Xiaosong Wang, associate professor in pathology and biomedical Informatics, leads the Computational Genomics and Translational Cancer Biology lab in the Pitt Cancer Institute. This unified computational and wet laboratory explores cancer genomics using next generation sequencing and genome profiling in a multidisciplinary approach uniting researchers in bioinformatics, genetics, and molecular and cell biology. The lab’s guiding principle is translational “bench to bedside” research – transforming genomic data into precision medicine to battle cancers, particularly breast cancer.
CRC is supporting the development and human imaging studies of a powerful new MRI technology being done by Pitt's Radiofrequency Research Facility and the 7 Tesla Bioengineering Research program led by bioengineering professor Tamer Ibrahim. The 7 Tesla scanner is one of the most powerful MRI devices in the world, able to reveal details not visible in typical MRI machines. particularly in brain markers implicated in diseases associated with aging, such as Alzheimer’s and late life depression, The lab l develops adiofrequency antennas to create even electromagnetic waves to avoid potentially dangerous heating of brain tissue, for which the team uses CRC to simulate hundreds of thousands of possible antenna configurations.
The star-nosed mole of North America and the naked mole rat of East Africa are both blind. They underwent the same adapatation to living underground, although they are different species separated by thousands of miles. Marine mammals like manatees and dolphins underwent shared adaptations to aquatic life. What could the convergence of independent physical changes reveal about the evolution of the genes responsible for those physical changes? The labs of Maria Chikina and Nathan Clark explore this evolution relying on CRC resources for computation tasks to compare rates of evolution for a gene in one species to rates of evolution for a gene in another species.
In the spring of 1006 CE a supernova in the constellation Lupus was the brightest stellar object ever recorded on Earth, bright enough for several months to be easily visible in daylight. Most supernovae are not dramatically visible from Earth and don’t leave visible evidence. What they do leave are supernova remnants: expanding balls of gas heated to millions of degrees Celsius. The remnants hold clues to the origins and deaths of stars, and the lab of Pitt astrophysicist Carles Badenes searches for those clues helped by the resources of the Center for Research Computing.
Two years ago Pitt economist Stefania Albanesi co-authored a paper refuting conventional wisdom that the 2007-2009 global credit crisis was triggered by mortgage defaults of borrowers with low credit scores. Albanesi found that borrowers with higher credit scores accounted for an outsized percentage of mortgage defaults. Albanesi and graduate student Domonkos Vamossy asked two questions – Why didn’t credit scores predict default particularly well? Can one create credit scores that predict better? They developed a deep learning model to predict consumer default that outperforms standard credit scoring models in accuracy, a model that could help policy makers reduce consumer default and large-scale risks.