Search results for "Component analysis"
showing 10 items of 562 documents
Effect of natamycin on the enumeration, genetic structure and composition of bacterial community isolated from soils and soybean rhizosphere
2004
Natamycin is commonly used to control fungal growth on agar media used for bacterial enumeration or strain isolation. However, there is no conclusive report on the possible effect of this antibiotic on bacterial growth or on the diversity of the recovered soil bacteria. Therefore, the possible effects of natamycin on the numbers of bacteria isolated at 12 degrees C from three different soils and soybean rhizosphere soil were investigated using natamycin concentrations ranging from 0 to 200 mg l(-1). Our results demonstrate that natamycin concentrations, which inhibit the growth of fungi on the media, have a small but significant inhibitory effect on the number of bacterial colony forming un…
Use of nodulation pattern, stress tolerance, nodC gene amplification, RAPD-PCR and RFLP-16S rDNA analysis to discriminate genotypes of Rhizobium legu…
2005
Twenty-seven new Rhizobium isolates were obtained from root nodules of wild and crop legumes belonging to the genera Vicia, Lathyrus and Pisum from different agroecological areas in central and southern Italy. A polyphasic approach including phenotypic and genotypic techniques was used to study their diversity and their relationships with other biovars and species of rhizobia. Analysis of symbiotic properties and stress tolerance tests revealed that wild isolates, showed a wide spectrum of nodulation and a marked variation in stress tolerance compared with reference strains tested in this study. All rhizobial isolates (except for the isolate CG4 from Galega officinalis) were presumptively i…
Polar Classification of Nominal Data
2013
Many modern systems record various types of parameter values. Numerical values are relatively convenient for data analysis tools because there are many methods to measure distances and similarities between them. The application of dimensionality reduction techniques for data sets with such values is also a well known practice. Nominal (i.e., categorical) values, on the other hand, encompass some problems for current methods. Most of all, there is no meaningful distance between possible nominal values, which are either equal or unequal to each other. Since many dimensionality reduction methods rely on preserving some form of similarity or distance measure, their application to such data sets…
Principal component analysis on molecular descriptors as an alternative point of view in the search of new Hsp90 inhibitors
2009
Inhibiting a protein that regulates multiple signal transduction pathways in cancer cells is an attractive goal for cancer therapy. Heat shock protein 90 (Hsp90) is one of the most promising molecular targets for such an approach. In fact, Hsp90 is a ubiquitous molecular chaperone protein that is involved in folding, activating and assembling of many key mediators of signal transduction, cellular growth, differentiation, stress-response and apoptothic pathways. With the aim to analyze which molecular descriptors have the higher importance in the binding interactions of these classes, we first performed molecular docking experiments on the 187 Hsp90 inhibitors included in the BindingDB, a pu…
Increasing the Coverage of Medicinal Chemistry-Relevant Space in Commercial Fragments Screening
2014
Analyzing the chemical space coverage in commercial fragment screening collections revealed the overlap between bioactive medicinal chemistry substructures and rule-of-three compliant fragments is only ∼25%. We recommend including these fragments in fragment screening libraries to maximize confidence in discovering hit matter within known bioactive chemical space, while incorporation of nonoverlapping substructures could offer novel hits in screening libraries. Using principal component analysis, polar and three-dimensional substructures display a higher-than-average enrichment of bioactive compounds, indicating increasing representation of these substructures may be beneficial in fragment …
Space-Time FPCA Clustering of Multidimensional Curves.
2018
In this paper we focus on finding clusters of multidimensional curves with spatio-temporal structure, applying a variant of a k-means algorithm based on the principal component rotation of data. The main advantage of this approach is to combine the clustering functional analysis of the multidimensional data, with smoothing methods based on generalized additive models, that cope with both the spatial and the temporal variability, and with functional principal components that takes into account the dependency between the curves.
Ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry to identify contaminants in water: an insight on environment…
2013
Ultra-high pressure liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QqTOF-MS) acquiring full scan MS data for quantification, and automatic data dependent information product ion spectra (IDA-MS/MS) without any predefinition of the ions by the user was checked for identifying organic contaminants in water samples. The use of a database with more than 2000 compounds achieved high confidence results for a wide number of contaminants based upon retention time, accurate mass, isotopic pattern and MS/MS library searching. More than 20 contaminants, mostly pharmaceuticals, but also mycotoxins and polyphenols were unambiguously identified. Furthermore, the combination of s…
Direct analysis in real-time high-resolution mass spectrometry as a valuable tool for polyphenols profiling in olive oil
2018
A fast and reliable method to characterize the polyphenolic compound profiles in extra virgin olive oil (EVOO) has been developed using direct analysis in real time (DART) and linear ion-trap Orbitrap mass spectrometry (LTQ-Orbitrap-MS). Hydroalcoholic extraction increased speed and reduced matrix effects, and DART-MS/MS ensured accurate analysis. Characterization of polyphenol fingerprinting in EVOO samples takes 2 min. This method exhibited proper linearity (R2 ≥ 0.99) in the range of 5–2500 μg g−1, limit of detection (LOD) of 1.5 μg g−1 (signal-to noise S/N = 3), and limits of quantitation (LOQs) of 5 μg g−1 (S/N = 10) for resveratrol (a polyphenol not detected in olive oil). Six spiked …
Discrete Derivatives for Atom-Pairs as a Novel Graph-Theoretical Invariant for Generating New Molecular Descriptors: Orthogonality, Interpretation an…
2013
This report presents a new mathematical method based on the concept of the derivative of a molecular graph (G) with respect to a given event (S) to codify chemical structure information. The derivate over each pair of atoms in the molecule is defined as ∂G/∂S(vi , vj )=(fi -2fij +fj )/fij , where fi (or fj ) and fij are the individual frequency of atom i (or j) and the reciprocal frequency of the atoms i and j, respectively. These frequencies characterize the participation intensity of atom pairs in S. Here, the event space is composed of molecular sub-graphs which participate in the formation of the G skeleton that could be complete (representing all possible connected sub-graphs) or comp…
Regression Wavelet Analysis for Lossless Coding of Remote-Sensing Data
2016
A novel wavelet-based scheme to increase coefficient independence in hyperspectral images is introduced for lossless coding. The proposed regression wavelet analysis (RWA) uses multivariate regression to exploit the relationships among wavelet-transformed components. It builds on our previous nonlinear schemes that estimate each coefficient from neighbor coefficients. Specifically, RWA performs a pyramidal estimation in the wavelet domain, thus reducing the statistical relations in the residuals and the energy of the representation compared to existing wavelet-based schemes. We propose three regression models to address the issues concerning estimation accuracy, component scalability, and c…