A study of coronene?coronene association using atom?atom pair potentials

In this work, via the use of the ‘comparison’ concept, Random Forest (RF) models were successfully generated using unbalanced data sets that assign different importance factors to atom pair potentials to enhance their ability to identify native proteins from decoy proteins. Individual and combined data sets consisting of twelve decoy sets were used to test the performance of the RF models. We find that RF models increase the recognition of native structures without affecting their ability to identify the best decoy structures. We also created models using scrambled atom types, which create physically unrealistic probability functions, in order to test the ability of the RF algorithm to create useful models based on inputted scrambled probability functions. From this test we find that we are unable to create models that are of similar quality relative to the unscrambled probability functions. Next we created uniform probability functions where the peak positions as the same as the original, but each interaction has the same peak height. Using these uniform potentials we were able to recover models as good as the ones using the full potentials suggesting all that is important in these models are the experimental peak positions.

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Calculation of intermolecular interaction in aromatic molecular clusters from direction dependent atom‐pair potentials

The Journal of Chemical Physics ◽

10.1063/1.468863 ◽

1995 ◽

Vol 102 (23) ◽

pp. 9149-9159 ◽

Cited By ~ 13

Author(s):

Gershon Rosenblum ◽

Shammai Speiser

Keyword(s):

Intermolecular Interaction ◽

Molecular Clusters ◽

Atom Pair ◽

Pair Potentials

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Random Forest Refinement of the KECSA2 Knowledge-based Scoring Function for Protein Decoy Detection

10.26434/chemrxiv.7231058 ◽

2018 ◽

Author(s):

Jun Pei ◽

Zheng Zheng ◽

Kenneth M. Merz Jr.

Keyword(s):

Random Forest ◽

Scoring Function ◽

Peak Height ◽

Data Sets ◽

Atom Pair ◽

Probability Functions ◽

Knowledge Based ◽

Pair Potentials ◽

Native Proteins ◽

Combined Data

In this work, via the use of the ‘comparison’ concept, Random Forest (RF) models were successfully generated using unbalanced data sets that assign different importance factors to atom pair potentials to enhance their ability to identify native proteins from decoy proteins. Individual and combined data sets consisting of twelve decoy sets were used to test the performance of the RF models. We find that RF models increase the recognition of native structures without affecting their ability to identify the best decoy structures. We also created models using scrambled atom types, which create physically unrealistic probability functions, in order to test the ability of the RF algorithm to create useful models based on inputted scrambled probability functions. From this test we find that we are unable to create models that are of similar quality relative to the unscrambled probability functions. Next we created uniform probability functions where the peak positions as the same as the original, but each interaction has the same peak height. Using these uniform potentials we were able to recover models as good as the ones using the full potentials suggesting all that is important in these models are the experimental peak positions.

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Theoretical description of the fluoranthene-fluoranthene association using atom-atom pair potentials

10.1109/stsm.1994.835223 ◽

1994 ◽

Author(s):

M. Rubio ◽

J. Sanchez-Marin ◽

E. Orti

Keyword(s):

Theoretical Description ◽

Atom Pair ◽

Pair Potentials

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Theoretical description of the fluoranthene-fluoranthene association using atom-atom pair potentials

Synthetic Metals ◽

10.1016/0379-6779(94)03176-7 ◽

1995 ◽

Vol 71 (1-3) ◽

pp. 2081-2082 ◽

Cited By ~ 1

Author(s):

M. Rubio ◽

J. Sánchez-Marín ◽

E. Ortí

Keyword(s):

Theoretical Description ◽

Atom Pair ◽

Pair Potentials

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Friedel'S law breakdown and interpretation of stacking fault images in tetrahedral semiconductors

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100126408 ◽

1987 ◽

Vol 45 ◽

pp. 318-319

Author(s):

Rob. W. Glaisher ◽

A.E.C. Spargo

Keyword(s):

Relative Phase ◽

Point Group ◽

Binary Compound ◽

Stacking Fault ◽

Fold Axis ◽

Atom Pair ◽

Tetrahedral Semiconductors ◽

Group Symmetries ◽

Thin Crystal ◽

Phase Differences

Images of <11> oriented crystals with diamond structure (i.e. C,Si,Ge) are dominated by white spot contrast which, depending on thickness and defocus, can correspond to either atom-pair columns or tunnel sites. Olsen and Spence have demonstrated a method for identifying the correspondence which involves the assumed structure of a stacking fault and the preservation of point-group symmetries by correctly aligned and stigmated images. For an intrinsic stacking fault, a two-fold axis lies on a row of atoms (not tunnels) and the contrast (black/white) of the atoms is that of the {111} fringe containing the two-fold axis. The breakdown of Friedel's law renders this technique unsuitable for the related, but non-centrosymmetric binary compound sphalerite materials (e.g. GaAs, InP, CdTe). Under dynamical scattering conditions, Bijvoet related reflections (e.g. (111)/(111)) rapidly acquire relative phase differences deviating markedly from thin-crystal (kinematic) values, which alter the apparent location of the symmetry elements needed to identify the defect.

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