Editor's note: The MAGNet center formally closed in July 2016, following the mandatory conclusion of its grant after more than 10 years of activity. The pages in this section constitute an archive of its work.

A key focus of MAGNet is the interdisciplinary education of graduate and postdoctoral students. The goal is to train a new generation of biomedical researchers who posess the computational skills necessary to address important biological problems. The Training Core of the MAGNet Center (under the direction of Dr. Dennis Vitkup) supports computational biology and bioinformatics education at Columbia in several ways.

Center investigators are involved in many departmental and interdepartmental educational programs which offer doctoral education in computational biology. They work with each program to adapt their curriculum to serve the needs of computational biology graduate students.

Columbia offers a wide range of courses in Computational Biology and related fields. Most of these courses are taught by MAGNet faculty. The Center's Education Coordinator (Dr. Richard Friedman) works with the individual faculty members to make sure that all important topics are covered and to reduce redundancy between courses.

MAGNet coordinates a number of services for students and postdoctoral fellows:

• Academic advisement and tracking.
• Student seminar and journal club.
• Presentations at the annual Center retreat.
• Mailing list which advertises jobs and Summer internships.

Columbia's Training Program in Computational Biology is jointly administered by MAGNet and the Center for Computational Biology and Bioinformatics. The program offers interdisciplinary training that includes coursework in quantitative studies (computation, statistics, and/or physics), life sciences, and computational biology and bioinformatics, with mentored research in computational systems and structural biology at the labs of MAGNet investigators.

Many of the tools developed in the context of the Center's activities are used in classroom courses to train experimental biologists, clinical and translational researchers and medical students in computational methods. The geWorkbench platform plays a key role in this activity.