Quadratic Binary Programming Models in Computational Biology
Keywords:integer programming, quadratic binary programming, computational biology, sequence alignment, protein folding, contact map overlap, rotamer assignment, protein similarity
AbstractIn this paper we formulate four problems in computational molecular biology as 0-1 quadratic programs. These problems are all NP-hard and the current solution methods used in practice consist of heuristics or approximation algorithms tailored to each problem. Using test problems from scientific databases, we address the question, “Can a general-purpose solver obtain good answers in reasonable time?” In addition, we use the latest heuristics as incumbent solutions to address the question, “Can a general-purpose solver confirm optimality or find an improved solution in reasonable time?” Our computational experiments compare four different reformulation methods: three forms of linearization and one form of quadratic convexification.
How to Cite
Forrester, R. J., & Greenberg, H. J. (2008). Quadratic Binary Programming Models in Computational Biology. Algorithmic Operations Research, 3(2). Retrieved from https://journals.lib.unb.ca/index.php/AOR/article/view/5930