Support Vector Regression for Predicting Binding Affinity in Spinocerebellar Ataxia

2018 ◽  
pp. 173-184
Author(s):  
P. R. Asha ◽  
M. S. Vijaya
Keyword(s):  
Support Vector Regression ◽  
Binding Affinity ◽  
Spinocerebellar Ataxia ◽  
Support Vector

scholarly journals Affinity Prediction using Mutated Protein-Ligand Docking with Regression Techniques of SCA

2019 ◽  
Vol 8 (2) ◽  
pp. 3642-3648
Keyword(s):  
Drug Design ◽  
Support Vector Regression ◽  
Spinocerebellar Ataxia ◽  
Genetic Disorder ◽  
Ligand Docking ◽  
Support Vector ◽  
Autodock Vina ◽  
Affinity Prediction ◽  
Energy Profiles ◽  
Regression Techniques

Drug discovery for rare genetic disorder like spinocerebellar ataxia is very complicated in biomedical research. Numerous approaches are available for drug design in clinical labs, but it is time consuming. There is a need for affinity prediction of spinocerebellar ataxia, which will help in facilitating the drug design. In this work, the proteins are mutated with the information available from HGMD database. The repeat mutations are induced manually, and that mutated proteins are docked with ligand. The model is trained with extricated features such as energy profiles, rf-score, autodock vina scores, cyscore and sequence descriptors. Regression techniques like linear, polynomial, ridge, SVM and neural network regression are implemented. The predictive models are built with various regression techniques and the predictive model implemented with support vector regression is compared with support vector regression kernel. Among all regression techniques, SVR performs well than the other regression models.

Local and Regional Hour-Ahead Forecasts of Solar Irradiance with Training Data Selection and Support Vector Regression

2016 ◽  
Vol 136 (12) ◽  
pp. 898-907 ◽  
Author(s):  
Joao Gari da Silva Fonseca Junior ◽  
Hideaki Ohtake ◽  
Takashi Oozeki ◽  
Kazuhiko Ogimoto
Keyword(s):  
Support Vector Regression ◽  
Solar Irradiance ◽  
Training Data ◽  
Data Selection ◽  
Support Vector ◽  
Training Data Selection

Data Analytics to Help Improve Hydraulic Fracture Geometry Prediction Using Support Vector Regression: Case Study

2020 ◽  
Author(s):  
Avinash Wesley ◽  
Bharat Mantha ◽  
Ajay Rajeev ◽  
Aimee Taylor ◽  
Mohit Dholi ◽  
...  
Keyword(s):  
Support Vector Regression ◽  
Hydraulic Fracture ◽  
Data Analytics ◽  
Support Vector ◽  
Fracture Geometry
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