scholarly journals Analysis of the effects of related fingerprints on molecular similarity using an eigenvalue entropy approach

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Hiroyuki Kuwahara ◽  
Xin Gao
Keyword(s):  
Molecular Similarity ◽  
Chemical Compounds ◽  
Structural Similarity ◽  
Similarity Analysis ◽  
Optimal Selection ◽  
Two Dimensional ◽  
Chemical Fingerprints ◽  
Binary Features ◽  
Selection Of ◽  
Similarity Scores

AbstractTwo-dimensional (2D) chemical fingerprints are widely used as binary features for the quantification of structural similarity of chemical compounds, which is an important step in similarity-based virtual screening (VS). Here, using an eigenvalue-based entropy approach, we identified 2D fingerprints with little to no contribution to shaping the eigenvalue distribution of the feature matrix as related ones and examined the degree to which these related 2D fingerprints influenced molecular similarity scores calculated with the Tanimoto coefficient. Our analysis identified many related fingerprints in publicly available fingerprint schemes and showed that their presence in the feature set could have substantial effects on the similarity scores and bias the outcome of molecular similarity analysis. Our results have implication in the optimal selection of 2D fingerprints for compound similarity analysis and the identification of potential hits for compounds with target biological activity in VS.

scholarly journals Analysis of the effects of related fingerprints on molecular similarity using an eigenvalue entropy approach

2019 ◽  
Author(s):  
Hiroyuki Kuwahara ◽  
Xin Gao
Keyword(s):  
Biological Activity ◽  
Virtual Screening ◽  
Molecular Similarity ◽  
Chemical Compounds ◽  
Structural Similarity ◽  
Optimal Selection ◽  
Two Dimensional ◽  
Chemical Fingerprints ◽  
Selection Of ◽  
Similarity Scores

AbstractTwo-dimensional (2D) chemical fingerprints are widely used as numerical features for the quantification of structural similarity of chemical compounds, which is an important step in similarity-based virtual screening (VS). Here, using an eigenvalue-based entropy approach, we sought to identify 2D fingerprints with little to no contribution to shaping the eigenvalue distribution of the feature matrix as related fingerprints and examined the degree to which these related 2D fingerprints influence molecular similarity scores via Tanimoto coefficient. We found that there are many related fingerprints in publicly available fingerprint schemes and that their presence in the feature set tends to decrease the similarity scores. Our results have implication in the optimal selection of 2D fingerprints and the identification of potential hits for compounds with target biological activity in VS.

On estimation of noise variance in two-dimensional signal processing

1991 ◽  
Vol 23 (3) ◽  
pp. 476-495 ◽  
Author(s):  
Peter Hall ◽  
J. W. Kay ◽  
D. M. Titterington
Keyword(s):  
Image Processing ◽  
Signal Processing ◽  
Digital Signal ◽  
Optimal Selection ◽  
Two Dimensional ◽  
Noise Variance ◽  
Asymptotically Optimal ◽  
Extensive Analysis ◽  
Optimal Configurations ◽  
Selection Of

Estimation of noise variance is an important component of digital signal processing, in particular of image processing. In this paper we develop methods for estimating the variance of white noise in a two-dimensional degraded signal. We discuss optimal configurations of pixels for difference-based estimation, and describe asymptotically optimal selection of weights for the component pixels. After extensive analysis of possible configurations we recommend averaging linear configurations over a variety of different orientations (usually two or four). This approach produces estimators with properties of both statistical and numerical efficiency.

On estimation of noise variance in two-dimensional signal processing

1991 ◽  
Vol 23 (03) ◽  
pp. 476-495 ◽  
Author(s):  
Peter Hall ◽  
J. W. Kay ◽  
D. M. Titterington
Keyword(s):  
Image Processing ◽  
Signal Processing ◽  
Digital Signal ◽  
Optimal Selection ◽  
Two Dimensional ◽  
Noise Variance ◽  
Asymptotically Optimal ◽  
Extensive Analysis ◽  
Optimal Configurations ◽  
Selection Of

Estimation of noise variance is an important component of digital signal processing, in particular of image processing. In this paper we develop methods for estimating the variance of white noise in a two-dimensional degraded signal. We discuss optimal configurations of pixels for difference-based estimation, and describe asymptotically optimal selection of weights for the component pixels. After extensive analysis of possible configurations we recommend averaging linear configurations over a variety of different orientations (usually two or four). This approach produces estimators with properties of both statistical and numerical efficiency.

Bridging the Gap between Quantitative and Qualitative Historical Research: an application of multiple regression analysis and homogeneity analysis with alternating least squares

1996 ◽  
Vol 8 (3) ◽  
pp. 133-144 ◽  
Author(s):  
María del Mar del Pozo Andrés ◽  
Jacques F A Braster
Keyword(s):  
Least Squares ◽  
Multiple Regression ◽  
Historical Research ◽  
Alternating Least Squares ◽  
Categorical Variables ◽  
Two Dimensional ◽  
Homogeneity Analysis ◽  
Regression Approach ◽  
Dimensional Picture ◽  
Selection Of

In this article we propose two research techniques that can bridge the gap between quantitative and qualitative historical research. These are: (1) a multiple regression approach that gives information about general patterns between numerical variables and the selection of outliers for qualitative analysis; (2) a homogeneity analysis with alternating least squares that results in a two-dimensional picture in which the relationships between categorical variables are graphically presented.

