Toni Kazic, PhD, FACMI

Dr. Kazic received her BS in microbiology from the University of Illinois in 1975 and a PhD in genetics in 1984 from the University of Pennsylvania. After a 2-year postdoctoral fellowship in bacterial genetics at Fox Chase Cancer Center, she moved to Washington University where she stayed in a variety of roles until 2001. Her interest in computational biology led her to a visiting scientist’s role at Argonne National Laboratory in 1990 and a consulting role with the Division of Computer Research and Technology at NIH in 1991. An instructor in the Institute for Biomedical Computing at Washington University, she took a year off in 1996–1997 to serve as Program Director for Computational Biology at the NSF. Since 2001, she has been an associate professor of computer science at the University of Missouri-Columbia, with a secondary appointment in health management and informatics since 2003.

In 1990, Dr. Kazic wrote a seminal paper that directly linked computer science techniques to the biological domain. The paper arose from her work at Argonne National Laboratory and was entitled ‘‘Prototyping Databases in Prolog,’’ published as a book chapter in The Practice of Prolog. Her work from that time was the genesis of her research on the design of biochemical databases and use of computational logic to model networks of biochemical reactions as cellular systems.

A member of the NLM’s Biomedical Library and Informatics Review Committee, Dr. Kazic is also an educator, having supervised the research of postdocs, grad students (computer science, chemistry, statistics, health informatics, bioinformatics, biochemistry, and plant biology) and undergrads. Her work has consistently stressed the importance of accurately representing what is known about biochemistry so that the data can be used to model biological phenomena rather than settling for representations that are computationally convenient or customary. Realizing the dream of accurate, inclusive models has stimulated her development of new approaches to biological databases, the representation of biochemical ideas and data, and the semantic interoperability of databases.