An Evolutionary Programming Algorithm for Automatic Chromatogram Alignment

Scientists use liquid chromatography/mass spectrometry (LC/MS) instruments to measure metabolic responses to external stimuli. The data from these instruments can be distorted due to changes in the testing environment. Automating the removal of distortions is crucial in processing the data. The purpose of this thesis is to develop an algorithm that will automate the process. The data produced by the LC/MS instrument were treated as images and image registration techniques were applied. A polynomial transformation function was assumed. An evolutionary programming algorithm was used to determine the coefficients of the polynomial. The data was manipulated to determine the best registration technique. This thesis describes the data manipulation and details of the algorithm. The results show that the evolutionary programming algorithm is a reasonable solution for automating the registration of chromatograms. These results also show that more work needs to be performed to fine-tune the algorithm to work with distorted chromatograms