Generic programming depends on the decomposition of programs into simpler components which may be developed separately and combined arbitrarily, subject only to well-
defined interfaces. Bioinformatics deals with the application of computational techniques to data present in the Biological sciences. A genetic sequence is a succession of letters which represents the basic structure of a hypothetical DNA molecule, with the capacity to carry
information. This research article studied the relationship between the running times of a generic-based filtering program and different samples of genetic sequences in an increasing order of magnitude. A graphical result was
obtained to adequately depict this relationship. It
was also discovered that the complexity of the generic tree program was O (log2 N). This research article provided one of the systematic approaches of generic programming to
Bioinformatics, which could be instrumental in elucidating major discoveries in Bioinformatics, as regards efficient data management and analysis
