The Master of Science degree in CBB is no longer being offered
Core Courses
BIOL SCI 323 Bioinformatics: Biological Sequence and Structure Analysis
An introductory course exploring the principles and applications of computational tools to research problems in biology. Prerequisites: introductory-level biochemistry, protein structure and function, and some background in discrete mathematics, statistics and probability. Prerequisites: BIOL SCI 301 or equivalent, BIOL SCI 361 or equivalent, and permission of instructor.
BIOL SCI 378 Functional Genomics
Gene expression patterns and their causes.
CHEM ENG 395 Special Topics in Chemical Engineering : Networks
Special Topics in Chemical Engineering: Networks - ″What do metabolic pathways and ecosystems, the Internet, and propagation of HIV infection have in common?" Until a few years ago, the answer would have been very little. The first two examples are biological and shaped by evolution, the third is a human creation, and the fourth is an unwieldy mixture of biology and sociological components. However, in the last few years the answer that has emerged is that they all share similar network architectures.
In this course, I will define a graph. I will then define a number of quantities that can be used to quantitatively characterize the structure of any graph. I will also briefly discuss the implications of the values of some of those quantities fore the dynamics of processes taking place of the graph. An example would be to investigate whether the emergence of an epidemic on a given population depends on the structure of the graph of contacts among individuals.
I will then introduce the most fundamental network models proposed in the literature. In the second part of the course, I will demonstrate the application of network analysis to complex systems in a number of disciplines, including "Systems biology and the characterization of cellular networks," "The spread of infections," "The structure of natural ecosystems," and "Technological networks."
EECS 336 Design and Analysis of Algorithms
Discussion of fundamental concepts and techniques for designing efficient algorithms and analyzing their performance. Topics include recurrences; sorting and order statistics; dynamic programming; greedy strategies; amortized analysis; advanced data structures; linear programming; efficient reductions and computational hardness.
Contemporary large scale approaches to biological research problems; including whole-genome transcriptional profiling, proteomic analysis, and high-throughput phenotypic screening.
STAT 465 Statistical Methods in Bioinformatics and Computational Biology
The goal of this course is to provide an introduction of statistical methodologies in important topics in bioinformatics and computational biology. The major topics covered in this course include microarray gene expression data analysis; biological sequence analysis; EST and SAGE data analysis. Statistical theory or methods to be introduced in this course include Z-test, t-test, regression, ANOVA, multivariate data analysis, Bayesian statistics, bootstrap, Monte-Carlo simulation, clustering algorithms, Markov Chain, Hidden Markov Chain, mixture model, etc. The students will be trained to apply the learned tools to solve real problems in the term projects or their own research.
Seminar Series and Related Courses
CBB 460 CBB Program Seminar Series - 0 units
Students must register for the CBB Program Seminar Series each quarter of enrollment with the exception of summer. Students are required to attend and participate in presentations and discussions. Fall 2006 will focus on writing and presentation skills.
CBB 499 Projects - 3 units total
Students perform their independent research under the advice of a member of the CBB faculty. Each student conducts independent research on different aspects of a
research project in two separate laboratories over the course of their 3 quarters of independent research. The most important function of the research project is
for students to collect the necessary data required to prepare their written thesis. Faculty members and students discuss available research projects in the lab and decide on a research project.
The Laboratory Research Agreement is signed by both the student and mentor, then submitted to the
CBB Program Office along with a working title and abstract for the proposed research; at the end of each research term, the student submits a Research Report.
CBB 560 Summer Research Internship - 0 units
The Research Internship is traditionally completed during the summer term, although in special cases a student may enroll during other terms. Students work with an industry partner on a research project. As with the Independent Research Projects, at the beginning of the term students will be expected to submit a short description of the research planned for the term. Also, if the industry partner allows it, students will be expected to submit aresearch report and present a seminar describing the project and significant results at the end of the term.
Informal Seminar Programs
In addition to the formal seminar series, numerous informal seminar programs are offered within the university. These include special departmental seminars, symposia, laboratory group meetings, various journal clubs, and meetings of special interest groups, such as the Molecular Biology Club, the Biophysics Club, and the Joint Biostatistics/Bioinformatics Group on the Chicago campus. You will be contacted directly by the CBB Program if there is a seminar outside of the CBB Seminar Series that is of special interest to CBB students. Participation in such activities is considered an important part of graduate training.
