Statistics Majors
Bioinformatics Option for Statistics Majors
Goal Curriculum Sequence Advisors
Purpose and Goals
With 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. The quantitative biology concentration within the Statistics major will provide students with a working knowledge of computing and the biological sciences in order to pursue 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 the molecular level. This curriculum will give Statistics students the necessary background in Biology and Computer Science that 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.
Statistics QuBi concentrators will be able to explore, summarize, produce and interpret graphical representations of as well as implement probabilistic models and make statistical inference from biological/omics data.
The Department of Mathematics & Statistics also has an MA program in Statistics and Applied Mathematics with track III in Bioinformatics
Statistics QuBi concentrators will be able to explore, summarize, produce and interpret graphical representations of as well as implement probabilistic models and make statistical inference from biological/omics data.
The Department of Mathematics & Statistics also has an MA program in Statistics and Applied Mathematics with track III in Bioinformatics
Curriculum
Major Entry Requirements – 8 credits
MATH 150 (4 cr.) Calculus with Analytic Geometry IMATH 155 (4 cr.) Calculus with Analytic Geometry II
Major Core Curriculum – 29 credits
MATH 250 (4 cr.) Calculus with Analytic Geometry IIIMATH 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
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:
Computing Component – 6 credits
CSCI 132 Practical UNIX and Programming (3 cr.) (NEW)
CSCI 232 Relational Database & SQL (3 cr.) (NEW)
Students will also take the following natural science courses, which will fulfill the requirements for a minor in Biology or in Chemistry:
Chemistry Component – 12 credits
CHEM 102 General Chemistry I (3 cr.)CHEM 104 General Chemistry II (3 cr.)
CHEM 106 General Chemistry Lab (3 cr.)
CHEM 222 Organic Chemistry (3 cr.)
CHEM 106 General Chemistry Lab (3 cr.)
CHEM 222 Organic Chemistry (3 cr.)
Note that CHEM 102 and CHEM 104-106 are GER/2/E courses. The GER/2/E block consists of at least 7 credits.
Biology Component– 12 credits
BIOL 100 Principles of Biology I (4.5 cr.)
BIOL 203 Molecular Biology and Genetics (4.5 cr.)
BIOL 425 Computational Molecular Biology (3 cr.)
BIOL 203 Molecular Biology and Genetics (4.5 cr.)
BIOL 425 Computational Molecular Biology (3 cr.)
TOTAL CREDITS – 67 CREDITS
Sample Course Sequence*
*Please see a QuBi advisor for individualized course plans
| Fall (Year 1) – 7 credits GER/1/B: MATH 150 GER/2/E: CHEM 102 |
Spring (Year 1) – 10 credits MATH 155 GER/2/E: CHEM 104-106 |
Fall (Year 2) – 11.5 credits STAT 212 MATH 250 BIOL 100 |
Spring (Year 2) – 10 credits MATH 254 or 354 MATH 260 STAT 213 |
Fall (Year 3) – 9 credits STAT 214 STAT 311 CSCI 132 |
Spring (Year 3) – 9 credits STAT 312 CSCI 232 CHEM 222 |
Fall (Year 4) – 4.5 credits BIOL 203 |
Spring (Year 4) – 6 credits BIOL 425 STAT 313 |
Faculty Adviser
Dr. Ronald Neath, (212) 396-6044, rneath@hunter.cuny.edu
Acknowledgments
National Institutes of Health (NIH)/MARC Program
Howard Hughes Medical Institute (HHMI)
Center for the Study of Gene Structure and Function
National Institutes of Health (NIH)/MARC Program
Howard Hughes Medical Institute (HHMI)
Center for the Study of Gene Structure and Function