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Results for “Principal Component Analysis”

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PubMed1990

Development of feature detectors by self-organization. A network model.

We present a two-layered network of linear neurons that organizes itself as to extract the complete information contained in a set of presented patterns. The weights between layers obey a Hebbian rule. We propose a local anti-Hebbian rule for lateral, hierarchically organized weights within the output layer. This rule forces the activities of the output units to become uncorrelated and the lateral weights to vanish. The weights between layers converge to the eigenvectors of the covariance matrix of input patterns, i.e., the network performs a principal component analysis, yielding all principal components. As a consequence of the proposed learning scheme, the output units become detectors of orthogonal features, similar to ones found in the brain of mammals.

Color Perception↗

PubMed1999

Feature extraction through LOCOCODE.

Low-complexity coding and decoding (LOCOCODE) is a novel approach to sensory coding and unsupervised learning. Unlike previous methods, it explicitly takes into account the information-theoretic complexity of the code generator. It computes lococodes that convey information about the input data and can be computed and decoded by low-complexity mappings. We implement LOCOCODE by training autoassociators with flat minimum search, a recent, general method for discovering low-complexity neural nets. It turns out that this approach can unmix an unknown number of independent data sources by extracting a minimal number of low-complexity features necessary for representing the data. Experiments show that unlike codes obtained with standard autoencoders, lococodes are based on feature detectors, never unstructured, usually sparse, and sometimes factorial or local (depending on statistical properties of the data). Although LOCOCODE is not explicitly designed to enforce sparse or factorial codes, it extracts optimal codes for difficult versions of the "bars" benchmark problem, whereas independent component analysis (ICA) and principal component analysis (PCA) do not. It produces familiar, biologically plausible feature detectors when applied to real-world images and codes with fewer bits per pixel than ICA and PCA. Unlike ICA, it does not need to know the number of independent sources. As a preprocessor for a vowel recognition benchmark problem, it sets the stage for excellent classification performance. Our results reveal an interesting, previously ignored connection between two important fields: regularizer research and ICA-related research. They may represent a first step toward unification of regularization and unsupervised learning.

Algorithms↗

PubMed2004

PCR-array gene expression profiling of hepatocellular carcinoma.

Many trials using DNA microarrays have been reported for various human malignancies, but an efficient molecular diagnostic system has yet to be established. Here, we adopted a high throughput quantitative PCR-array system based on adaptor-tagged competitive PCR (ATAC-PCR), as a novel technique for gene expression profiling of hepatocellular carcinoma (HCC). This PCR-array contained 3,072 genes derived from three different cDNA libraries, including 298 additional known genes suspected to be involved in hepatocarcinogenesis. Using this PCR-array with 20 pairs of liver tissues (20 HCC, 20 surrounding nontumor liver), we identified a total of 117 genes differing in expression levels in the two liver tissues. Hierarchical clustering analysis and principal component analysis with these genes revealed distinct gene expression patterns in the HBV-positive group and the HCV-positive groups. Among 117 genes, only 7 (GPAA1, TMEM9, FACL4, ADFP, MAWBP, PACE4, FOS) were common to both groups. In conclusion, this PCR-array analysis with an appropriate set of genes is considered useful for gene expression profiling of HCC, and we identified some genes which may play a common key role in hepatocarcinogenesis.

Aged↗

PubMed2005

Application of oligonucleotide microarrays for bacterial source tracking of environmental Enterococcus sp. isolates.

In an effort towards adapting new and defensible methods for assessing and managing the risk posed by microbial pollution, we evaluated the utility of oligonucleotide microarrays for bacterial source tracking (BST) of environmental Enterococcus sp. isolates derived from various host sources. Current bacterial source tracking approaches rely on various phenotypic and genotypic methods to identify sources of bacterial contamination resulting from point or non-point pollution. For this study Enterococcus sp. isolates originating from deer, bovine, gull, and human sources were examined using microarrays. Isolates were subjected to Box PCR amplification and the resulting amplification products labeled with Cy5. Fluorescent-labeled templates were hybridized to in-house constructed nonamer oligonucleotide microarrays consisting of 198 probes. Microarray hybridization profiles were obtained using the ArrayPro image analysis software. Principal Components Analysis (PCA) and Hierarchical Cluster Analysis (HCA) were compared for their ability to visually cluster microarray hybridization profiles based on the environmental source from which the Enterococcus sp. isolates originated. The PCA was visually superior at separating origin-specific clusters, even for as few as 3 factors. A Soft Independent Modeling (SIM) classification confirmed the PCA, resulting in zero misclassifications using 5 factors for each class. The implication of these results for the application of random oligonucleotide microarrays for BST is that, given the reproducibility issues, factor-based variable selection such as in PCA and SIM greatly outperforms dendrogram-based similarity measures such as in HCA and K-Nearest Neighbor KNN.

