Developing new computational strategies to understand complex genetic systems.
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Developing new computational strategies to understand complex genetic systems.
The Carter Lab uses data to strengthen the interface between experimental systems and common disease in humans, such as Alzheimer's and Type 2 Diabetes. We develop computational methods to analyze genetic architecture, design translatable studies of model systems, perform data alignment to precisely quantify disease relevance, and share data through open science platforms. This work involves mapping networks of interacting genes, integrating phenotypic and molecular data, critically evaluating models with experimental tests, and exploring how biological complexity is encoded in genetic data.
Our primary disease focus is leveraging genetic and genomic data to identify and test potential treatments for Alzheimer’s disease. We are using human genetics to create the next generation of late-onset Alzheimer’s disease mouse and non-human primate models. These models comprise a multi-species strategy to understand Alzheimer’s disease origins and progression in molecular and pathophysiological detail. They are designed to be preclinical platforms for the rapid validation of diagnostic biomarkers and rigorous evaluation of precision therapeutics that target the pathways that drive dementia. We also comprehensively analyze data from human and experimental studies to critically assess therapeutic hypotheses. Through this work, we are derisking molecular targets to accelerate the discovery of precise, targeted therapeutic approaches.
We are embedded in a network of collaborative projects and centers including MODEL-AD, TREAT-AD, and MARMO-AD. By integrating knowledge and standardizing analytical strategies across these research consortia, we are maximizing the translational value of computational and experimental research. We are creating data resources and analytical tools that enable researchers to rapidly and reliably test new findings across prior studies, with the goal of accelerating Alzheimer’s research by avoiding past failures and instantly reinforcing promising new discoveries.