Bioinformatics Option for Statistics Majors

     Within the advent of genomics and proteomics, the biological sciences are evolving from mainly experimental sciences performed at the bench to one in which large databases of information, probabilistic models and statistical analysis techniques play a significant role. Typical probabilistic models include variance components, hidden Markov models, Bayesian networks, and coalescent. Typical statistical methods include maximum likelihood, Bayesian inference, Monte Carlo Markov chains, and some methods of classification and clustering. Stochastic modeling and statistical methods are applied to a wide range of problems from Biology, such as mapping quantitative trait loci, analyzing gene expression data, sequence alignment, and reconstructing evolutionary trees. Thus, we propose a new option within the Statistics major to provide students with a working knowledge of computing and biological sciences in order to pursue lead research in applied mathematical and statistical methodology.

    There is a need at Hunter College to prepare and train a new generation of mathematicians and statisticians capable of using computational analysis to solve important engineering problems arising from the new frontiers of biology and medicine at molecular level. The proposed curriculum will give Statistics students the necessary background in Biology and Computer Science they need for a working understanding of the subject-matter, while putting a strong emphasis on a rigorous methodological training. These students will be well prepared for bioengineering careers in bioinformatics, the pharmaceutical industry, and the biotechnology industry. They will also be well prepared for graduate studies in the mathematics and statistics of bioinformatics.

     The major core courses will remain unchanged. They are currently as follows:

MATH 254 (3 cr.) Ordinary Differential Equations -or- MATH 354 Dynamical Systems and Chaos
MATH 260 (4 cr.) Linear Algebra
STAT 212 (3 cr.) Discrete Probability
STAT 213 (3 cr.) Introduction to Applied Statistics
STAT 214 (3 cr.) Data Analysis Using Statistical Software
STAT 311 (3 cr.) Probability Theory
STAT 312 (3 cr.) Stochastic Processes
STAT 313 (3 cr.) Introduction to Mathematical Statistics

     Students are normally required to take an additional 3-credit course in statistics, mathematics or computer science approved by the undergraduate statistics advisor. In order to pursue the Bioinformatics sequence, students are required instead to complete the following computer science sequence:

Note that CHEM 102-103 and CHEM 104-105 are GER/2/E courses. 
The GER/2/E block consists of at least 7 credits.

*BIOL 200 prerequisite is recommended but not required.
**BIOL 300 prerequisite is recommended but not required.