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.

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.

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.

scholarly journals Increase of efficiency of QSAR — the analysis of carcinogenic activity of halogeneted hydrocarbons

2005 ◽  
Vol 3 (2) ◽  
pp. 5-14
Author(s):  
Aleksey V Tarasov ◽  
Serikbay K Abilev ◽  
Ramis M Velibekov ◽  
Valentin A Tarasov
Keyword(s):  
Biological Activity ◽  
Computer Program ◽  
Chemical Compounds ◽  
Carcinogenic Activity ◽  
Structural Descriptors ◽  
Selection Of

The new principle of analysis of structureactivity of carcinogenic compounds is offered. It is basis on use a compound structural descriptors representing a combination untied among themselves of structural fragments of a molecule. The computer program is developed, allowing to generate every possible structural fragments of molecules of chemical compounds and their  combinations and to carry out selection of the compound descriptors statistically significantly influencing their biological activity. In work it is used the samples consisting of 89 halogeneted hydrocarbons for which their carcinogenic activity on rodents is investigated.

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.

Virus-Like Particles in a Human Breast Cancer: Structural Similarity to Previously Reported Particles

1973 ◽  
Vol 31 ◽  
pp. 378-379
Author(s):  
G. Kasnic ◽  
S. E. Stewart ◽  
C. Urbanski
Keyword(s):  
Breast Cancer ◽  
Biological Activity ◽  
Human Breast Cancer ◽  
Osteogenic Sarcoma ◽  
Human Tumor ◽  
Structural Similarity ◽  
Cell Tumor ◽  
Human Breast ◽  
Human Tumor Cell ◽  
Type Particle

We have reported the maturation of an intracisternal A-type particle in murine plasma cell tumor cultures and three human tumor cell cultures (rhabdomyosarcoma, lung adenocarcinoma, and osteogenic sarcoma) after IUDR-DMSO activation. In all of these studies the A-type particle seems to develop into a form with an electron dense nucleoid, presumably mature, which is also intracisternal. A similar intracisternal A-type particle has been described in leukemic guinea pigs. Although no biological activity has yet been demonstrated for these particles, on morphologic grounds, and by the manner in which they develop within the cell, they may represent members of the same family of viruses.

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
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