The overall objectives of this core are to enhance the productivity of CIDD investigators and the quality of their research. The core can assist IDDRC projects with study design, data management, and statistical analysis. This assistance has ranged from simple consultation to answering specific data management or analysis questions, to collaborative involvement from the design stage through proposal writing, data collection and management, to the publication of results.
Fei Zov, Ph.D.
Margaret R. Burchinal, Ph.D.
Jeremy Simon, Bioinformation Analyst
Young Truong, Statistician
The Bioinformatics and Biostatistics Core provides CIDD investigators with design, statistical and data management assistance. The overall objectives of the Core are to enhance the productivity of CIDD investigators and to enhance the quality of their research. We achieve these objectives by collaborating with investigators, providing them with services through every stage of a research project. We participate in:
- writing grant proposals;
- developing efficient experimental designs;
- designing data collection instruments and conducting pilot tests;
- designing and implementing database management systems;
- supervising execution of the study and collection of data;
- operating database management systems to clean, store, and retrieve and archive data;
- performing statistical analyses and writing research papers and reports
To each phase of the research effort we contribute the unique perspectives and experiences of psychometricians, biometricians, professionally trained research database managers, and a support staff of proficient programmers and data managers.
Membership and Access Information
To be considered for membership in the CIDD and to gain access to core resources in the IDDRC, please visit the Membership and Access Information page. Membership and Access Information
Bioinformatics and Biostatics Core Expertise and Contact Information Core Director
Fei Zou, Ph.D.
Analysis of genetics and genomes data
Analysis of behavioral assessments, lingitudinal data, latent class, and latent profile analysis.
Design, implementatin, analysis, and biological interpretation of high-throughput sequencing-based studies, including RN-seq and exome sequencing, as well as functinoal genomics assays such as ChIP, Dnase, FAIRE, and ATAC.
Analysis of imaging data, small samples, mixed models, time series modeling, multivariate statistical methods and statistical machine learning.