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New Collaborative Seed Grant Program Gives Eight Awards
Projects bring School of Medicine together with campus around quantitative problems
A new program aimed at fostering interactions between researchers in the School of Medicine and the campus has awarded its first round of seed grants to eight project teams.
"The overarching goal of this program is to encourage collaborations around quantitative basic and clinical research challenges," said Larry Carin, vice provost for research. "For example, that might take the form of attacking problems of relevance to clinical sciences by applying 'Big Data' analysis to electronic health records."
In addition to having at least one representative from both campus and School of Medicine, each proposal was required to identify a plan for obtaining external funding after the seed-funded phase.
"This is one of many things being done to bring the Campus and SoM into closer alignment," Carin said. "That is one of Provost Sally Kornbluth's key strategic goals."
The eight teams selected will each receive $50,000 in support. The grantees for "Collaborative Quantitative Approaches to Problems in the Basic and Clinical Sciences" are:
- "A geometric approach to modeling human microbiota dynamics," Sayan Mukherjee (Statistical Science); Lawrence David (Molecular Genetics and Microbiology).
- "Incorporating dynamic Electronic Health Records data into a model for patient deterioration," Rebecca Steorts (Statistical Science); Benjamin Goldstein (Biostatistics and Bioinformatics); Cara O'Brien (Medicine).
- "Interactive 3D fluid dynamics for cerebral aneurysm treatment planning," Amanda Randles (Biomedical Engineering); L. Fernando Gonzalez (Neurosurgery).
- "Joint Modeling of Multiple 'Omics Data for Clinical Research," Ricardo Henao (Electrical and Computer Engineering); Micah McClain (Medicine); Ephraim Tsalik (Medicine); Deepak Voora (Medicine).
- "Predicting REaDmissions to Improve Care Transitions for Heart Failure (PREDICT-HF)," Katherine Heller (Statistical Science); Zubin Eapan (Medicine).
- "'Smart Health' algorithm to automate cervical cancer screening," Guillermo Sapiro (Electrical and Computer Engineering); Nimmi Ramanujam (Biomedical Engineering); John Schmitt (Obstetrics and Gynecology).
- "Understanding the processes that produce antigenic variation in malaria," Gregory Wray (Biology); Jen-Tsan Chi (Molecular Genetics and Microbiology).
- "Using tumor cell genealogies to understand tumor dynamics and predict clinical outcomes," Richard Durrett (Mathematics); Katia Koelle (Biology); Edward Patz (Pharmacology & Cancer Biology).