  Human body consists of lot of cells, each cell consist of DeOxaRibo Nucleic
Acid (DNA). Identifying the genes from the DNA sequences is a very difficult
task. But identifying the coding regions is more complex task compared to the
former. Identifying the protein which occupy little place in genes is a really
challenging issue. For understating the genes coding region analysis plays an
important role. Proteins are molecules with macro structure that are
responsible for a wide range of vital biochemical functions, which includes
acting as oxygen, cell signaling, antibody production, nutrient transport and
building up muscle fibers. Promoter region identification and protein structure
prediction has gained a remarkable attention in recent years. Even though there
are some identification techniques addressing this problem, the approximate
accuracy in identifying the promoter region is closely 68% to 72%. We have
developed a Cellular Automata based tool build with hybrid multiple attractor
cellular automata (HMACA) classifier for protein coding region, promoter region
identification and protein structure prediction which predicts the protein and
promoter regions with an accuracy of 76%. This tool also predicts the structure
of protein with an accuracy of 80%.
