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Neural Network scoring specifications

Information


Unique identifier OMICS_16878
Name Neural Network scoring
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages Python
License GNU General Public License version 3.0
Computer skills Advanced
Version 2.01
Stability Stable
Requirements
AutoDock, Vina, MGLTools
Maintained Yes

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  • person_outline Jacob Durrant

Publications for Neural Network scoring

Neural Network scoring citations

 (4)
library_books

Comparing Neural Network Scoring Functions and the State of the Art: Applications to Common Library Screening

2013
J Chem Inf Model
PMCID: 3735370
PMID: 23734946
DOI: 10.1021/ci400042y

[…] molecular size (molecular weight, total solvent accessible surface area, volume, number of ring atoms, and number of heteroatoms) and polarizability (Table ). It is interesting that both Vina and the neural-network scoring functions demonstrated similar trends, even though they evaluate ligand binding using very different methodologies. Others have identified similar biases in the FlexX and Gold d […]

library_books

FunFOLDQA: A Quality Assessment Tool for Protein Ligand Binding Site Residue Predictions

2012
PLoS One
PMCID: 3364224
PMID: 22666491
DOI: 10.1371/journal.pone.0038219

[…] ultiple Linear Regression methods, when the correlations of the predictive output scores to the observed scores (either MCC or BDT) were calculated. ROC analysis was also undertaken, showing that the Neural Network scoring method achieved the largest AUC score and therefore the highest confidence for the CASP8 dataset. We therefore decided to utilize the Neural Network to combine the FunFOLDQA fea […]

library_books

An artificial intelligence tool to predict fluid requirement in the intensive care unit: a proof of concept study

2008
PMCID: 2646316
PMID: 19046450
DOI: 10.1186/cc7140

[…] eagues [] and Cevenini and colleagues [] compared different models in predicting ICU morbidity after cardiac surgery and found the Bayesian and logistic regression models to be superior to artificial neural network, scoring systems and k-nearest neighbour in terms of discrimination, generalisation and calibration for this particular task. Bayesian network has also been used to predict prognosis of […]

library_books

Computational approaches for modeling human intestinal absorption and permeability

2006
J Mol Model
PMCID: 2441499
PMID: 16583199
DOI: 10.1007/s00894-005-0065-z

[…] [] was comparable to that derived using PSA [] for the same set of compounds (Table ). Very recently, a quantitative model for predicting the %HIA was proposed by combining a genetic algorithm and a neural network scoring function []. The significance of the model can be appreciated from the small (9.4%) root-mean-square error (rmse) obtained for a training set of 67 compounds. However, the major […]


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Neural Network scoring institution(s)
Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, CA, USA; Department of Pharmacology, University of California San Diego, La Jolla, CA, USA; Department of Chemistry and Biochemistry, NSF Center for Theoretical Biological Physics, National Biomedical Computation Resource, University of California San Diego, La Jolla, CA, USA; Howard Hughes Medical Institute, University of California San Diego, La Jolla, CA, USA
Neural Network scoring funding source(s)
Supported by the NIH GM31749, NSF MCB-1020765, and MCA93S013, the Howard Hughes Medical Institute, the National Center for Supercomputing Applications, the San Diego Supercomputer Center, the W.M. Keck Foundation, the National Biomedical Computational Resource, and the Center for Theoretical Biological Physics.

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