Disease relevance of Principal Component Analysis

• Using principal component analysis, it was found that high nIgE and IL-5 levels are specific for CRS with nasal polyps [1].
• Genetics of colitis susceptibility in IL-10-deficient mice: backcross versus F2 results contrasted by principal component analysis [2].

Psychiatry related information on Principal Component Analysis

• A principal component analysis identified three interpretable factors: Emotional/Cognitive Concern for Dieting, Calorie Knowledge, Behavioral Dieting Control. Only Emotional/Cognitive Concern for Dieting equated with RS as both measures correlated with self-esteem and restrained drinking [3].

High impact information on Principal Component Analysis

• By using principal component analyses (PCA), a differentiation axis was exposed, reflecting lineages and maturation stages of normal hematopoietic cells [4].
• Mapping of ventricular repolarization potentials in patients with arrhythmogenic right ventricular dysplasia: principal component analysis of the ST-T waves [5].
• A weighted composite score developed from a principal-component analysis of the same measures improved to a significantly greater degree with olanzapine, compared with haloperidol [6].
• RESULTS: Principal-component analyses revealed main effects of diagnosis, sex, and age for the CSF increases seen in the schizophrenia patients, in male subjects, and in association with age [7].
• Principal component analysis of the tRNA-enzyme complexes revealed that the selenocysteine synthase appears to bind only one seryl-tRNA(sec) per dimer, which is consistent with the result of biochemical binding studies [8].

Biological context of Principal Component Analysis

• Unsupervised principal component analysis of all samples revealed that samples self-cluster into four groups consistent with histological phenotypes of proliferative (PE), early-secretory (ESE), mid-secretory (MSE), and late-secretory (LSE) endometrium [9].
• The use of principal component analysis to resolve the spectra and kinetics of cytochrome c oxidase reduction by 5,10-dihydro-5-methyl phenazine [10].
• This was also demonstrated by principal component analysis of DRB1 and DQB1 allele frequencies, which separated the Tokelauan population from Cook Islanders, Tongans and Samoans [11].
• Using principal component analysis, we derived five factors from 13 main contents of the Yale-Brown Obsessive-Compulsive Scale (YBOCS), and considered them as quantitative phenotypes to evaluate their possible association with an insertion/deletion polymorphism in the promoter region of the serotonin transporter gene (5-HTTLPR) [12].
• The development of Quantitative Structure Activity Relationships (QSAR's) often relies heavily on the application of statistical methods such as multi-linear regression (MLR) or principal component analysis/partial least square (PCA/PLS) [13].

Anatomical context of Principal Component Analysis

• To explore abnormal patterns of brain functional connections with respect to language processing, we applied a principal component analysis to resting regional cerebral metabolic data obtained with positron emission tomography in patients with right- and left-sided temporal lobe epilepsy and controls [14].
• Principal component analysis based on the intensity of 1238 protein spots indicated that the HCC cells and the normal hepatocytes had distinct proteomic profiles [15].

Associations of Principal Component Analysis with chemical compounds

• A principal component analysis has been applied on equilibrium simulations of a beta-heptapeptide that shows reversible folding in a methanol solution [16].
• The relationships between age, BMI, HbAlc, serum AG, fasting and 2-h plasma glucose, and urinary glucose were also examined using principal component analysis with a varimax rotation [17].
• RESULTS: Unsupervised principal component analysis showed that the androgen-dependent and androgen-independent tumors segregated from one another [18].
• In the field of metabonomics, (1)H NMR and full scan mass spectrometry methods have usually been combined with principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) to detect patterns in biofluids that correspond to specific effects, usually a toxic site effect of a compound [19].
• Various subsets of pharmacological activity indices of benzodiazepines, of 8-quinolinol derivatives, and of rifamycin B amides were decomposed into mutually independent components by using principal component analysis [20].

Gene context of Principal Component Analysis

• Moreover, principal component analysis on ranks evidenced a poor association between TSP-1 and -2, VEGF and TP [21].
• Guided by principal component analysis, we instead discovered that the most efficient bacterial selenoprotein production conditions were obtained with the high-transcription T7lac-driven pET vector system in presence of the selA, selB, and selC genes, with induction of production at late exponential phase [22].
• Principal component analysis using KIR gene data from 20 populations was performed to determine genetic differences and relations between populations [23].
• The relationships between age, sex, tumor size, GH and PRL plasma levels, granularity, and percentage of GH-, alpha SU-, and PRL-immunoreactive cells were established in 105 acromegalic patients by three statistical methods, mainly by a principal component analysis [24].
• The principal component analysis of gene frequencies at HP, GC and PI loci shows two groups in the Basque Country: one comprising the indigenous inhabitants and those of mixed descent, the other of immigrants [25].

Analytical, diagnostic and therapeutic context of Principal Component Analysis

• A biometric approach partly involving principal component analysis has been used to examine the changes in phenotypic characters of shoot-tip derived potato plants recovered from tissue culture, dimethyl sulphoxide (DMSO) and cryopreservation in comparison with field-grown tuber-derived plants [26].
• Qualitative study of ethanol content in tequilas by Raman spectroscopy and principal component analysis [27].

References