Research in this area explores the use of computational methods to better categorize, visualize, and model biological data and systems. These problems often involve massive, high-dimensional datasets and their solutions draw from many disciplines of computer science including database management, data mining, machine learning, and algorithmic optimization. Research in this group includes algorithms for sequence and structure analysis, protein structure prediction, virtual screening and lead discovery, data modeling of scientific applications, DBMS (database management system) extensions in support of brain image and proteomics analyses, and building predictive models for effective disease diagnoses. The research group has increasing collaboration with the College of Biological Sciences, the Medical School, and the Mayo Clinic.
Ci Fu, Xiang Zhang (Ph.D. student), Amanda O Veri, Kali R Iyer, Emma Lash, Alice Xue, Huijuan Yan, Nicole M Revie, Cassandra Wong, Zhen-Yuan Lin, Elizabeth J Polvi, Sean D Liston, Benjamin VanderSluis (Ph.D. 2014), Jing Hou, Yoko Yashiroda, Anne-Claude Gingras, Charles Boone, Teresa R O’Meara, Matthew J O’Meara, Suzanne Noble, Nicole Robbins, Chad L Myers (professor), Leah E Cowen
Kathie A Mihindukulasuriya, Ruben AT Mars, Abigail J Johnson, Tonya Ward, Sambhawa Priya, Heather R Lekatz, Krishna R Kalari, Lindsay Droit, Tenghao Zheng, Ran Blekhman, Mauro D’Amato, Gianrico Farrugia, Dan Knights (professor), Scott A Handley, Purna C Kashyap
Henry N Ward (Ph.D. student), Michael Aregger, Thomas Gonatopoulos-Pournatzis, Maximilian Billmann (postdoctoral associate), Toshiro K Ohsumi, Kevin R Brown, Benjamin J Blencowe, Jason Moffat, Chad L Myers (professor)
Hamid Safizadeh (Ph.D. student), Scott W Simpkins (Ph.D. 2018), Justin Nelson (Ph.D. 2019), Sheena C Li, Jeff S Piotrowski, Mami Yoshimura, Yoko Yashiroda, Hiroyuki Hirano, Hiroyuki Osada, Minoru Yoshida, Charles Boone, Chad L Myers (professor)