Development and implementation of (Q)SAR modeling within the CHARMMing web-user interface.
J Comput Chem
; 36(1): 62-7, 2015 Jan 05.
Article
em En
| MEDLINE
| ID: mdl-25362883
ABSTRACT
Recent availability of large publicly accessible databases of chemical compounds and their biological activities (PubChem, ChEMBL) has inspired us to develop a web-based tool for structure activity relationship and quantitative structure activity relationship modeling to add to the services provided by CHARMMing (www.charmming.org). This new module implements some of the most recent advances in modern machine learning algorithms-Random Forest, Support Vector Machine, Stochastic Gradient Descent, Gradient Tree Boosting, so forth. A user can import training data from Pubchem Bioassay data collections directly from our interface or upload his or her own SD files which contain structures and activity information to create new models (either categorical or numerical). A user can then track the model generation process and run models on new data to predict activity.
Palavras-chave
Texto completo:
1
Bases de dados:
MEDLINE
Assunto principal:
Interface Usuário-Computador
/
Internet
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Relação Quantitativa Estrutura-Atividade
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
J Comput Chem
Assunto da revista:
QUIMICA
Ano de publicação:
2015
Tipo de documento:
Article