The Biostatics and Risk Assessment Center (BRAC) will provide biostatistical and bioinformatics assistance that can increase the productivity and scientific value of each study with which it is asked to collaborate. The following is a sample list of biostatistical and bioinformatics methods within BRAC's domain of expertise:

 

Biostatistics

 

Bioinformatics & Data Mining

 
  • Quantitative Risk Assessment
 
  • Significance Analysis of Microarrays
 
  • Survival Analysis with Censored Data
 
  • False Discovery Rates
 
  • Mixed and Random Effects Models
 
  • Multiple Comparisons
 
  • Longitudinal Data Analysis
 
  • Analysis for SNPs, aCGH Data
 
  • Generalized Linear Models and Logistic Regression
 
  • Linkage Analysis and Genetic Association Studies
 
  • Categorical Data Analysis
 
  • Analysis of LC-MS/MS, MALDI/ToF Data
 
  • Analysis of Dose-response and Toxicity Data
 
  • Analysis of Genomic Sequences Data
 
  • Analysis of Exposure Data
 
  • Genome-wide Association Studies
 
  • Analysis of Reliability Data
 
  • Hidden Markov Models (HMM)
 
  • Analysis of Infectious Disease Data
 
  • Supervised Machine Learning
 
  • Analysis of Vaccine Data
 
  • Unsupervised Machine Learning
 
  • Design and Analysis of Clinical Trials Data
 
  • Hierarchical Cluster Analysis
 
  • Analysis of Quality-of-Life Data
 
  • Discrimination and Classification
 
  • Meta Analysis
 
  • Artificial Neural Networks
 
  • Latent Variable Models and Causal Analysis
 
  • Support Vector Machines
 
  • Statistical Issues in Experimental Design
 
  • Self-Organizing Map
 
  • Sample Size and Power Considerations
 
  • Bagging, Boosting, and Classification Trees
 
  • Nonparametric and Semi-parametric Statistical Methods
 
  • Sequence Analysis of Nucleic Acids and Proteins
 
  • Empirical Bayes and Hierarchical Bayes Models
 
  • Principal Component Analysis, Singular Value Decomposition
 
  • Analysis of Variance and Covariance Models
   
 
  • Multiple imputations for missing data