VIDD computational biology scientists develop novel computational methods and tools that are applied to genomic statistics and high throughput biological assays for a better understanding of infectious disease processes and host immune responses. These researchers combine empirical data with mathematical computational methodologies for deciphering the complexities of human disease.
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Characterizing T cells induced by candidate vaccines using flow cytometry. Developing new assays to evaluate vaccine efficacy with HIV Vaccine Trials Network. Studies include examining T cell function at the single-cell level using advanced flow cytometric techniques; examples include T cell responses to vaccination and to viral infections such as CMV, EBV, HIV, and hepatitis B.
Statistical and computational methods for bioinformatics applications, statistical modeling for genome sequence analysis and statistical modeling frameworks. The interface between computer science, statistics, and molecular biologyand such as development of new informatics methods in genomics and post-genomics
Computational and statistical methods development for high-throughput, high-content biological data.
Modeling and integration of data from high throughput assays for biomarker discovery, clinical outcome prediction and disease classification.
Current studies include development of methods for T-cell based sieve analysis, quantification of vaccine induced T cell responses, systems biology of influenza and time-dependent correlates analysis of HIV efficacy trial.
Research focus includes vaccine clinical trials, the design and analysis of Phase I/II trials, for evaluating vaccine effects on immune responses; the design and analysis of Phase 2b/III trials, for evaluating vaccine efficacy, immune correlates, sieve analysis, and post-infection vaccine effects; general biostatistical methods research, such as survival analysis, causal inference, and evaluation of surrogate endpoints
Developing methods and tools for high throughput, high dimensional experiments with applications in vaccine research and immunology; flow cytometry, peptide microarrays, next generation sequencing; Bayesian inference and computation and statistical computing
Research focus included the design and evaluation of vaccine field trials; modeling infectious disease dynamics and strategies for mitigation and control; causal inference in infectious diseases; and evaluating surrogates of protection.
Immunologic endpoint determination for experimental vaccines (HIV, pneumococcus, malaria, TB, flu) and
Logistics, operations, quality assurance, and assay validation for immunologic evaluation of vaccines in the clinical trial setting
Research focus includes statistical methods for bioassays (e.g., flow cytometry, sequencing); dynamic modeling of biological systems (e.g., multi-type cell populations, B-cell repertoire); nonparametric methods for supervised and unsupervised learning; stochastic processes (e.g., branching processes); algorithms for scalable data analysis.
Design and analysis of vaccine efficacy trials, genotype-specific vaccine efficacy-based sieve analysis,immune correlates of vaccine protection, analysis of vaccine-induced immune response durability and survival analysis
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