Yufeng Wu, an assistant professor of Computer Science & Engineering, has been awarded a National Science Foundation Early Career Development (CAREER) Award to conduct research aimed at developing efficient algorithms that will enable accurate inferences to be made from massive data collected in population genomics studies. The five-year award, funded by the Division of Information & Intelligent Systems, totals nearly $500,000.
It is the 10th CAREER Award for the Computer Science & Engineering department, and the 26th for active faculty members within the School of Engineering.
Dr. Wu’s CAREER research will build upon his ongoing work aimed at developing algorithms that will yield insights into the origin and manifestations of genomic traits and building more accurate biological models. For the new research, he will apply combinatorial optimization techniques and probabilistic models to improve the speed and accuracy of high-throughput gene sequencing, with a focus on computational population genomics.
A genome represents the entire hereditary history of an organism as detailed in the DNA. High-throughput sequencing allows researchers to obtain accurate results for individual genomes quickly and more economically than was previously possible. Drawing meaningful conclusions from large populations is a more challenging problem, and requires development of sophisticated computational methods for analyzing large amount of sequencing data.
Dr. Wu plans to develop new computational methods for analyzing large amounts of high-throughput gene sequencing data from individuals both affected and not affected by a given, highly complex trait, such as Down Syndrome. “High-throughput sequencing is becoming an important technology for understanding complex traits, due to its unique advantages. High throughput sequencing allows researchers to detect low frequency genetic variants that only affect a small portion of population, and to do so in a cost-effective way,” he said.
Read more about Dr. Wu’s research here: http://www.engr.uconn.edu/drwufunding.php?id=5.