Properties and behaviors of biological systems and objects often behave randomly, and analyzing them with bioinformatics programs can present certain limitations. A new book written by University of Missouri College of Engineering researchers offers insight into how fuzzy set theory and fuzzy logic can provide tools to aid in solving some of these problems.
Dong Xu, the James C. Dowell professor in computer science, and department chair, and James Keller, curators’ professor in the electrical and Computer engineering and computer science and the R.L. Tatum professor for the college, along with two graduate students, Mihail Popescu and Rajkumar Bondugula, have coauthored a book that addresses the pairing.
“It’s a great combination of two disciplines,” said Xu. “It offers a bridge to connect them.”
As the first book on the topic, “Applications of Fuzzy Logic in Bioinformatics,” published by Imperial College Press in August, offers a unique and detailed look at how the two approaches compliment each other.
“Brilliant successes have been achieved through the use of models based on bivalent logic and probability theory,” writes Lotfi A. Zadeh in the book’s forward. “However, there are many problems such as those discussed in “Applications of Fuzzy Logic to Bioinformatics,” in which better results can be achieved with better models based on the use of fuzzy logic.”