Prediction of P-glycoprotein substrates by a support vector machine approach.

scientific article

Prediction of P-glycoprotein substrates by a support vector machine approach. is …
instance of (P31):
scholarly articleQ13442814

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P8978DBLP publication IDjournals/jcisd/XueYSCWC04
P356DOI10.1021/CI049971E
P698PubMed publication ID15272858
P5875ResearchGate publication ID8436573

P50authorChun Wei YapQ57056600
Ying XueQ42837170
P2093author name stringChen YZ
Cao ZW
Wang JF
Sun LZ
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The drug transporter P-glycoprotein limits oral absorption and brain entry of HIV-1 protease inhibitorsQ34065800
Screening with tumor markers: critical issuesQ34551044
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Structure-activity relationships for xenobiotic transport substrates and inhibitory ligands of P-glycoproteinQ42015740
A computational ensemble pharmacophore model for identifying substrates of P-glycoproteinQ43963966
Prediction of torsade-causing potential of drugs by support vector machine approach.Q44771784
Multi-class protein fold recognition using support vector machines and neural networksQ48681384
Molecular Diversity and Representativity in Chemical DatabasesQ50695147
Traditional topological indices vs electronic, geometrical, and combined molecular descriptors in QSAR/QSPR researchQ51652447
Novel computer program for fast exact calculation of accessible and molecular surface areas and average surface curvatureQ52013462
Support Vector Machines for predicting HIV protease cleavage sites in proteinQ52043614
Theoretical calculation and prediction of P-glycoprotein-interacting drugs using MolSurf parametrization and PLS statisticsQ54049500
P4510describes a project that usessupport vector machineQ282453
P433issue4
P921main subjectsupport vector machineQ282453
P304page(s)1497-1505
P577publication date2004-07-01
P1433published inJournal of Chemical Information and Computer SciencesQ104614957
P1476titlePrediction of P-glycoprotein substrates by a support vector machine approach
P478volume44

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