Research On The Diagnosising Of Ovarian Cancr Based On Proteomics

Cancer is ordinary and frequent illness that do great harm to human being's healthiness. Detecting cancer early has great significance to its therapy and judgement from cure. Serum proteomic pattern diagnosis technology is a new proteomic flat.Gaining protein spectrum through high dimension mass spectrum in this flat can be as a criterion to diagnose illness. This technology has great application foreground in detecting cancer early. At present, most of biomarkers gaining from SELDI-TOF-MS are low molecule mass protein pieces produced from tiny environment of special cancer.Through inspecting cancer suggests its sensitivity and specialty are better traditional cancer marker, its sensitivity is nearly 100% and specialty is over 95%. So, it has important clinic application value in inspecting cancer early and warning early, this paper is focused on proteomic mass spectrum ovarian diagnosising.First, proteomics and protein chip are introduced. The technology of SELDI-TOF is stressed, including its basic principle, mechanism, clinic application and existent problem. Second, preprocess ovarian mass spectrum, including loading data, resampling the spectrum, baseline correction, noise reduction. Use LDA to reduce data dimensionality in order to classify in the end.In the end, data is classified. LDA and KNN are used to classify data reduced dimensionality in this paper. Comparing sensitivity and specialty and choosing different training set and testing set, LDA is a better classifier that can be learned from the paper.