Animals↗

PubMed2006

Biogenic amines in natural ciders.

Biogenic amines play an important physiological role in mammals, and high amounts of some exogenous amines in human diet may contribute to a wide variety of toxic effects. These amines are commonly found in many foodstuffs, particularly in fermented products such as cheese, meat products, beer, wine, and ciders. Here, the level of biogenic amines in some natural ciders was examined. Twenty-four samples of cider purchased from commercial sources were analyzed by reverse-phase high-performance liquid chromatography and fluorescence detection after precolumn derivatization with o-phthaldialdehyde. Amine levels were variable, ranging from not detected to 23 mg/liter. The average level of total biogenic amines in ciders was 5.94 +/- 8.42 mg/liter. Putrescine, histamine, and tyramine were the prevailing amines being present in 50.0, 37.5, and 33.3% of the ciders studied; very small amounts of ethylamine and phenylethylamine were observed in only one sample. Other cider parameters were analyzed to determine whether they affect the biogenic amine content in ciders, and the results were evaluated by applying cluster analysis and principal component analysis. Ciders that showed lower glycerol contents and higher amounts of 1,3-propanediol had much higher levels of histamine, tyramine, and putrescine, suggesting a high activity of lactic acid bacteria during cider making and thus the need for effective control of lactic acid bacteria.

Beverages↗

PubMed2004

Metal leachability and anthropogenic signal in roadside soils estimated from sequential extraction and stable lead isotopes.

Several roadside soil samples were collected at two field sites in Sweden. They were analysed for total elemental content (using both ICP-MS and XRF) and stable lead isotopes. Extraction with deicing salt solution and sequential extraction were performed in order to elucidate the potential mobility due to the use of deicing agents. The total concentrations of elements, especially lead, have decreased and lead is presently almost at background concentrations (15-51 ppm for surface samples). However, the isotopic signature indicates that old gasoline lead still is left at the site constructed prior to 1975. The field site constructed in 1992 showed, however, no 206Pb/207Pb ratio below 1.14. Only minor amounts were leached using deicing salt solutions; for lead only 0.29%, on average, was extracted indicating that the mobile fraction already was released. Sequential extraction indicated that lead mainly was associated with reducible (34.4%) and oxidisable (35.4%) fractions. Exchangable and acid soluble fractions contained 20.3% while 10.0% was found in the residual fraction. The salt extraction released, however, very low concentrations indicating that most in fraction 1 is acid soluble (e.g. carbonates). Tungsten was also found at high concentrations indicating a possible impact from studded tires. For tungsten the following composition was obtained: residual (48.0%) > oxidisable (47.6%) > reducible (3.3%) > exchangeable/acid soluble (1.1%). From the isotopic studies it was also suggested that the order for incorporating anthropogenic lead into soils is exchangeable/carbonates > (hydr)oxides > organic matter > residual. The multivariate technique principal component analysis (PCA) seems promising for evaluating large sequential extraction datasets.

Environmental Monitoring↗

PubMed2006

Classification of lactic acid bacteria with UV-resonance Raman spectroscopy.

UV-resonance Raman spectroscopy is applied as a method for the identification of lactic acid bacteria from yogurt. Eight different strains of bacteria from Lactobacillus acidophilus, L. delbrueckii ssp. bulgaricus, and Streptococcus thermophilus were investigated. At an excitation wavelength of 244 nm signals from nucleic acids and proteins are selectively enhanced. Classification was accomplished using different chemometric methods. In a first attempt, the unsupervised methods hierarchical cluster analysis and principal component analysis were applied to investigate natural grouping in the data. In a second step the spectra were analyzed using several supervised methods: K-nearest neighbor classifier, nearest mean classifier, linear discriminant analysis, and support vector machines.

Cluster Analysis↗

PubMed2004

PCA in studying coordination and variability: a tutorial.

