Biostatistics & Bioinformatics 101: Best Practices for Cancer Data

Promoting a Rigorous and Reproducible Statistical and Bioinformatics Approach for Your Research

Understanding biostatistics and computational biology is paramount for cancer research. BIOSTATISTICS AND BIOINFORMATICS 101, BB 101: Best Practices for Cancer Data, at the University of Florida Health Cancer Center is a diverse program presented in a 12-lecture series.

The lectures introduce the basic principles of statistics, bioinformatics and computational biology, including AI. They are intended for those who are in the process of learning biostatistical and bioinformatics applications or for those who want a refresher course. Types of data, descriptive statistics, estimation, hypothesis testing, correlation/regression, survival analysis, sample size calculation/power analysis, and an introduction to bioinformatics and AI will be taught in this course series. Some classes will introduce basic theory and application of computing as a tool. Over the course, the reproducibility and replicability of scientific research will be emphasized considerably.

Course goal

This class aims to introduce the basic statistical and computational biology concepts and methods for cancer research and promote rigorous and reproducible statistical approaches for cancer research.

Who should take this course?

Clinicians, fellows, cancer researchers and cancer research-focused students. No prerequisites on graduate school-level statistical courses are required. Only UF students/employees are eligible. Exceptional cases should be discussed with the coordinator before the registration deadline.


Wednesdays from Sept. 6 to Nov. 29 (no lecture on Wed. Nov 22) | 2-3 p.m. | Virtual via Zoom

NOTE: You are welcome to attend individual lectures, but you must attend at least 10 of the 12 lectures and complete the assignments for those lectures to receive a certificate of course completion.

  • Introduction | Sept. 6
  • Estimation/Hypothesis Testing and Statistical Inferences | Sept. 13
  • Common Statistical Tests I | Sept. 20
  • Common Statistical Tests II | Sept. 27
  • Introduction to Clinical Trials | Oct. 4
  • Survival Analysis | Oct. 11
  • Sample Size Calculation I | Oct. 18
  • Sample Size Calculation II | Oct. 25
  • Introduction to Bioinformatics/Computational Biology | Nov. 1
  • RNA-Seq Analysis: Best Practices | Nov. 8
  • Single-cell RNA-Seq Analysis: Best Practices | Nov. 15
  • DNA Methylation Analysis: Best Practices | Nov. 29

Registration for fall 2023 is now closed.


Ken Thompson
Administrative Assistant

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