Introduction to BioInformatics
Registration ends: TBA Price: $1,250.00 Course Unavailable

Short Course: Introduction to BioInformatics

Dates: TBA

Location: Texas Training & Conference Center; 11200 Richmond, Houston, TX

Cost: $1250/Participant, includes all course materials, meals and taxes

Discount: 20% discount for any state or federal government employee


Texas A&M University is hosting a two-day short course on the modern science of BioInformatics. This course is designed for medical professionals, managers, technicians, and researchers interested in learning more about the statistical analysis of genomic data with applications in genetic analysis, bioengineering and agriculture.

There is rapid turnover of bioinformatic algorithms and software tools in the literature, but there are a handful of key statistical principles that apply to all -omics data analyses. Understanding the basic statistics that underlies the typical bioinformatic tasks can help ground one's results in sound statistical practice, regardless of the specific -omics technology being employed. The emphasis of this short course is therefore to survey the statistical aspects of:

  1. exploratory data analysis,
  2. preprocessing and normalization,
  3. differential expression analysis, and
  4. classification, as they apply to -omics data analysis.

The course is being held in a computer classroom. During class, participants have access to work stations for reviewing example data and online resources. Computer software for BioInformatics analysis, R and its bioinformatics packages, will be provided with the course. Participants are provided USB drives with the class software for use on their home or office computers.


Day 1:

  • Gentle introduction to key topics in biology and technology
    • DNA, genes, proteins
    • Central dogma of molecular biology
    • DNA microarrays
    • Protein mass spectrometry
    • Next-generation sequencing
  • Exploring -omics data with pictures
    • Boxplots and scatterplots
    • Cluster analysis and heatmaps
    • Singular value decomposition
  • Preprocessing -omics data
    • Normalization to remove systematic biases
    • Issues with missing data

Day 2:

  • Differential expression analysis
    • Gentle introduction to h ypothesis testing
    • Assigning p-values to genes/proteins
    • False discovery rates
  • Classification
    • Gentle introductino to discriminant analysis
    • Nearest centroid classification for -omics data
    • Assigning accuracy measures to a classifier


Alan Dabney, Associate Professor; Department of Statistics; Texas A&M University

Alan Dabney

Dr. Dabney's interests are in bioinformatics and biostatistics with particular focus in proteomics, the quantitative study of proteins and how they change in complex biological systems. Shortly after graduating from the University of Washington in 2006 with a Ph.D. in Biostatistics, Dr. Dabney joined the faculty at Texas A&M University (TAMU) where he teaches bioinformatics, biostatistics and introductory statistics. He has received honors for his teaching at TAMU from the TAMU Center for Teaching Excellence.