Bioinformatics and Biostatistics MS

The Bioinformatics and Biostatistics MS program educates and trains bioinformatics and biostatistics scientists to collaborate with researchers in the basic, medical and clinical sciences; to conduct methodological research; to collaborate with local, state or national health institutions; and to serve our institute, university and the bioinformatics, biostatistics, and health-care professions. In addition to their classroom studies, the program’s students have opportunities to gain practical training through mentored, hands-on data analyses in the context of exciting biological, medical and health science research projects.

Required Core (21 credits)

STA 502LEC - Intro Stat Inference Credits: 3
or
STA 521LEC - Intro Theoretical Stat 1 Credits: 3
STA 509LEC - Statistical Genetics Credits: 3
STA 511LEC - Advanced Statistical Computing Credits: 3
STA 525LEC - Stats for Bioinformatics Credits: 3
STA 545LEC - Statistical Data Mining I Credits: 3
STA 546LEC - Data Mining II Credits: 3
STA 782SEM - Departmental Seminar Credits: 0
CHB 550LEC - Pub Hlth Popultn Wellbng Credits: 3

Electives (12 credits)

Select 4 courses, not previously taken, from:

BCH 519LEC - Bioinformatics & Comp Bio Credits: 3
or
CSE 503LR - Computer Science for Non Majors Credits: 3
CSE 536LEC - Computational Biology Credits: 3
CSE 562LEC - Database Systems Credits: 3
CSE 601LEC - Data Mining and Bioinformatics Credits: 3
STA 503LEC - Introduction to Applied Statistics I Credits: 3
STA 504LEC - Introduction to Applied Statistics II Credits: 3
STA 517LEC - Categorical Data Analysis Credits: 3
STA 521LEC - Intro Theoretical Stat 1 Credits: 3
STA 522LEC - Intro Theoretical Stat 2 Credits: 3
STA 526LEC - Design and Analysis of Clinical Experiments Credits: 3
STA 531LEC - Sample Survys Thery-Meths Credits: 3
STA 536LEC - Statistical Design and Analysis of Experiments Credits: 3
STA 561LEC - Longitudinal Data Analysis Credits: 3
STA 571LEC - Spec Top in Statistics Credits: 3
STA 575LEC - Survival Analysis Credits: 3
STA 581LEC - Multivar Data Analysis Credits: 3

Culminating Experience: Project or Thesis (3 credits)

STA 601TUT - Project Guidance Credits: 1 - 6
STA 700TUT - Thesis Guidance Credits: 1 - 16

Total Credit Hours: 36

3.0 Degree GPA required

Program Learning Outcomes (PLOs)

1) Communicate statistics and bioinformatics results effectively to an identified audience in writing and orally.

2) Work with probability and random variables in practice and in theory

3) Use and explain basic theories of statistical inference as applied to problems in genetics and bioinformatics

4) Use and explain linear (simple and multiple) and logistic regression

5) Apply prediction models and machine learning to bioinformatics or informatics data

6) Use one or more statistical packages including Bioconductor to perform standard bioinformatic analyses

SED Statement

This program is officially registered with the New York State Education Department (SED).