Computational Biology & Bioinformatics Capstone
CS 4884
I -- Catalog Description
Advanced topics in computational biology and bioinformatics (CBB). Teambased approach to solving open-ended problems in CBB. Projects drawn from
areas of expertise in the department, e.g., algorithms for CBB, computational
models for biological systems, analysis of structure-function relationships in
biomolecules, genomic data analysis and data mining, computational genomics,
systems biology. Design, implementation, documentation and presentation of
solutions. Pre: C or better in 3824 (3H, 3C).
Course Number:
4884
ADP TITLE: Comp Bio & Bioinfo Capstone
II - Learning Objectives
Having successfully completed this course, students will be able to:
 design a solution to a significant open-ended problem in CBB;
 design, implement, debug, and test an advanced computing system that
addresses the selected problem using skills learned in previous courses;
 choose appropriate theories and techniques to address the problem;
 judge performance/complexity tradeoffs among alternative theories and/or
methodologies in this context;
 document and present (using written, oral and visual means) the design
process and the results of a proposed solution to the selected problem;
 select an appropriate evaluation methodology to confirm that the solution
meets the design goals;
 evaluate and critically assess the proposed solution(s);
 demonstrate the ability to function effectively in teams.
III - Justification
Computational biology and bioinformatics (CBB) is an important new research
area that is emerging at the intersection of computer science and biology. There
is a high demand in both industrial and research settings for students trained in
the basics of this emerging field. This course gives a capstone design
experience for students interested in CBB. It exposes students to open-ended
problems in this area and requires synthesis and integration of state-of-the-art
methods, techniques, and tools. Successful completion of this course will help
prepare students for the complexities of solving real-world problems in CBB.
Working on the projects will enable the students to exercise and reinforce
fundamental principles they have learned in prior courses, e.g., courses in
numerical methods, data structures and algorithms.
The course activities also reinforce, via evaluated project reports and
presentations, written and oral communication skills.
The course is offered at the 4000 level since it presumes students have
successfully completed a required 3000 level prerequisite.
IV - Prerequisites and Co-requisites
Students need the introduction to CBB (including basic biological concepts and
terminology) offered by CS 3824, as well as a solid foundation in data structures,
algorithms and numerical methods, as provided by courses that are prerequisites
to 3824, e.g., CS 3114.
V - Texts and Special Teaching Aids
Specific project topics will vary, and hence the texts and teaching aids will vary.
Some example textbooks (choose one of the following):
Jones, Neil C. and Pavel A. Pevzner. AN INTRODUCTION TO
BIOINFORMATICS ALGORITHMS. Cambridge, MA: MIT Press, 2004,
454.
Fall, Christopher P., Eric S. Marland, John M. Wagner, and John Tyson,
COMPUTATIONAL CELL BIOLOGY. Berlin: Springer, 2002, 488.
Schlick, Tamar. MOLECULAR MODELING AND SIMULATION. Berlin:
Springer, 2002, 656.
VI – Syllabus
Background & foundation (topics selected from below):
 Introduction to genome biology
 State-of-art review of computer techniques
used in CBB
 Dynamic programming
 Pattern matching algorithms
 Clustering algorithms
 Tree construction algorithms
 Macromolecular structure
 Graph algorithms
 Modeling and Simulation Techniques
 Numerical methods
Identification & classification of open-ended problem(s)
Project Implementation and evaluation techniques
 Analysis of alternative designs
 Design of experimentation and evaluation
methodologies
 Synthesis of complex solutions
 Presentation of results
Feedback-driven project development
25%
Project presentation & demonstration techniques
10%
Project documentation techniques
Total
10%
100%
VII - Old (current) Syllabus
Not applicable.
VIII - Core Curriculum guidelines
Not applicable.
10%
35%
10%