizing motifs in DNA or protein sequences; (d) conducting phylogenetic
reconstructions based on sequence data; (e) analyzing individual characte
rs and their
effects on such reconstructions; and (f) querying and constructing customized databases.

IMPLEMENTATION SCHEDULE

The proposed major is ready for implementation in Fall 2004. The sample four
-
year schedule presented below indicates that new cour
ses for the major will begin in the

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third year of undergraduate study. Hence, we have ample time to market the major to
both current and incoming students. The new director should be hired immediately and
the two additional faculty positions should be fill
ed during academic year 2004
-
2005.
The full
-
scale marketing of the program, including the distribution of advertising
materials, should also be done in academic year 2004
-
2005.



SAMPLE FOUR
-
YEAR SCHEDULE



FALL

SPRING

YEAR 1


BIOL 101

CHEM 102 & CHEM 1
12

CHEM 101 & CHEM 111

COMP 271

COMP 170

MATH 132

MATH 131

ENGLISH 106

ENGLISH 105

COMP 171: Scripting Languages, 1 credit.


BIOL 283: Genetics Lab




16

16

YEAR 2


BIOL 282

BIOL 371: GENOMICS [ORYEAR 3]

CHEM 223 and CHEM 225

CHEM 224 and CHEM 22
6

COMP 211 Discrete Structures

COMP 363: DESIGN & Analysis of Algo.

PHILOSOPHY 120

PHILOSOPHY CORE



HISTORY CORE

THEOLOGY CORE

16

16

YEAR 3


CHEM OR BIOL 361

BIOL 388: Bioinformatics

ELECTIVE


BIOL 394: Ethical Issues in Bioinformatics
1 credit

COMP: DATABASE DESIGN

STAT: 335 Biostatistics 4 credits

STAT 337: Quant. Methods in Bioinfor.

LITERATURE CORE

ELECTIVE

THEOLOGY CORE

SOCIAL SCIENCE CORE

17

16

YEAR 4


CHEM 365: Proteomics

BIOL 390 [MB LAB] 4 credits

COMP 38
3: COMPUTATIONAL
BI
OINFORMATICS

SOCIAL SCIENCE CORE

PHILOSOPHY CORE

LITERATURE CORE

LITERATURE CORE

COMMUNICATIONS/EXPRESSIVE
ARTS CORE


12

THEOLOGY CORE

HISTORY CORE

15

16

64

64



LIBRARY RESOURCES


The following journals and books are a representative collection of reso
urces
integral to the new program. The number and type of actual library acquisitions will be
determined later.

Journals

1.

Applied Bioinformatics

2.

Applied Genomics and Proteomics (both publ
ished by Open Mind Journals)

3.

In Silico Biology

4.

Computational Methods in Molecular Biology

Books

1.

Introduction to Molecular Biology: Interdisciplinar
y Statistics by Michael S.
Waterman

2.

Bioinformatics Computing by Bryan Bergeron, M.D. (2003)

3.

Exploration and Analysis of DNA microarray and protein array data by
Amaratunga, D. and Cabrera, J. (2004)

4.

Mathematical and Statistical Methods for Genetic Analysis

by Kenneth Lange,
2nd edition (2002)

5.

Statistical Analysis of Gene Expression Data by Speed, T (ed) (2003)

6.

The Analysis of Gene Expression Data: Methods and Software by Parmiginai, G,
Garrett, E.S., Irizarry, R.A. and Zeger, S.L. (eds) (2003).

7.

Textbooks in

the syllabi for the new courses.


Resource Needs and Timeline


Description



Needed timeframe

Program Director

Fall 2004

Assistant Professors (2 new hires)

Fall 2005

System Administrator

Fall 2005

Part
-
time Secretary

Fall 2004

Computers, Misc. Hardw
are & Software:

Fall 2005


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--
Server,Printers


--
Misc. Hardware & Software


--
Networking and maintenance support




Supplies

+mailing


Fall 2004

Advertisement, Brochures

Fall 2004

Travel & Meetings
:

Fall 2005

Subscriptions

Fall 2005

Books

Fall 20
05
-
2006

Other: Faculty Start
-
Up Funds

Fall 2005
-

2006

Faculty Recruiting Costs

Fall 2004