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At least 397 records · Page 22Linked to original sources
PubMed1996

Principal component analysis and large-scale correlations in non-coding sequences of human DNA.

We have calculated a full set of second-order correlation functions of nucleotides in noncoding DNA. They are found to be independently invariant in regard to permutations of A and T, and also C and G. Considering correlation functions as a 4 x 4 matrix with a symmetrical basis, we have found the principal components-objects with zero cross-correlations. These three principal components are present the base compositions: (A + T - C - G), (A - T), (C - G). The long-range behavior of these principal components yields power-law dependencies with different critical exponents.

Base Composition↗
PubMed2003

Using principal component analysis to monitor spatial and temporal changes in water quality.

Chemical, biological and physical data monitored at 12 locations along the Passaic River, New Jersey, during the year 1998 are analyzed. Principal component analysis (PCA) was used: (i) to extract the factors associated with the hydrochemistry variability; (ii) to obtain the spatial and temporal changes in the water quality. Solute content, temperature, nutrients and organics were the main patterns extracted. The spatial analysis isolated two stations showing a possible point or non-point source of pollution. This study shows the importance of environmental monitoring associated with simple but powerful statistics to better understand a complex water system.

Environmental Monitoring↗
PubMed1992

Genetic structures in the Po Delta: principal components, systemic functions and the relative age of the beta-thalassemia polymorphism.

The principal component representations of the genetic structure of the human population of the Po Delta, obtained from 7 polymorphic loci, are compared with the representations obtained from the systemic function of gene frequencies devised by Womble 1951. It is noted that, when tridimensional representations are used, some consistency is visible in the results of the two methods for the description of the genetic population structure in the area under study. Both methods indicate that the present structure of the balanced polymorphism for beta-thalassemia in the area appears to be more recent than the structure of the neutral polymorphisms studied.

Alleles↗
PubMed1992

Structure model of core proteins in photosystem I inferred from the comparison with those in photosystem II and bacteria; an application of principal component analysis to detect the similar regions between distantly related families of proteins.

A principal component analysis based on the physico-chemical properties of amino acid residues is developed to assign similar regions between distantly related families of proteins, taking account of the species diversities in respective families. The most important advantage of this analysis should be that it reflects different physico-chemical properties and thus can predict more detailed structural properties, including the transmembrane helices, than the hydropathy analysis. Its first application reconfirms the similarity between the core proteins of photosynthetic reaction center in purple bacteria and those of photosystem II, indicating that the low percentage of identical amino acid residues estimated previously between them is due to much allowance for amino acid substitutions in purple bacteria. The application of this analysis to the core proteins of photosystem I reveals that any of these proteins includes two domains, each showing high similarity to the amino acid sequences of core proteins in photosystem II and purple bacteria. A core structure model of A1 and A2 proteins folded into four layers of sheets of transmembrane helices is proposed to provide a molecular basis for the electron pathway suggested by spectroscopic experiments as well as for the interaction sites with plastocyanin, 9 kDa protein and LHC proteins.

Amino Acid Sequence↗
PubMed1981

Principal component analysis of slow brain potentials during six second anticipation intervals.

The comparison of principal component analyses between seven experimental studies demonstrates a remarkable similarity of the extracted components. Slow scalp-recorded potentials of the brain (SPs) during a constant 6 sec foreperiod can be described by an early frontal, and a late preparatory component. Furthermore, an additional intermediate component may be retained by the PCA. This component seems to reduce the between-subject variance and often describes processes dependent on stimulus repetition. There is evidence favoring the varimaxed solution of the PCA for the parametrization of most of the experimental data.

Biofeedback, Psychology↗
PubMed2000

Comparison of two exploratory data analysis methods for fMRI: fuzzy clustering vs. principal component analysis.

Exploratory data-driven methods such as Fuzzy clustering analysis (FCA) and Principal component analysis (PCA) may be considered as hypothesis-generating procedures that are complementary to the hypothesis-led statistical inferential methods in functional magnetic resonance imaging (fMRI). Here, a comparison between FCA and PCA is presented in a systematic fMRI study, with MR data acquired under the null condition, i.e., no activation, with different noise contributions and simulated, varying "activation." The contrast-to-noise (CNR) ratio ranged between 1-10. We found that if fMRI data are corrupted by scanner noise only, FCA and PCA show comparable performance. In the presence of other sources of signal variation (e.g., physiological noise), FCA outperforms PCA in the entire CNR range of interest in fMRI, particularly for low CNR values. The comparison method that we introduced may be used to assess other exploratory approaches such as independent component analysis or neural network-based techniques.