OBJECTIVE: To explain and underscore the use of principal component analysis in clinical biomechanics as an expedient, unbiased means for reducing high-dimensional data sets to a small number of modes or structures, as well as for teasing apart structural (invariant) and variable components in such data sets. DESIGN: The method is explained formally and then applied to both simulated and real (kinematic and electromyographic) data for didactical purposes, thus illustrating possible applications (and pitfalls) in the study of coordinated movement. BACKGROUND: In the sciences at large, principal component analysis is a well-known method to remove redundant information in multidimensional data sets by means of mode reduction. At present, principal component analysis is starting to penetrate the fundamental and clinical study of human movement, which amplifies the need for an accessible explanation of the method and its possibilities and limitations. Besides mode reduction, we discuss principal component analysis in its capacity as a data-driven filter, allowing for a separation of invariant and variant properties of coordination, which, arguably, is essential in studies of motor variability. METHODS: Principal component analysis is applied to kinematic and electromyographic time series obtained during treadmill walking by healthy humans. RESULTS: Common signal structures or modes are identified in the time series that turn out to be readily interpretable. In addition, the identified coherent modes are eliminated from the data, leaving a filtered, residual pattern from which useful information may be gleaned regarding motor variability. CONCLUSIONS: Principal component analysis allows for the detection of modes (information reduction) in both kinematic and electromyographic data sets, as well as for the separation of invariant structure and variance in those data sets. RELEVANCE: Principal component analysis can be successfully applied to movement data, both as feature extractor and as data-driven filter. Its potential for the (clinical) study of human movement sciences (e.g., diagnostics and evaluation of interventions) is evident but still largely untapped.

Algorithms↗

PubMed2002

Levels and distribution patterns of polychlorinated biphenyl congeners in surface sediments from Galicia coast (Northwestern, Spain) according to granulometric characteristics.

In order to know distribution patterns of polychlorinated biphenyl congeners in the marine environment from Galida, PCBs n degrees 31, 28, 52, 101, 118, 153, 105, 138, 156 and 180 were isolated by Soxhlet extraction from three fractions of different particle size (<0.063 mm, 0.063-0.2 mm and >0.2 mm) in surface marine sediments; the quantification was performed using GC-MS and GC-ECD. Distribution of PCB congeners was shifted in favour of higher chlorinated compounds (CBs 138,153 and 180) and highly correlated to TOC content. In general, the finest fractions (<0.063 mm) of sediment presented the highest loadings of PCBs, only the sediment from As Pías zone exhibited the highest concentration of chlorinated congeners in the coarsest fraction. CB 52 concentration, slightly volatile compound, was related to water temperature. By means of multivariate techniques of data exploration as hierarchical duster analysis and principal components analysis, sediment samples from un-contaminated and slightly contaminated areas were clearly separated; groupings between samples from nearby zones appeared.

Geologic Sediments↗

PubMed2026

Genome-Wide SNP Characterisation of Three Kazakh Sheep Breeds: Kazakh Fat-Tailed Coarse-Wool, Degeres, and Etti Merino.

Kazakhstan's sheep portfolio underpins much of the country's mutton and wool production, yet several of its principal breeds remain genomically uncharacterised. The aim of this study was to characterise the genomic diversity, population structure, and global phylogenetic placement of three economically important Kazakh breeds and to determine whether they constitute separate gene pools requiring independent management. We present the first genome-wide SNP characterisation to include the Degeres (DE), the Etti Merino (EM), and the Kazakh fat-tailed coarse-wool (KKG) breeds simultaneously. A total of 1497 animals (DE = 354, EM = 642, KKG = 501) sampled across seven production households were genotyped and, after quality control, analysed at 42,279 SNPs, of which 22,766 LD-pruned markers were used for principal component analysis and AMOVA. We applied principal component analysis (PCA), pairwise FST, analysis of molecular variance (AMOVA), neighbour-joining phylogenetics, model-based ancestry estimation (ADMIXTURE), and Hill-number diversity profiling, and projected the breeds against the global Ovine SNP50 HapMap panel (74 reference breeds, 2819 animals; 37,685 shared SNPs). All three breeds retained uniformly high within-breed diversity (expected heterozygosity 0.413-0.417) with fixation indices at or near zero. AMOVA partitioned 94.03% of variance within breeds (ΦST = 0.060, p < 0.001). PCA, phylogeny, and ADMIXTURE concordantly resolved three breed-specific clusters at K = 3, with a maximum interbreed FST of 0.038 within the study dataset. Against the global panel, EM was genetically closest to Merino and Merino-derived reference breeds (pooled FST = 0.017) and substantially more distant from Southwest Asian sheep (FST = 0.045), whereas DE and KKG showed the reciprocal pattern (FST = 0.027 and 0.020 to Southwest Asia, 0.052 to the Merino group). DE additionally displayed the heterozygote excess and partial admixture expected of an incompletely consolidated composite. These results delineate three distinct gene pools and carry direct implications for breed management and the conservation of genomic diversity in Kazakhstani sheep.

ADMIXTURE↗

PubMed2004

[Content of inorganic elements of Salvia miltiorrhiza root in different area and physicochemical properties of its growing soil].