Pathway Complexity in the Stacking of Imine-linked Macrocycles Related to Two-Dimensional Covalent Organic Frameworks

2019 ◽  
Author(s):  
Shiwei Wang ◽  
Anton Chavez ◽  
Simil Thomas ◽  
Hong Li ◽  
Nathan C. Flanders ◽  
...  
Keyword(s):  
Temperature Dependence ◽  
Structural Similarity ◽  
Discrete Models ◽  
Side Chains ◽  
Two Dimensional ◽  
Assembly Process ◽  
Covalent Organic Frameworks ◽  
Electron Systems ◽  
Monomer Structure ◽  
Kinetic Traps

This work reports on the assembly of imine-linked macrocycles that serve as models of two-dimensional covalent organic frameworks (2D COFs). Interlayer interactions play an important role in the formation of 2D COFs, yet the effect of monomer structure on COF formation, crystallinity, and susceptibility to exfoliation are not well understood. For example, monomers with both electron-rich and electron-poor π-electron systems have been proposed to strengthen interlayer inter-actions and improve crystallinity. Here we probe these effects by studying the stacking behavior of imine-linked macrocycles that represent discrete models of 2D COFs. <div><br></div><div>Specifically, macrocycles based on terephthaldehyde (PDA) or 2,5-dimethoxyterephthaldehyde (DMPDA) stack upon cooling molecularly dissolved solutions. Both macrocycles assemble cooperatively with similar ΔHe values of -97 kJ/mol and -101 kJ/mol, respectively, although the DMPDA macrocycle assembly process showed a more straightforward temperature dependence. Circular dichroism spectroscopy performed on macrocycles bearing chiral side chains revealed a helix reversion process for the PDA macrocycles that was not observed for the DMPDA macrocycles. <br></div><div><br></div><div>Given the structural similarity of these monomers, these findings demonstrate that the stacking processes associated with nanotubes derived from these macrocycles, as well as for the corresponding COFs, are complex and susceptible to kinetic traps, casting doubt on the relevance of thermodynamic arguments for improving materials quality. <br></div>

Application of L6 Orthogonal Array for Optimal Selection of Some Process Parameters in GMAW Process

2012 ◽  
Vol 45 (4) ◽  
pp. 41 ◽  
Author(s):  
M. K. Saha ◽  
Santanu Das ◽  
A. Bandyopadhyay ◽  
S. Bandyopadhyay
Keyword(s):  
Process Parameters ◽  
Orthogonal Array ◽  
Optimal Selection ◽  
Selection Of

Application of L6 Orthogonal Array for Optimal Selection of Some Process Parameters in GMAW Process

2012 ◽  
Vol 45 (4) ◽  
pp. 41
Author(s):  
M. K. Saha ◽  
Santanu Das ◽  
A. Bandyopadhyay ◽  
S. Bandyopadhyay
Keyword(s):  
Process Parameters ◽  
Orthogonal Array ◽  
Optimal Selection ◽  
Selection Of

scholarly journals Methodology for Determining the Location of River Ports on a Modernized Waterway Based on Non-Cost Criteria: A Case Study of the Odra River Waterway

2021 ◽  
Vol 13 (6) ◽  
pp. 3571
Author(s):  
Bogusz Wiśnicki ◽  
Dorota Dybkowska-Stefek ◽  
Justyna Relisko-Rybak ◽  
Łukasz Kolanda
Keyword(s):  
Large Scale ◽  
Multicriteria Decision Making ◽  
Research Process ◽  
Optimal Selection ◽  
Investment Projects ◽  
Odra River ◽  
Research Problems ◽  
Selection Of ◽  
Construction Works

The paper responds to research problems related to the implementation of large-scale investment projects in waterways in Europe. As part of design and construction works, it is necessary to indicate river ports that play a major role within the European transport network as intermodal nodes. This entails a number of challenges, the cardinal one being the optimal selection of port locations, taking into account the new transport, economic, and geopolitical situation that will be brought about by modernized waterways. The aim of the paper was to present an original methodology for determining port locations for modernized waterways based on non-cost criteria, as an extended multicriteria decision-making method (MCDM) and employing GIS (Geographic Information System)-based tools for spatial analysis. The methodology was designed to be applicable to the varying conditions of a river’s hydroengineering structures (free-flowing river, canalized river, and canals) and adjustable to the requirements posed by intermodal supply chains. The method was applied to study the Odra River Waterway, which allowed the formulation of recommendations regarding the application of the method in the case of different river sections at every stage of the research process.

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