Decision Forest specifications

Information


Unique identifier OMICS_18852
Name Decision Forest
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages Java
Computer skills Advanced
Stability Stable
Maintained Yes

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Documentation


Maintainer


  • person_outline Weida Tong

Publications for Decision Forest

Decision Forest citations

 (2)
library_books

Competitive docking model for prediction of the human nicotinic acetylcholine receptor α7 binding of tobacco constituents

2018
Oncotarget
PMCID: 5908294
PMID: 29682193
DOI: 10.18632/oncotarget.24458

[…] itize laboratory experiments needed to study tobacco constituents. Among available computational methods such as pharmacophore modeling [–], comparative molecular field analysis [], decision tree [], decision forest [–], support vector machine [, ], and other machine learning methods [–], molecular docking is one of the most established and widely-used approaches to assess the binding activity of […]

library_books

Consensus Modeling for Prediction of Estrogenic Activity of Ingredients Commonly Used in Sunscreen Products

2016
PMCID: 5086697
PMID: 27690075
DOI: 10.3390/ijerph13100958

[…] experimental data, we then used a consensus modeling method to predict their qualitatively and quantitatively binding activity towards the estrogen receptor (ER). The consensus modeling comprised two Decision Forest (DF) models that were built using two different training data sets. The two DF models were validated using five-fold cross validations and external chemicals. In addition to utilizing […]

Decision Forest institution(s)
Division of Bioinformatics, Z-Tech at National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, USA; Division of Systems Toxicology, Center for Toxicoinformatics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, USA

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