Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0220723 (PCA)
 4,687 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Breast cancer is a leading cause of mortality in women. In Malaysia, it is the most common cancer to affect women. The most common form of breast cancer is infiltrating ductal carcinoma (IDC). A proteomic approach was undertaken to identify protein profile changes between cancerous and normal breast tissues from 18 patients. Two protein extracts; aqueous soluble and membrane associated protein extracts were studied. Thirty four differentially expressed proteins were identified. The intensities of the proteins were used as variables in PCA and reduced data of six principal components (PC) were subjected to LDA in order to evaluate the potential of these proteins as collective biomarkers for breast cancer. The protein intensities of SEC13-like 1 (isoform b) and calreticulin contributed the most to the first PC while the protein intensities of fibrinogen beta chain precursor and ATP synthase D chain contributed the most to the second PC. Transthyretin precursor and apolipoprotein A-1 precursor contributed the most to the third PC. The results of LDA indicated good classification of samples into normal and cancerous types when the first 6 PCs were used as the variables. The percentage of correct classification was 91.7% for the originally grouped tissue samples and 88.9% for cross-validated samples.
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PMID:The PCA and LDA analysis on the differential expression of proteins in breast cancer. 2120 8

Persons at risk for Alzheimer's disease (AD) demonstrate altered cortical activation measured by functional MRI (fMRI) years before symptoms of disease are expected. We used fMRI to study the differences in cortical activation between 13 women with a family history of AD and at least one apolipoprotein E4 allele, a risk factor for AD, and a control group of 11 women lacking both factors. Our primary goal was to assess how well the two groups are able to be statistically separated, a task which directly affects the performance of post hoc classification. The dimension of the dataset, however, precludes the use of ordinary classification methods. In this paper we show the superiority of using oriented PLS (OrPLS) to accomplish the classification in the presence of this dimensionality problem. We are able to reduce the misclassification rates on the standardized fMRI data from an average of about 48% for PCA, to an average of 27% for PLS, and then to perfect classification for OrPLS.
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PMID:Using OrPLS to Identify Asymptomatic Women at Risk For Alzheimer's Disease. 2134 44