Brain↗
PubMed2000

Simultaneous spectrophotometric determination of phenobarbital, phenytoin and methylphenobarbital in pharmaceutical preparations by using partial least-squares and principal component regression multivariate calibration.

Two multivariate calibration methods, partial least squares (PLS-2) and principal component regression (PCR) have been applied to the simultaneous spectrophotometric analysis of ternary mixtures of phenytoin (DPH), phenobarbital (PBT) and methylphenobarbital (MPBT) in the Comital-L pharmaceutical formulation. The PLS-2 and PCR procedures were employed to evaluate the data of a variable number of calibration solutions measured over the wavelength range 400-700 nm. The concentration ranges used to construct the calibration matrix were varied between 5 and 30 microg ml(-1). The proposed methods were validated by applying them to the analysis of the Comital-L pharmaceutical formulation and the average relative errors were less than 6% for each one of the analyzed compounds. The results obtained by both proposed methods have been compared with the results obtained by application of a RPLC reference method.

Least-Squares Analysis↗
PubMed1991

Principal components analysis of the Psychological Screening Inventory in a sample of substance abusers.

A principal components analysis of responses to the Psychological Screening Inventory from a sample of substance abusers was conducted. Subjects were 153 inpatients admitted to a midwestern program for chemical dependency treatment. Means for age and education were 28.0 yr. (SD = 8.1) and 11.4 (SD = 1.8), respectively. Analysis indicated that a two-factor solution best described these data. Factor 1 reflected over-all maladjustment, while Factor 2 was a measure of extroversion. Clinical utility of the inventory was discussed.

Adult↗
PubMed2001

Principal components analysis of protein structure ensembles calculated using NMR data.

One important problem when calculating structures of biomolecules from NMR data is distinguishing converged structures from outlier structures. This paper describes how Principal Components Analysis (PCA) has the potential to classify calculated structures automatically, according to correlated structural variation across the population. PCA analysis has the additional advantage that it highlights regions of proteins which are varying across the population. To apply PCA, protein structures have to be reduced in complexity and this paper describes two different representations of protein structures which achieve this. The calculated structures of a 28 amino acid peptide are used to demonstrate the methods. The two different representations of protein structure are shown to give equivalent results, and correct results are obtained even though the ensemble of structures used as an example contains two different protein conformations. The PCA analysis also correctly identifies the structural differences between the two conformations.

Macromolecular Substances↗
PubMed2004

Discrimination of normal and malignant gastric tissues with FTIR spectroscopy and principal component analysis.

In this paper, the identification of normal and malignant gastric tissues, including 11 cases of cancerous tissues and 10 cases of normal tissues, was investigated using mid-IR spectroscopy and principal componentanalysis (PCA). The results indicated that the difference between cancerous and normal tissues was found in the first principal component. The IR detection and PCA results are in agreement with the biopsy results. The combination of these two methods might provide a new opportunity for clinical application.

Algorithms↗
PubMed2002

QSAR of human factor Xa inhibitor N2-aroylanthranilamides using principal component factor analysis.

Quantitative structure-activity relationship (QSAR) study of human factor Xa inhibitor N2-aroylanthranilamides, recently reported by Yee et al. (J. Med. Chem., 43, 873-882), has been performed using principal component factor analysis as the preprocessing step. The study reveals that presence of electron-donating R2 substituent at the para position (with respect to the amide linkage) is conducive to the binding affinity, whereas a meta R2 substituent decreases the affinity. Again, electron-donating R1 substituents with less bulk and optimum hydrophilic-lipophilic balance (particularly, methyl and methoxy groups) favor the activity. The study further suggests that electron-withdrawing R3 substituents are detrimental for the activity, whereas bulkier R4 substituents (particularly NHSO2Me group) increase the activity.

Antithrombin III↗
PubMedDate not supplied

Analysis of the ST-segment in terms of principal components: application on multichannel magnetocardiographic recordings.

Parameterization of the ST-segment is used as a tool for risk stratification for patients to suffer from ventricular tachycardia. This parameterization is performed in terms of Principal Component Analysis (PCA) applied on multichannel magnetocardiographic (MCG) recordings. 55-channel MCG was recorded from 14 normal persons, 10 patients with CHD, 14 patients with MI, and six patients with VT. We found a significantly (p < 0.05) lower PCA-score in patients with MI compared to normals. The lowest PCA-score was found in VT patients. Significant differences can be found between VT patients and normals and also between VT patients and CHD patients.

Adult↗
PubMed2003

Localization of the event-related potential novelty response as defined by principal components analysis.

