scholarly article | Q13442814 |
P356 | DOI | 10.1002/MINF.201100146 |
P698 | PubMed publication ID | 27477100 |
P2093 | author name string | Matthew W B Trotter | |
Sean B Holden | |||
Nicholas C V Pilkington | |||
P2860 | cites work | Drug induced QT prolongation and torsades de pointes | Q24673854 |
Knowledge-based analysis of microarray gene expression data by using support vector machines | Q27939386 | ||
Kernel Functions for Attributed Molecular Graphs – A New Similarity-Based Approach to ADME Prediction in Classification and Regression | Q29305726 | ||
Comparison of the predicted and observed secondary structure of T4 phage lysozyme | Q29398301 | ||
Assessing the accuracy of prediction algorithms for classification: an overview | Q29615358 | ||
Evaluation of human intestinal absorption data and subsequent derivation of a quantitative structure-activity relationship (QSAR) with the Abraham descriptors. | Q30652076 | ||
Drug design by machine learning: support vector machines for pharmaceutical data analysis | Q30668015 | ||
A statistical framework for genomic data fusion | Q30929198 | ||
Classification of multidrug-resistance reversal agents using structure-based descriptors and linear discriminant analysis | Q30966916 | ||
Learning interpretable SVMs for biological sequence classification | Q33244587 | ||
Improved sub‐cellular resolution via simultaneous analysis of organelle proteomics data across varied experimental conditions | Q33740768 | ||
hERG-related drug toxicity and models for predicting hERG liability and QT prolongation | Q33845924 | ||
Nonleadlikeness and leadlikeness in biochemical screening | Q34174693 | ||
ADMET in silico modelling: towards prediction paradise? | Q35075770 | ||
Graph Kernels for Molecular Similarity | Q38910020 | ||
Drug discovery using support vector machines. The case studies of drug-likeness, agrochemical-likeness, and enzyme inhibition predictions | Q40547918 | ||
Structure-activity relationships for xenobiotic transport substrates and inhibitory ligands of P-glycoprotein | Q42015740 | ||
A simple approach discriminating cardio-safe drugs from toxic ones | Q42194344 | ||
From machine learning to natural product derivatives that selectively activate transcription factor PPARgamma | Q43204326 | ||
A computational ensemble pharmacophore model for identifying substrates of P-glycoprotein | Q43963966 | ||
Active learning with support vector machines in the drug discovery process. | Q45967032 | ||
Using Kernel Alignment to Select Features of Molecular Descriptors in a QSAR Study | Q46559332 | ||
Substructure-based support vector machine classifiers for prediction of adverse effects in diverse classes of drugs | Q47312966 | ||
Effect of molecular descriptor feature selection in support vector machine classification of pharmacokinetic and toxicological properties of chemical agents. | Q47406031 | ||
An overview of statistical learning theory | Q50660273 | ||
Ensemble of linear models for predicting drug properties | Q51955499 | ||
3D analysis of facial morphology. | Q51999018 | ||
On the mechanism of human intestinal absorption | Q52036402 | ||
A general pattern for substrate recognition by P‐glycoprotein | Q54145580 | ||
Gene Selection for Cancer Classification using Support Vector Machines | Q56535529 | ||
A Tutorial on Support Vector Machines for Pattern Recognition | Q56885196 | ||
Toward a pharmacophore for drugs inducing the long QT syndrome: insights from a CoMFA study of HERG K(+) channel blockers | Q57005299 | ||
Asymptotic Behaviors of Support Vector Machines with Gaussian Kernel | Q60241079 | ||
Classification structure-activity relations (C-SAR) in prediction of human intestinal absorption | Q73000510 | ||
Prediction of drug absorption using multivariate statistics | Q73126791 | ||
Structure-activity relationships of P-glycoprotein interacting drugs: kinetic characterization of their effects on ATPase activity | Q73705879 | ||
Reversal of P-glycoprotein mediated multidrug resistance by novel anthranilamide derivatives | Q74658137 | ||
ADME evaluation. 2. A computer model for the prediction of intestinal absorption in humans | Q78578799 | ||
P433 | issue | 3-4 | |
P921 | main subject | drug discovery | Q1418791 |
multiple kernel learning | Q25048660 | ||
P304 | page(s) | 313-322 | |
P577 | publication date | 2012-04-04 | |
P1433 | published in | Molecular Informatics | Q3319476 |
P1476 | title | Multiple Kernel Learning for Drug Discovery | |
P478 | volume | 31 |
Q57382555 | Machine Learning for First-Order Theorem Proving | cites work | P2860 |
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