"Statistics in Cancer" Seminar

A required Biostatistics course for the trainees is the “Statistics in Cancer” seminar class, which will be held every other semester. The seminar class will be a mechanism for the trainees to interact with each other, the program director and the associate director.

This course will allow the trainees to learn about specialized topics in Cancer Research and  to see specific examples of high level biostatistics input in a Cancer Research  project. Presentations will be made by the trainees, instructor and guest speakers on current research. We will bring in Cancer statisticians to give seminars to the trainees. The trainees will have the opportunity to meet with visiting speakers.

Additional Requirements

Trainees will take the regular core and elective classes required by the Department of Biostatistics to satisfy degree requirements.  There are two additional required classes for this training program.  Trainees will be expected to take additional coursework to learn about the science and biology of cancer. 

Trainees from Epidemiology would be expected to take coursework in Biostatistics and Statistics equivalent to a MS degree.

Recommended Elective Classes
Biostat 606: Introduction to Biocomputing
Biostat 619: Clinical Trials
Biostat 675: Survival Analysis
Bioinformatics 523: Introductory Biology for Computational Scientists
Required Classes for the Program
Biostat 810: Approaches to the Responsible Practice of Biostatistics
Epidemiology 621: Cancer Epidemiology (This class can be used to satisfy the School of Public Health epidemiology requirement)

Cancer-Related Courses

Students in this training program would be required to take additional courses to bring their knowledge of molecular biology, cancer biology and cancer genetics to a higher level. The other courses required by the trainees of this training program would vary depending on the background biological knowledge of the trainees and their interest.

Potential relevant courses are listed below:

  • Epidemiology 511: Introduction to Public Health Genetics
  • Epidemiology 512: Biologic Basic of Disease Introduction to Public Health Genetic
  • Epidemiology 515: Genetics in Public Health
  • Epidemiology 516: Genomics in Epidemiology
  • Epidemiology 636: Cancer Risk and Epidemiology   Modeling
  • Bioinformatics 527: Introduction to Bioinformatics and Computational Biology
  • Bioinformatics 545: High-throughput Molecular Genomic and Epigenomic Data Analysis
  • Bioinformatics 590: Image Processing and Advanced Machine Learning for Cancer Bioinformatics 
  • Environmental Health Sciences 504: Genes and the Environment