"You take a problem that could be solved recursively from the top down and solve it iteratively from the bottom up instead. You store your intermediate results in a table for later use; otherwise, you would end up computing them repeatedly — an inefficient algorithm. But dynamic programming is usually applied to optimization problems like the rest of this article's examples, rather than to problems like the Fibonacci problem. The next example is a string algorithm, like those commonly used in computational biology."
