Volcano plots, hydrodesulfurization and surface 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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Field-Ion Microscopy of BCC Metals: A Study of Image Differences and Topographical Variations

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100071016 ◽

1973 ◽

Vol 31 ◽

pp. 114-115

Author(s):

O. T. Inal ◽

L. E. Murr

Keyword(s):

Liquid Nitrogen ◽

Liquid Nitrogen Temperature ◽

Surface Atom ◽

Image Brightness ◽

Field Ion Microscopy ◽

Topographic Features ◽

Bcc Metals ◽

Electron Orbital ◽

Ion Microscopy ◽

Field Ion Microscope

When sharp metal filaments of W, Fe, Nb or Ta are observed in the field-ion microscope (FIM), their appearance is differentiated primarily by variations in regional brightness. This regional brightness, particularly prominent at liquid nitrogen temperature has been attributed in the main to chemical specificity which manifests itself in a paricular array of surface-atom electron-orbital configurations.Recently, anomalous image brightness and streaks in both fcc and bee materials observed in the FIM have been shown to be the result of surface asperities and related topographic features which arise by the unsystematic etching of the emission-tip end forms.

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