UW-Madison to train students in computational biology

A team of UW–Madison biologists and computer scientists has received nearly $5 million to train students to handle the increasingly complex problems that researchers in biology and medicine will face.

Biology has enormous potential for improving our health, environmental quality and food production. But researchers are finding that they need greater computational skills to advance biology and interpret the staggering amounts of data that experiments now generate.

“The program’s objective is to train students to be highly skilled in both biology and quantitative areas such as computer science or statistics,” says UW–Madison biochemist George Phillips. “It prepares students to function at the interface between the biological and computational sciences.”

The trainees will be among the 21st-century scientists who interpret the DNA sequences of genomes, discover the three-dimensional structures of proteins, analyze and map brain activity, and build detailed simulation models that mimic the networks that regulate cells, tissues and even entire organisms.

“There is an explosion of interest in this area on campus,” says computer scientist Jude Shavlik. “During the past four years the Department of Computer Sciences has been working with the Medical School’s Department of Biostatistics and Medical Informatics, and the Genome Center to build a campus program in computational biology and bioinformatics. We already have a vibrant group of over two-dozen faculty and graduate students working on exciting aspects of this challenging area.”

Phillips, Shavlik and geneticist Frederick Blattner received the five-year grant in March from the National Library of Medicine — a branch of the National Institutes of Health. The National Library of Medicine has awarded only a half dozen training grants nationally that focus on computer science and biology. The UW–Madison Graduate School will provide support to help administer the program.

The UW–Madison is a national leader in biology and computer sciences, Shavlik says. Campus researchers are developing and improving the new techniques that will help them address biological questions. The techniques include:

• Machine learning, in which computers are taught to recognize and search for patterns, such as a molecular shape that has potential as a pharmaceutical.
• Statistical methods that allow researchers to analyze thousands of genes and find the few that affect traits such as disease resistance.
• Mathematical optimization, which scientists might use to improve the way they look for patterns or carry out expensive calculations.
• Image analysis and visualization of structures, such as the molecular shapes that determine biological activity.
• Management of large and expanding data bases, such as the those for DNA sequences and protein structures.
• Computer models that simulate biological processes, such as the activity of different genes over the lifetime of an organism.
• Procedures for analyzing and improving the gene chips researchers use to monitor the activity of thousands of genes at any one time.

The program will support 16 graduate students, four postdoctoral trainees, and six summer interns each year. Students from the College of Agricultural and Life Sciences, the College of Letters and Science, the College of Engineering and the Medical School will be eligible for traineeships.

A unique aspect of the training program is that all students will have mentors in both the biological sciences and computer sciences or statistics. Students will receive degrees in their chosen majors — computer science, biochemistry or chemical engineering, for example. They will take courses that provide students from the biological sciences with training in computer science, and vice versa.