OBJECTIVE: To provide basis of environmental factors of genuine crude drug, Salvia miltiorrhiza root. METHOD: On-the-spot investigation and indoor chemical analysis were made to study the physicochemical properties of growing soil and content of inorganic elements of S. miltiorrhiza, and obtained data were analysed with SPSS 10.0 software. RESULT: S. miltiorrhiza root of high harvest area accumulated Cu and Zn. In soil principal component analysis, no principal component was obvious. So the drug has good adaptability in ecological environment of soil. CONCLUSION: Ecological environment of soil isn't leading factor in forming genuine crude S. miltiorrhiza.

China↗

PubMed2001

High-resolution metabolic phenotyping of genetically and environmentally diverse potato tuber systems. Identification of phenocopies.

We conducted a comprehensive metabolic phenotyping of potato (Solanum tuberosum L. cv Desiree) tuber tissue that had been modified either by transgenesis or exposure to different environmental conditions using a recently developed gas chromatography-mass spectrometry profiling protocol. Applying this technique, we were able to identify and quantify the major constituent metabolites of the potato tuber within a single chromatographic run. The plant systems that we selected to profile were tuber discs incubated in varying concentrations of fructose, sucrose, and mannitol and transgenic plants impaired in their starch biosynthesis. The resultant profiles were then compared, first at the level of individual metabolites and then using the statistical tools hierarchical cluster analysis and principal component analysis. These tools allowed us to assign clusters to the individual plant systems and to determine relative distances between these clusters; furthermore, analyzing the loadings of these analyses enabled identification of the most important metabolites in the definition of these clusters. The metabolic profiles of the sugar-fed discs were dramatically different from the wild-type steady-state values. When these profiles were compared with one another and also with those we assessed in previous studies, however, we were able to evaluate potential phenocopies. These comparisons highlight the importance of such an approach in the functional and qualitative assessment of diverse systems to gain insights into important mediators of metabolism.

Amino Acids↗

PubMed2002

Molecular dynamics simulation of 7, 8-dihydro-8-oxoguanine DNA.

To elucidate the effect of guanine lesion produced by the oxidative damage on DNA, 1 nanosecond molecular dynamics simulations of native and oxidized DNA were performed. The target DNA molecules are dodecamer duplex d(CGCGAATTCGCG)(2) and its derivative duplex d(C(1)G(2)C(3)(8-oxoG)(4)A(5)A(6)T(7)T(8)C(9)G(10)C(11)G(12).d(C(13)G(14)C(15)G(16)A(17)A(18)T(19)T(20)C(21)G(22)C(23)G(24), which has one oxidized guanine, 7, 8-dihydro-8-oxoguanine (8-oxoG), at the fourth position. The local structural change due to the lesion of 8-oxoG and the global dynamic structure of the 8-oxoG DNA were studied. It was found that the 8-oxoG DNA remained structurally stable during the simulation due to newly produced hydrogen bonds around the (8-oxoG)(4) residue. However, there were distinguishable differences in structural parameters and dynamic property in the 8-oxoG DNA. The conformation around the (8-oxoG)(4) residue departed from the usual conformation of native DNA and took an unique conformation of epsilon-zeta in B(II) conformation and chi in high anti orientation at the (8-oxoG)(4) residue, and adopted a very low helical twist angle at the C(3):G(22)-(8-oxoG)(4):C21) step. Further analysis by principal component analysis indicated that the formation of the hydrogen bonds around the (8-oxoG)(4) residue plays a role as a trigger for the conformational transition of the 8-oxoG DNA in the conformational space.

DNA↗

PubMed2005

Classification of Ilex species based on metabolomic fingerprinting using nuclear magnetic resonance and multivariate data analysis.

The metabolomic analysis of 11 Ilex species, I. argentina, I. brasiliensis, I. brevicuspis, I. dumosavar. dumosa, I. dumosa var. guaranina, I. integerrima, I. microdonta, I. paraguariensis var. paraguariensis, I. pseudobuxus, I. taubertiana, and I. theezans, was carried out by NMR spectroscopy and multivariate data analysis. The analysis using principal component analysis and classification of the (1)H NMR spectra showed a clear discrimination of those samples based on the metabolites present in the organic and aqueous fractions. The major metabolites that contribute to the discrimination are arbutin, caffeine, phenylpropanoids, and theobromine. Among those metabolites, arbutin, which has not been reported yet as a constituent of Ilex species, was found to be a biomarker for I. argentina,I. brasiliensis, I. brevicuspis, I. integerrima, I. microdonta, I. pseudobuxus, I. taubertiana, and I. theezans. This reliable method based on the determination of a large number of metabolites makes the chemotaxonomical analysis of Ilex species possible.

