Developing and validating predictive decision tree models from mining chemical structural fingerprints and high-throughput screening data in PubChem.
about
Hmrbase: a database of hormones and their receptorsProfiling animal toxicants by automatically mining public bioassay data: a big data approach for computational toxicologyCombination therapeutics in complex diseasesA machine learning-based method to improve docking scoring functions and its application to drug repurposingVirtual screening models for prediction of HIV-1 RT associated RNase H inhibitionMining Chemical Activity Status from High-Throughput Screening AssaysInvestigating the correlations among the chemical structures, bioactivity profiles and molecular targets of small moleculesAutomatic design of decision-tree induction algorithms tailored to flexible-receptor docking data.Infection status outcome, machine learning method and virus type interact to affect the optimised prediction of hepatitis virus immunoassay results from routine pathology laboratory assays in unbalanced dataA novel method for mining highly imbalanced high-throughput screening data in PubChem.Exploiting PubChem for Virtual Screening.Superaugmented eccentric distance sum connectivity indices: novel highly discriminating topological descriptors for QSAR/QSPR.Decision tree models for data mining in hit discovery.Efficient discovery of responses of proteins to compounds using active learningLinear and Nonlinear Support Vector Machine for the Classification of Human 5-HT1A Ligand Functionality.System response of metabolic networks in Chlamydomonas reinhardtii to total available ammonium.Antiviral Stratagems Against HIV-1 Using RNA Interference (RNAi) Technology.Accurate and interpretable nanoSAR models from genetic programming-based decision tree construction approaches.Inferring Chemogenomic Features from Drug-Target Interaction Networks.Literature Review of (Q)SAR Modelling of Nanomaterial Toxicity.Prediction of lysine ubiquitination with mRMR feature selection and analysis.Diverse models for anti-HIV activity of purine nucleoside analogs.Models for antitubercular activity of 5â-O-[(N-Acyl)sulfamoyl]adenosines.Identification of chemogenomic features from drug-target interaction networks using interpretable classifiers.Models for the prediction of receptor tyrosine kinase inhibitory activity of substituted 3-aminoindazole analogues.Fast rule-based bioactivity prediction using associative classification mining.Interpreting linear support vector machine models with heat map molecule coloring.Diverse models for the prediction of HIV integrase inhibitory activity of substituted quinolone carboxylic acids.Virtual screening by a new Clustering-based Weighted Similarity Extreme Learning Machine approach.Prediction of Compound Profiling Matrices Using Machine Learning.
P2860
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P2860
Developing and validating predictive decision tree models from mining chemical structural fingerprints and high-throughput screening data in PubChem.
description
2008 nî lūn-bûn
@nan
2008 թուականի Սեպտեմբերին հրատարակուած գիտական յօդուած
@hyw
2008 թվականի սեպտեմբերին հրատարակված գիտական հոդված
@hy
2008年の論文
@ja
2008年論文
@yue
2008年論文
@zh-hant
2008年論文
@zh-hk
2008年論文
@zh-mo
2008年論文
@zh-tw
2008年论文
@wuu
name
Developing and validating pred ...... put screening data in PubChem.
@ast
Developing and validating pred ...... put screening data in PubChem.
@en
type
label
Developing and validating pred ...... put screening data in PubChem.
@ast
Developing and validating pred ...... put screening data in PubChem.
@en
prefLabel
Developing and validating pred ...... put screening data in PubChem.
@ast
Developing and validating pred ...... put screening data in PubChem.
@en
P2093
P2860
P356
P1433
P1476
Developing and validating pred ...... put screening data in PubChem.
@en
P2093
Lianyi Han
Stephen H Bryant
Yanli Wang
P2860
P2888
P356
10.1186/1471-2105-9-401
P577
2008-09-25T00:00:00Z
P5875
P6179
1024436208