text: Dr. Senapathy's original objective in developing a method for identifying splice sites was to find complete genes in raw uncharacterized genomic sequence that could be used in the human genome project. In the landmark paper with this objective, he described the basic method for identifying the splice sites within a given sequence based on the Position Weight Matrix (PWM) of the splicing sequences in different eukaryotic organism groups for the first time. He also created the first exon detection method by defining the basic characteristics of an exon as the sequence bounded by an acceptor and a donor splice sites that had S&S scores above a threshold, and by an ORF that was mandatory for an exon. An algorithm for finding complete genes based on the identified exons was also described by Dr. Senapathy for the first time.
  Dr. Senapathy demonstrated that only deleterious mutations in the donor or acceptor splice sites that would drastically make the protein defective would reduce the splice site score (later known as the Shapiro–Senapathy score), and other non-deleterious variations would not reduce the score. The S&S method was adapted for researching the cryptic splice sites caused by mutations leading to diseases. This method for detecting deleterious splicing mutations in eukaryotic genes has been used extensively in disease research in the humans, animals and plants over the past three decades, as described above.
  The basic method for splice site identification, and for defining exons and genes was subsequently used by researchers in finding splice sites, exons and eukaryotic genes in a variety of organisms. These methods also formed the basis of all subsequent tools development for discovering genes in uncharacterized genomic sequences. It also was used in a different computational approaches including machine learning and neural network, and in alternative splicing research.