Research Projects

Grand Central Station before and during COVID-19
| Population Health Informatics | Systems Biology and Bioinformatics

Since early January 2020, Biocomplexity Institute researchers have been working with federal authorities to address questions like the risk of importation of COVID-19 to the United States and other countries; location of likely clusters within the United States; and estimation of various disease progression parameters.

All Projects

During World War II, the U.S. Army conducted surveys to reveal attitudes toward, and between Black and White Soldiers. These responses hold insights regarding attitudes about race, gender, and family roles of the time. Our research team used computational text analysis and social network analysis of handwritten responses to learn about the dynamics and language of soldiers in the 1940’s.
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National Well-being
BV-BRC is the Bacterial and Viral Bioinformatic Resource Center in this program, providing access to comprehensive datasets including genomics, structures, functions, and more.  BV-BRC also provides computational tools to quickly analyze data and make predictions using artificial intelligence techniques. The BV-BRC platform enables researchers to fully maximize the value of data related to pathogens.
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Population Health Informatics,Systems Biology and Bioinformatics
We are studying the spread of invasive plants in the Chitwan Annapurna Landscape (CHAL) of Nepal, which is part of a biodiversity hotspot. This problem of invasive species is an impediment to the achievement of multiple sustainable development goals drafted by the United Nations. CHAL has a rich diversity of flora and fauna, which is unfortunately threatened by the combined effects of climate change and increased human activities.
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Resilient Societies and Interdependent Infrastructures
This project aims to reduce malaria transmission by administering ivermectin to humans and livestock. Ivermectin is an endectocide, a drug that can kill ecto- and endoparasites, as well as mosquitoes that feed on treated humans or animals. The overall goal of the project is to conduct randomized control trials through mass drug administration of ivermectin (iMDA) in humans and animals in Tanzania and Mozambique.
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Population Health Informatics
The major goal of this project is to design, build, verify, and deploy an open-access general-purpose CI for network science, which we call net.science.
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Resilient Societies and Interdependent Infrastructures
The overall goal of this project is to develop methods for prediction of incidence rates and patient risk to HAIs and evaluate interventions to control their spread. The mechanisms of HAI transmission and antimicrobial resistance are very complex, and the available data are sparse and noisy. Therefore, risk prediction and evaluation of interventions cannot be done by simple statistical models restricted to one hospital.
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Population Health Informatics
Since early January 2020, Biocomplexity Institute researchers have been working with federal authorities to address questions like the risk of importation of COVID-19 to the United States and other countries; location of likely clusters within the United States; and estimation of various disease progression parameters.
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Population Health Informatics,Systems Biology and Bioinformatics
This project brings together a systems science approach, combines agent-based stochastic epidemic models, and techniques from machine learning, high performance computing, data mining, and spatial statistics, along with novel public and private datasets on immunization and incidence, to develop a novel methodology for identifying critical undervaccinated clusters.
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Population Health Informatics
This project has led to the development of a broad class of highly scalable libraries for problems in multiple areas, including network science, computer vision, bioinformatics and climate science. Team members have contributed by developing scalable algorithms for network generation and subgraph detection, which have been applied to problems in public health.
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Population Health Informatics,Resilient Societies and Interdependent Infrastructures,Social, Cognitive, and Behavioral Science
Natural language processing and machine learning are powerful techniques for extracting knowledge from the volumes of text-based data available. Collaborating with our agency partner, the National Center for Science and Engineering Statistics (NCSES), we are using administrative data from Federal RePORTER to identify the range of R&D topics funded by federal science and technology agencies, including emerging research areas.
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Official Statistics