Meltem Apaydin, a graduate student in the Department of Electrical and Computer Engineering at Texas A&M University, received the best paper award from the 2016 International Conference on Intelligent Biology and Medicine (ICIBM 2016).
Apaydin’s paper “Robust mutant strain design by pessimistic optimization,” describes a novel pessimistic optimization framework to derive robust knockout strategies under model uncertainty to design mutant microbial strains for desirable outcomes.
Apaydin and her co-authors, including her electrical and computer engineering Ph.D. thesis adviser, Dr. Xiaoning Qian, have shown that the existing optimistic bi-level optimization methods for mutant strain design have fast degenerative performance in uncertain and incorporative environments. The proposed pessimistic optimization leads to robust knockout strategies to achieve stable desirable in-silico performances. The full paper will be published in BMC Genomics.
The authors are currently seeking resources to experimentally validate the derived mutant microbial strains to demonstrate the potential of the proposed method in computational systems biology, especially in metabolic engineering.
Apaydin earned her Bachelor of Science degree in electrical and electronics engineering from Anadolu University in Turkey, and her Master of Science degree in electrical engineering from Texas A&M. She is currently working on her Ph.D. thesis project in electrical engineering. Her research focuses on deriving robust optimization methods in machine learning, with their life and materials science applications.