Recent research indicates that novel stimuli elicit at least two distinct components, the Novelty P3 and the P300. The P300 is thought to be elicited when a context updating mechanism is activated by a wide class of deviant events. The functional significance of the Novelty P3 is uncertain. Identification of the generator sources of the two components could provide additional information about their functional significance. Previous localization efforts have yielded conflicting results. The present report demonstrates that the use of principal components analysis (PCA) results in better convergence with knowledge about functional neuroanatomy than did previous localization efforts. The results are also more convincing than that obtained by two alternative methods, MUSIC-RAP and the Minimum Norm. Source modeling on 129-channel data with BESA and BrainVoyager suggests the P300 has sources in the temporal-parietal junction whereas the Novelty P3 has sources in the anterior cingulate.

Acoustic Stimulation↗
PubMed2004

Adaptive consensus principal component analysis for on-line batch process monitoring.

As the regulations of effluent quality are increasingly stringent, the on-line monitoring of wastewater treatment processes becomes very important. Multivariate statistical process control such as principal component analysis (PCA) has found wide applications in process fault detection and diagnosis using measurement data. In this work, we propose a consensus PCA algorithm for adaptive wastewater treatment process monitoring. The method overcomes the problem of changing operating conditions by updating the covariance structure recursively. The algorithm does not require any estimation compared to typical multiway PCA models. With this method process disturbances are detected in real time and the responsible measurements are directly identified. The presented methodology is successfully applied to a pilot-scale sequencing batch reactor for wastewater treatment.

Air Pollutants↗
PubMed2006

Constructing socio-economic status indices: how to use principal components analysis.

Theoretically, measures of household wealth can be reflected by income, consumption or expenditure information. However, the collection of accurate income and consumption data requires extensive resources for household surveys. Given the increasingly routine application of principal components analysis (PCA) using asset data in creating socio-economic status (SES) indices, we review how PCA-based indices are constructed, how they can be used, and their validity and limitations. Specifically, issues related to choice of variables, data preparation and problems such as data clustering are addressed. Interpretation of results and methods of classifying households into SES groups are also discussed. PCA has been validated as a method to describe SES differentiation within a population. Issues related to the underlying data will affect PCA and this should be considered when generating and interpreting results.

Data Collection↗
PubMed2005

Metabolic fingerprinting of Ephedra species using 1H-NMR spectroscopy and principal component analysis.

The metabolomic analysis of Ephedra species was performed using 1H-NMR spectroscopy and multivariate data analysis. A broad range of metabolites could be detected by 1H-NMR spectroscopy without any chromatographic separation. The principal component analysis used to reduce the huge data set obtained from the 1H-NMR spectra of the plant extracts clearly discriminated three different Ephedra species. The major differences in Ephedra sinica, Ephedra intermedia and Ephedra distachya var. distachya were found to be due to benzoic acid analogues in the aqueous fraction and ephedrine-type alkaloids in the organic fraction. Based on this metabolomic recognition, one of nine commercial Ephedra materials evaluated was shown to be a mixture of Ephedra species. This method will be a useful tool for chemotaxonomic analysis and authentification of Ephedra species including quality control of plant materials.

Ephedra↗
PubMed1977

Principal component analysis of the elongation of metacarpal and phalangeal bones.

A hypothesis that the first principal component computed from the covariance matrix of logarithms reflected the specific growth rates of corresponding bones was taken to analyze the growth pattern of the tubular bones of the hand. The total length of 19 tubular bones of the right hand was measured on standardized radiographs of Japanese children (33 boys, 33 girls). Metacarpals in boys and bones of the fifth digit in girls showed higher growth coefficients. The second, third and fourth proximal, and the third and fourth middle phalanges showed lower coefficients for both sexes. These observations suggest the signs of proximal row dominance in boys and of fifth ray dominance in girls in the elongation of the hand bones. A marked sex difference was found in the fifth middle phalanx. In girls the growth coefficients of this bone was much larger than any other bones, but was moderate in boys.

Adolescent↗
PubMed2001

Principal component analysis of mass spectra of peptides generated from the tryptic digestion of protein mixtures.

Principal component analysis (PCA) has been used to analyse mass spectral peptide profiles obtained from the enzymatic digestion of standard protein mixtures. Scores and loadings plots clearly revealed peptide fragments that differentiated one protein mixture from another. Peptide map search results identified with a high degree of certainty any additional proteins in these mixtures. As a proof-of-concept this methodology was applied to hepatic protein mixtures obtained from rats treated with two hepatotoxic compounds: methapyriline and SB-219994. Liver proteins were extracted, pre-separated by one-dimensional polyacrylamide gel electrophoresis, subjected to tryptic digestion and analysed by mass spectrometry. Two up-regulated proteins, glutathione S-transferase with methapyrilene and peroxisomal bifunctional enzyme with SB-219994, were identified in this manner.

Amino Acid Sequence↗