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Cancer cells contain genetic damage that can lead to tumorigenesis. Genetic damage found in cancer cells is of two types: dominant and the genes are termed proto-oncogenes; and recessive and the genes are termed tumor or growth suppressors, recessive oncogenes or anti-oncogenes. Oncogene proteins are a specific group of growth factors that promotes uncontrolled cell growth and proliferation. These proteins are derived from normal proto-oncogenes via a limited number of modifications, i.e mutations, insertions or deletions. Because proto-oncogenes control the cell cycle, it is obvious that should a proto-oncogene be mutated the potential for an unregulated cell cycle results. Therefore, a structure-function analysis of oncogene proteins is of great importance in understanding cell transformation that causes cancer development. In this paper we present and discuss the use of two related computational techniques for analysis of ras oncongene protein example. We showed that the methods are efficient for accurate prediction of the protein active/binding site locations critical for its bioactivity, i.e. cell transformation.