Analysis of Variance↗

PubMed2004

A new approach in clinical neuropsychology to the assessment of spatial working memory: the block suppression test.

The Block Suppression Paradigm developed by Beblo, Klaver, Grubich, Wachowius, and Herrmann (1999) is based on the Corsi Block tapping test and requires that a subject reproduces every 2nd block in a given sequence. Results from two studies of a standardized version, the Block Suppression Test (BST), are presented here. In Study 1 the BST was administered to 48 healthy subjects along with a battery of comprehensive neuropsychological tests. The reliability of the BST proved satisfactory under psychometric analysis, while Principal Component Analysis (PCA) confirmed its validity. In Study 2 the BST was administered to a clinical sample of 31 brain-damaged patients to demonstrate its clinical practicability.

Adult↗

PubMed2003

A method for dynamic spectrophotometric measurements in vivo using principal component analysis-based spectral deconvolution.

A method was developed for dynamic spectrophotometric measurements in vivo in the presence of non-specific spectral changes due to external disturbances. This method was used to measure changes in mitochondrial respiratory pigment redox states in photoreceptor cells of live, white-eyed mutants of the blowfly Calliphora vicina. The changes were brought about by exchanging the atmosphere around an immobilised animal from air to N2 and back again by a rapid gas exchange system. During an experiment reflectance spectra were measured by a linear CCD array spectrophotometer. This method involves the pre-processing steps of difference spectra calculation and digital filtering in one and two dimensions. These were followed by time-domain principal component analysis (PCA). PCA yielded seven significant time domain principal component vectors and seven corresponding spectral score vectors. In addition, through PCA we also obtained a time course of changes common to all wavelengths-the residual vector, corresponding to non-specific spectral changes due to preparation movement or mitochondrial swelling. In the final step the redox state time courses were obtained by fitting linear combinations of respiratory pigment difference spectra to each of the seven score vectors. The resulting matrix of factors was then multiplied by the matrix of seven principal component vectors to yield the time courses of respiratory pigment redox states. The method can be used, with minor modifications, in many cases of time-resolved optical measurements of multiple overlapping spectral components, especially in situations where non-specific external influences cannot be disregarded.

Animals↗

PubMed2005

The use of autecological and environmental parameters for establishing the status of lichen vegetation in a baseline study for a long-term monitoring survey.

In 1997 the ecological characteristics of the epiphytic species (83 lichens and two algae) of an urban area (Grenoble, France) were determined. Seven autecological indices were used to characterize the lichen ecology: illumination index, humidity index, pH of bark, nutrient status of substratum, ecological index of IAP and frequency. Six clusters (A1-A6) were defined using cluster analysis and principal component analysis. Seven environmental parameters characterizing the stations and the lichen releves were also used: elevation, parameters of artificiality (urbanization, traffic and local land use), IAP, and the percentage of nitrophytic and acidophytic species. Six clusters (B1-B6) were defined using cluster analysis and canonical correspondence analysis. Four clusters (C1-C4) were finally defined using an empirical integrated method combining the autecological and environmental parameters. This final clustering which established the status of the lichen vegetation in 1997 can be reliably used as a baseline study to effectively monitor environmental changes in this urban area.

Biodiversity↗

PubMed2004

Microsatellite DNA suggests regional structure in the fusiform rust fungus Cronartium quercuum f. sp fusiforme.

This paper reports results obtained from microsatellite DNA analysis of genetic structure for populations of the native fungus Cronartium quercuum f. sp fusiforme infecting loblolly pine (Pinus taeda L.) over much of this host's natural range. Mostly all fusiform rust galls formed under field conditions are produced as a result of infection and colonization by haploid mycelium originating from a single basidiospore of C. quercuum fusiforme. If multiple infections do occur, then only a single haplotype must ultimately dominate and be responsible for gall formation. High levels of microsatellite variability exist in C. quercuum fusiforme and most of this variation occurs within local populations (average 88.4%). A statistically significant proportion, however, is found among populations, and the magnitude of this differentiation is closely associated with geographic distance between populations. Unweighted pair-group mean analysis and principal components analysis both indicate that at least four genetically distinct regional groups of C. quercuum fusiforme exist in the south Atlantic and Gulf coastal plains. In summary, the distribution of genetic variability in C. quercuum fusiforme is consistent with a hypothesis of at least four metapopulations with gene flow occurring less among regions than among populations within regions, and where overall levels of gene migration are related to geographic distance between populations.

Basidiomycota↗