Does drug-target have a likeness?

Does drug-target have a likeness?

10.1160/ME0425

Saved in:

Bibliographic Details
Main Authors:	Xu, H., Fang, Y., Yao, L., Chen, Y., Chen, X.
Other Authors:	PHARMACY
Format:	Article
Published:	2014
Subjects:	Drug target Human genome Statistical learning Support vector machine
Online Access:	http://scholarbank.nus.edu.sg/handle/10635/105847
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	National University of Singapore

Similar Items

Learning the drug target-likeness of a protein
by: Xu, H., et al.
Published: (2014)

Computational study of therapeutic targets and ADME-Associated proteins and application in drug design
by: ZHENG CHANJUAN
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)

Computer prediction of allergen proteins from sequence-derived protein structural and physicochemical properties
by: Cui, J., et al.
Published: (2014)

Effects of training datasets on both the extreme learning machine and support vector machine for target audience identification on twitter
by: LO, Siaw Ling, et al.
Published: (2014)

Computer aided drug design: Drug target directed in silico approaches
by: CHEN XIN
Published: (2010)

Combinatorial support vector machines approach for virtual screening of selective multi-target serotonin reuptake inhibitors from large compound libraries
by: Shi, Z., et al.
Published: (2014)

Multi-target selection and high throughput quantitative structure-activity relationship model development
by: LIU XIN
Published: (2013)

Knowledge discovery in biomedical research and drug design : The development and application of biological databases
by: JI ZHILIANG
Published: (2010)

Statistical learning approaches for predicting pharmacological properties of pharmaceutical agents
by: LI HU
Published: (2010)

Generating an SVM Kernel function using genetic algorithm
by: IMMER, BALDOS
Published: (2012)

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

Model assessment through renormalization group in statistical learning
by: Wang, Q.-G., et al.
Published: (2014)

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

The Therapeutic Target Database: An Internet resource for the primary targets of approved, clinical trial and experimental drugs
by: Liu, X., et al.
Published: (2014)

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

Methods to Improve Virtual Screening of Potential Drug Leads for Specific Pharmacodynamic and Toxicological Properties
by: LIEW CHIN YEE
Published: (2012)

Text classification with kernels on the multinomial manifold
by: Zhang, D., et al.
Published: (2014)

Essay question generator based on Bloom’s taxonomy for assessing automated essay scoring system
by: Contreras, Jennifer O., et al.
Published: (2021)

Protein function and inhibitor prediction by statistical learning approach
by: HAN LIANYI
Published: (2010)

Privacy-preserving outsourced support vector machine design for secure drug discovery
by: LIU, Ximeng, et al.
Published: (2020)

The relaxed online maximum margin algorithm
by: Li, Y., et al.
Published: (2013)

Supervised and unsupervised machine learning for side-channel based Trojan detection
by: Jap, Dirmanto, et al.
Published: (2017)

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

High performance computational virtual screening tools: development and application to the discovery of kinase inhibitors
by: MA XIAOHUA
Published: (2011)

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

DISCOVERY OF INDOLYL PIPERAZINYLPYRIMIDINES WITH DUAL-TARGET PROFILES ADENOSINE A2¿ AND DOPAMINE D2 RECEPTORS FOR PD TREATMENT
by: SHAO YI-MING
Published: (2015)

Application of support vector machines to in silico prediction of cytochrome P450 enzyme substrates and inhibitors
by: Yap, C.W., et al.
Published: (2014)

Identifying novel type ZBGs and nonhydroxamate HDAC inhibitors through a SVM based virtual screening approach
by: Liu, X.H., et al.
Published: (2014)

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

Kernel methods for the incorporation of prior-knowledge into support vector machines
by: VEILLARD ANTOINE PAUL MITSUMASA
Published: (2013)

Emotional sentence identification in a story
by: Zhang, Z., et al.
Published: (2014)

AUTOMATIC LOCALIZATION OF EPIDURAL NEEDLE ENTRY SITE WITH LUMBAR ULTRASOUND IMAGE PROCESSING
by: YU SHUANG
Published: (2015)

Optimizing the cost function of histogram of oriented gradient-based INRIA dataset
by: Uy, Roger Luis, et al.
Published: (2014)

Discriminant analysis in pairwise kernel learning for SVM classification
by: Jiang, H., et al.
Published: (2014)

In silico prediction and screening of γ-secretase inhibitors by molecular descriptors and machine learning methods
by: Yang, X.-G., et al.
Published: (2014)

Prediction of relatedness in stack overflow: Deep learning vs. SVM: A reproducibility study
by: XU, Bowen, et al.
Published: (2018)

A novel genomics approach for the identification of drug targets in pathogens, with special reference to Pseudomonas aeruginosa
by: Sakharkar, K.R., et al.
Published: (2012)

Prediction of torsade-causing potential of drugs by support vector machine approach
by: Yap, C.W., et al.
Published: (2014)

Prediction of estrogen receptor agonists and characterization of associated molecular descriptors by statistical learning methods
by: Li, H., et al.
Published: (2014)