Computational Biology (BS)
Computational Biology (BS)
This program offered by College of Arts & Sciences/Biological
Sciences Department
• Interpret results using probability and statistics to make
conclusions. Predict if/how the interpretation might
impact individuals and/or populations globally, and
recognize potential global ethical issues. Present oral
project summary and/or written report documentation of
project.
Program Description
The bachelor of science in computational biology is a rigorous
degree designed for students who seek cross-disciplinary
education in biology, math, and computer science. The program
provides the student with a broad scientific foundation suitable
immediately upon graduation
Degree Requirements
A minimum of 128 credit hours consisting of the following:
for careers in biological information analysis in fields like:
bioinformatics, the biotechnology industry, medicine, research
in computational biology or bioinformatics, healthcare, or the
chemical and molecular disciplines.
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80 required credit hours
3 international language requirement credit hours
Applicable University Global Citizenship Program hours
Electives
Learning Outcomes
Curriculum
Upon completion of the computational biology program, students
will be able to:
Core Courses (45 hours)
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BIOL 1550, 1551 Essentials of Biology I (5 hours)
BIOL 1560, 1561 Essentials of Biology II (5 hours)
BIOL 2010 Evolution (3 hours)
BIOL 3050, 3051 Genetics (4 hours)
BIOL 4400 Research Methods (3 hours)
BIOL 4430 BS Senior Thesis (4 hours)
CHEM 1100, 1101 General Chemistry I (4 hours)
CHEM 1110, 1111 General Chemistry II (4 hours)
CHEM 2100, 2101 Organic Chemistry I (4 hours)
CHEM 3100, 3101 Biochemistry I (4 hours)
MATH 1610 Calculus I (5 hours)
Majors
• Describe and explain the core principles of biology,
chemistry, and information systems, as they relate to the
living world.
• Quantify matter, energy, and molecules of living
organisms and describe their roles in life processes.
• Describe the central dogma of biological information
storage, transmission, and expression in living
organisms.
• Explain processes underlying population diversity and
evolution.
• Analyze the origin and rationale of large datasets
and determine which molecular processes of living
organisms are informed by such data.
• Integrate the core principles of biology, chemistry,
and information systems to critique a scientific work in
writings and/or presentations.
• Locate, access, assess and manipulate large biological
datasets in a responsible manner, and identify the ethical
ramifications of the data interpretation.
• Identify what biological processes different types of
large datasets inform, and describe the advantages and
limitations of the data types.
• Be able to locate, access, format and manipulate large
datasets for computational analyses.
• Maintain a high level of honesty and integrity in all
scientific work by accurately reporting original data,
methods, and results for all experiments done.
• Give proper credit and references when using the work
of other researchers.
• Demonstrate the ability to apply relevant analyses to
biological datasets, evaluate significance, and integrate the
results with core principles.
• Use computers as a tool for doing research, gathering
data, analyzing data, and presenting results.
• Apply the scientific method to experimental design
and data interpretation; design and implement proper
controls for computational analysis and statistical
evaluation.
• Research and relate information taken from multiple
sources in the scientific literature to the use of large
datasets.
• Design and execute a research plan, interpret the results,
and communicate the scientific information in a responsible
manner, to grow as a global citizen.
• Use a dataset that informs a specific process in the life
sciences or biological information systems to formulate
hypotheses and predictions.
• Curate data responsibly; format data and perform
computational analyses.
Biology Courses (11 hours)
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BIOL 1580 Introduction to Computational Biology (1 hour)
BIOL 3600 Synthetic Biology - BioBlocks (3 hours)
BIOL 4050 Gene Expression (3 hours)
BIOL 4800 Computational Biology (4 hours)
Math and Computer Science Courses (21 hours)
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COSC 1550 Computer Programming I (3 hours)
COSC 1560 Computer Programming II (3 hours)
COSC 1570 Math for Computer Science (3 hours)
COSC 2810 Systems Analysis and Design (3 hours)
COSC 4110 Database Concepts (3 hours)
STAT 3100 Inferential Statistics (3 hours)
MATH 3610 Probability (3 hours)
One of the following courses:
• MATH 3210, Data Mining Foundations (3 hours)
• MATH 3220, Data Mining Methods (3 hours)
Admission
Students who are interested in applying to this degree program
should see the Admission Section of this catalog for general
requirements.
Webster University 2016-2017 Undergraduate Studies Catalog DRAFT
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