Prediction of torsade-causing potential of drugs by support vector machine approach

Prediction of torsade-causing potential of drugs by support vector machine approach

10.1093/toxsci/kfh082

Saved in:

Bibliographic Details
Main Authors:	Yap, C.W., Cai, C.Z., Xue, Y., Chen, Y.Z.
Other Authors:	COMPUTATIONAL SCIENCE
Format:	Article
Published:	2014
Subjects:	Linear solvation energy relationship Prediction Support vector machine Torsade de pointes
Online Access:	http://scholarbank.nus.edu.sg/handle/10635/53101
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	National University of Singapore

Similar Items

Determination of Torsade-causing potential of drug candidates using one-class classification and ensemble modelling approaches
by: He, Y., et al.
Published: (2014)

Cisapride and torsades de pointes in a pacemaker patient
by: Ng, K.-S., et al.
Published: (2016)

Prediction of transporter family from protein sequence by support vector machine approach
by: Lin, H.H., et al.
Published: (2014)

Enzyme Family Classification by Support Vector Machines
by: Cai, C.Z., et al.
Published: (2014)

Effect of training datasets on support vector machine prediction of protein-protein interactions
by: Lo, S.L., et al.
Published: (2014)

A fast iterative nearest point algorithm for support vector machine classifier design
by: Keerthi, S.S., et al.
Published: (2014)

QSAR and predictors of eye and skin effects
by: Liew, C.Y., et al.
Published: (2014)

Hidden Logistic Linear Regression for Support Vector Machine based phone verification
by: Li, B., et al.
Published: (2013)

Application of support vector machine to prediction of cross-reactive allergens and recognition of viral sequences
by: MUH HON CHENG
Published: (2010)

Prediction of antifungal activity with support vector machine
by: Li, Z.-R., et al.
Published: (2014)

Applying support vector machines to predict building energy consumption in tropical region
by: Dong, B., et al.
Published: (2014)

Splice Site Prediction Using Support Vector Machines with a Bayes Kernel
by: ZHANG, Ya, et al.
Published: (2006)

Enlarging the terminal region of nonlinear model predictive control using the support vector machine method
by: Ong, C.J., et al.
Published: (2014)

Homology-free prediction of functional class of proteins and peptides by support vector machines
by: Zhu, F., et al.
Published: (2014)

Learning with support vector machines for query-by-multiple-examples
by: Dell, Z., et al.
Published: (2013)

Link Prediction in a Weighted Network Using Support Vector Machine
by: Co, Jan Miles, et al.
Published: (2016)

Protein function classification via support vector machine approach
by: Cai, C.Z., et al.
Published: (2014)

Convergence of the extended Lagrangian support vector machine
by: Yang, X.W., et al.
Published: (2014)

Support vector machine classification of physical and biological datasets
by: Cai, C.-Z., et al.
Published: (2014)

Protein function prediction via protein-protein interaction - a Support Vector Machine approach
by: LO SIAW LING
Published: (2010)

An extended Lagrangian support vector machine for classifications
by: Yang, X., et al.
Published: (2014)

Time-Series Link Prediction Using Support Vector Machines
by: Fernandez, Proceso L, Jr, et al.
Published: (2017)

Prediction of RNA-binding proteins from primary sequence by a support vector machine approach
by: Han, L.Y., et al.
Published: (2014)

Saliency analysis of support vector machines for gene selection in tissue classification
by: Cao, L., et al.
Published: (2016)

Predicting taxi-out time at congested airports with optimization-based support vector regression methods
by: Lian, Guan, et al.
Published: (2018)

Stability regions for constrained nonlinear systems and their functional characterization via support-vector-machine learning
by: Ong, C.J., et al.
Published: (2014)

Simple tiered classifiers
by: Hall, P., et al.
Published: (2014)

Advances in exploration of machine learning methods for predicting functional class and interaction profiles of proteins and peptides irrespective of sequence homology
by: Cui, J., et al.
Published: (2014)

Virtual screening methods as tools for drug lead discovery from large chemical libraries
by: Ma, X.H., et al.
Published: (2014)

Geometric error compensation for multi-axial precision motion systems using support vectors
by: Teo, C.-S., et al.
Published: (2014)

Flood stage forecasting with support vector machines
by: Liong, S.-Y., et al.
Published: (2014)

Support vector machine in chaotic hydrological time series forecasting
by: YU XINYING
Published: (2010)

Extraction of brain tumor from MR images using one-class support vector machine
by: Zhou, J., et al.
Published: (2014)

Extraction of brain tumor from MR images using one-class support vector machine
by: Zhou, J., et al.
Published: (2016)

Machine learning-based prediction of survival prognosis in cervical cancer
by: Ding, Dongyan, et al.
Published: (2022)

A new method on gene selection for tissue classification
by: Hao, Y., et al.
Published: (2014)

Incorporating prior-knowledge in support vector machines by kernel adaptation
by: Veillard, A., et al.
Published: (2013)

Question Classification using Support Vector Machines
by: Zhang, D., et al.
Published: (2013)

Prediction of functional class of the SARS coronavirus proteins by a statistical learning method
by: Cai, C.Z., et al.
Published: (2014)

Effect of training data size and noise level on support vector machines virtual screening of genotoxic compounds from large compound libraries
by: Kumar, P., et al.
Published: (2014)