scholarly journals Multi-Dimensional Statistical Analysis of Spatial Structures of DNA in Interfaces Complexes of Homeodomain-DNA Family: Helical Parameters

2020 ◽  
Author(s):  
R.V. Polozov ◽  
T.I. Grokhlina ◽  
L.A. Panchenko ◽  
V.V. Ivanov
Keyword(s):  
Statistical Analysis ◽  
Spatial Structures ◽  
Helical Parameters

scholarly journals Spatial and correlation analysis of engineering-geological survey data for logistics center construction

Vestnik MGSU ◽  
2019 ◽  
pp. 976-990
Author(s):  
Konstantin V. Kurguzov ◽  
Igor K. Fomenko
Keyword(s):  
Statistical Analysis ◽  
Survey Data ◽  
Spatial Correlation ◽  
Geostatistical Analysis ◽  
Geological Survey ◽  
Spatial Structures ◽  
Geostatistical Methods ◽  
Lack Of Information ◽  
Survey Report ◽  
Deformation Features

Introduction: at present, the geostatistical methodology is broadly used abroad for constructing spatial-correlation and spatial-stochastic models of lithoengineering systems, including description and analysis of soil body heterogeneity. The main goal of this work is an attempt to evaluate the possibility of generating a spatial-correlation model of lithoengineering space based on survey data which could be used for subsequent simulation and deterministic-stochastic analysis of geotechnical structures as well as when designing bases and foundations. Materials and methods: main input parameters for spatial analysis were geological survey report and cone-penetration test (CPT) data. The data were analyzed using descriptive statistic methods, with the calculation of particular and ambiguous values and using statistical software STATISTICA. Later use of the results of the statistical analysis aims at the application of geostatistical interpolation models (kriging) for generating spatial structures of deformation features. The article elaborates experimental correlation functions (variograms) to validate the developed spatial structures. The functions show not only the validity of the spatial simulation but also a level of heterogeneity of the researched soil body. Results: the statistical analysis of the initial data showed relative homogeneity of the researched soil body properties what is substantiated by GOST 20522 instructions. Nevertheless, the geostatistical analysis resulted in the opposite conclusion. Principally, this is due to the lack of information on the researched geological medium. Conclusions: requirements of current Russian standard GOST 20522 do not contain a sufficient amount of information for geostatistical analysis and simulation of a soil body based on modern geostatistical methods. As a result, data of standard engineering-geological researches cannot be used for developing digital foundation models as well as for using probabilistic approaches in geotechnics.

scholarly journals The study of interhelical angles in the structural motifs formed by two helices

2017 ◽  
Vol 12 (1) ◽  
pp. 83-101 ◽  
Author(s):  
Д.А. Тихонов ◽  
D.A. Tikhonov
Keyword(s):  
Statistical Analysis ◽  
Protein Data Bank ◽  
Entire Range ◽  
Structural Organization ◽  
Protein Structures ◽  
Data Bank ◽  
Acute Angle ◽  
Spatial Structures ◽  
Pass Through ◽  
Selection Of

In this paper a statistical analysis of distributions of inter-helical angles in pairs of consecutive and connected α-helices in spatial structures of proteins is presented. A number of rules for selection of the helical pairs from a set of protein structures obtained from the Protein Data Bank (PDB) were developed. The set of helical pairs has been analyzed for the purpose of classification and finding out the features of protein structural organization. All pairs of connected helices were divided into three subsets according to the criterion of crossing of projections of the helices on parallel planes, which pass through the axes of the helices. It is shown that the distribution of all types of helical pairs, whose projections do not cross each others, covers almost the entire range of inter-helical angles. The distribution have a single maximum which is close to right angle. Most pairs in this set constitute helical pairs consisting of α- and 310-helices, and most pairs with the crossing projections of helices are helical pairs formed by two α-helices. It is also shown that a great amount of the pairs of connected α-helices has acute angle 20° ≤ φ ≤ 60° between the axes of the helices. The distribution of all types of helical pairs depending on the length of the inter-helical connections was also analyzed. It is shown that the structures with short connections occur most often in all the subsets.

