ABSTRACT In the thesis, a bacteria identification software tool is developed to identify an unknown bacterium based on its status, Gram-Staining, oxygen demand, endospore and ways of producing energy. The software uses biochemical analysis to determine which biochemical tests are needed to classify common Grams bacteria. It is crucial to identify the bacteria efficiently. However, it used to be a time and resource consuming process because many and even irrelevant biochemical tests would need to be done to classify unknown bacteria. As a result, the time to wait for correct disease diagnosis and treatment of infection will put patients’ at high risk. With the new bacteria identification software tool, the system can select the biochemical tests needed based on the results of primary tests. For example, when identifying Grams bacteria, Oxydation and Catalas tests can be run first, then the system will determine the likely species to identify and necessary further biochemical tests to do. Technicians will subsequently run the tests and inform the system the findings. Finally the system will submit the results of identification. However, when target bacteria can not be differentiated, the system will also suggest other further tests to be done. Therefore, by using the software tool, the time to obtain results will be greatly reduced thus allows a rapid response to diagnose disease and treat infection.
