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HIV Drug Resistance Database, also known as Stanford HIV RT and Protease Sequence Database, is a database at Stanford University that tracks 93 common mutations of HIV.It has been recompiled in 2008 listing 93 common mutations, after its initial mutation compilation in 2007 of 80 mutations.
Download as PDF; Printable version; In other projects ... Pages in category "Stanford University" ... History of Stanford University; HIV Drug Resistance Database ...
In 2014, Hader was appointed Director of the Division of Global HIV and TB at the US Centers for Disease Control and Prevention (CDC). [2] She helped implement the U.S. President's Emergency Plan for AIDS Relief (PEPFAR) to collect more data and increase global access to life-saving HIV treatment.
Joshua A. Salomon is Professor of Health Policy at the Stanford University School of Medicine, where he is also director of the Prevention Policy Modeling Lab. He previously served as Professor of Global Health at the Harvard T.H. Chan School of Public Health .
The Stanford HIV Drug Resistance Database and the International AIDS Society publish lists of the most important of these; first year listing 80 common mutations, and the latest year 93 common mutations, and made available through the Stanford HIV RT and Protease Sequence Database. [citation needed]
The Pharmacogenomics Knowledgebase (PharmGKB) is a publicly available, online knowledge base responsible for the aggregation, curation, integration and dissemination of knowledge regarding the impact of human genetic variation on drug response. [1]
Yvonne "Bonnie" Maldonado is an American physician, pediatrician, and Professor of Pediatrics and of Health Research and Policy at Stanford University, with a focus on Infectious Diseases. She founded Stanford's pediatric HIV Clinic and now serves as Stanford University School of Medicine's Senior Associate Dean of Faculty Development and ...
HIV Resistance Response Database Initiative (RDI) was formed in 2002 to use artificial intelligence (AI) to predict how patients will respond to HIV drugs using data from more 250,000 patients from around 50 countries around the world. The RDI used its models to power its HIV Treatment Response Prediction System (HIV-TRePS).