Statistical analysis of classification

1966 ◽  
Vol 24 ◽  
pp. 188-189
Author(s):  
T. J. Deeming
Keyword(s):  
Multivariate Analysis ◽  
Statistical Analysis ◽  
Classification Scheme ◽  
Analytical Procedure ◽  
Narrow Band ◽  
Scientific Research ◽  
Maximum Amount ◽  
Amount Of Information

If we make a set of measurements, such as narrow-band or multicolour photo-electric measurements, which are designed to improve a scheme of classification, and in particular if they are designed to extend the number of dimensions of classification, i.e. the number of classification parameters, then some important problems of analytical procedure arise. First, it is important not to reproduce the errors of the classification scheme which we are trying to improve. Second, when trying to extend the number of dimensions of classification we have little or nothing with which to test the validity of the new parameters.Problems similar to these have occurred in other areas of scientific research (notably psychology and education) and the branch of Statistics called Multivariate Analysis has been developed to deal with them. The techniques of this subject are largely unknown to astronomers, but, if carefully applied, they should at the very least ensure that the astronomer gets the maximum amount of information out of his data and does not waste his time looking for information which is not there. More optimistically, these techniques are potentially capable of indicating the number of classification parameters necessary and giving specific formulas for computing them, as well as pinpointing those particular measurements which are most crucial for determining the classification parameters.

The three-dimensional structure of frozen-hydrated left- and right-handed forms of bacterial flagellar filaments from an identical serotype

1986 ◽  
Vol 44 ◽  
pp. 298-299
Author(s):  
S. Trachtenberg ◽  
D. J. DeRosier
Keyword(s):  
Ionic Strength ◽  
Basal Body ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
Protein Species ◽  
Liquid Environment ◽  
Bacterial Flagellum ◽  
Left And Right ◽  
Rotary Motor ◽  
Helical Parameters

The bacterial cell is propelled through the liquid environment by means of one or more rotating flagella. The bacterial flagellum is composed of a basal body (rotary motor), hook (universal coupler), and filament (propellor). The filament is a rigid helical assembly of only one protein species — flagellin. The filament can adopt different morphologies and change, reversibly, its helical parameters (pitch and hand) as a function of mechanical stress and chemical changes (pH, ionic strength) in the environment.

Quantitative parallel EELS spectrum imaging developed as a new tool in AEM

1992 ◽  
Vol 50 (2) ◽  
pp. 1202-1203
Author(s):  
Gianluigi Botton ◽  
Gilles L'espérance
Keyword(s):  
Statistical Analysis ◽  
Spatial Resolution ◽  
Personal Computer ◽  
Systematic Study ◽  
Present Author ◽  
Chemical Elements ◽  
Detection Limits ◽  
Research Groups ◽  
Quantitative Performance ◽  
Spectrum Imaging

As interest for parallel EELS spectrum imaging grows in laboratories equipped with commercial spectrometers, different approaches were used in recent years by a few research groups in the development of the technique of spectrum imaging as reported in the literature. Either by controlling, with a personal computer both the microsope and the spectrometer or using more powerful workstations interfaced to conventional multichannel analysers with commercially available programs to control the microscope and the spectrometer, spectrum images can now be obtained. Work on the limits of the technique, in terms of the quantitative performance was reported, however, by the present author where a systematic study of artifacts detection limits, statistical errors as a function of desired spatial resolution and range of chemical elements to be studied in a map was carried out The aim of the present paper is to show an application of quantitative parallel EELS spectrum imaging where statistical analysis is performed at each pixel and interpretation is carried out using criteria established from the statistical analysis and variations in composition are analyzed with the help of information retreived from t/γ maps so that artifacts are avoided.

Intraindividual Variability in Development Within and Between Individuals

2001 ◽  
Vol 6 (3) ◽  
pp. 187-193 ◽  
Author(s):  
John R. Nesselroade
Keyword(s):  
Statistical Analysis ◽  
Research Design ◽  
Intraindividual Variability ◽  
Factor Analytic

A focus on the study of development and other kinds of changes in the whole individual has been one of the hallmarks of research by Magnusson and his colleagues. A number of different approaches emphasize this individual focus in their respective ways. This presentation focuses on intraindividual variability stemming from Cattell's P-technique factor analytic proposals, making several refinements to make it more tractable from a research design standpoint and more appropriate from a statistical analysis perspective. The associated methods make it possible to study intraindividual variability both within and between individuals. An empirical example is used to illustrate the procedure.

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