Expertise

The Biostatics and Risk Assessment Center (BRAC) is in the School of Public Health, University of Maryland at College Park. BRAC provides statistical 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 statistical 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
	Analysis of Variance and Covariance Models		Singular Value Decomposition
	Multiple imputations for missing data		Next Generation Sequencing
	Survey Design and Analysis		Analysis of Neuroimaging Data
	Propensity Scores		Microbiome Analytics