Skip to main content
Explore URMC
menu
URMC / Center for AIDS Research / Core Facilities & Services / Biostatistics, Bioinformatics and Computational Biology Core

 

Biostatistics, Bioinformatics and Computational Biology Core

This core is an interdisciplinary core of biostatisticians, modelers, biocomputing scientists, software tool developers and bioinformaticians with expertise in various HIV/AIDS research areas. In addition to providing novel and standard statistical methods, this core seeks to support and collaborate with Investigators in the areas of grant proposal, study design and manuscript/abstract preparation. This core additionally provides training through seminars and hands-on lab specific training and consultation.

Core Leadership

Brent JohnsonBrent Johnson, Ph.D.
Core Director

P: (585) 273-1869
Brent_Johnson@urmc.rochester.edu

Tong Tong WuTong Tong Wu, Ph.D.
Associate Core Director

P: (585) 276-6858
tongtong_wu@urmc.rochester.edu

Biostatistics Unit

Provides biostatistics support for design and analysis of HIV/AIDS-related in vitro and in vivo lab experiments, clinical studies, prevention/behavior studies and epidemiological and translational studies.

Biomathematical Modeling Unit

Supports and promotes new multidisciplinary collaborations by providing modeling support to further HIV/AIDS-related research and to expand existing modeling efforts. Modeling expertise and projects include the following.

  • PK/PD modeling of antiretroviral therapies
  • HIV viral dynamics in AIDS clinical studies
  • HIV viral fitness modeling for in vitro experiments
  • AIDS epidemics modeling
  • HIV RNA structure and sequence modeling
  • Pathway modeling, cellular signaling and regulatory network modeling
  • High-throughput data modeling and analysis

Biocomputing/Bioinformatics Unit

Provides translational data management and informatics services for HIV/AIDS-related research and studies, including the development of databases and data management, biocomputing and bioinformatics tools, and computational algorithms.