Bayesian models leveraging bioactivity and cytotoxicity information for drug discovery.
about
Learning from the past for TB drug discovery in the futureNew target prediction and visualization tools incorporating open source molecular fingerprints for TB Mobile 2.0Enhancing hit identification in Mycobacterium tuberculosis drug discovery using validated dual-event Bayesian modelsLooking back to the future: predicting in vivo efficacy of small molecules versus Mycobacterium tuberculosisFinding new collaboration models for enabling neglected tropical disease drug discoveryMachine Learning Models and Pathway Genome Data Base for Trypanosoma cruzi Drug DiscoveryCombining Metabolite-Based Pharmacophores with Bayesian Machine Learning Models for Mycobacterium tuberculosis Drug DiscoveryBigger data, collaborative tools and the future of predictive drug discoveryComputational prediction and validation of an expert's evaluation of chemical probesFusing dual-event data sets for Mycobacterium tuberculosis machine learning models and their evaluation.Are bigger data sets better for machine learning? Fusing single-point and dual-event dose response data for Mycobacterium tuberculosisBayesian models trained with HTS data for predicting β-haematin inhibition and in vitro antimalarial activity.Predicting Mouse Liver Microsomal Stability with "Pruned" Machine Learning Models and Public Data.Machine Learning Model Analysis and Data Visualization with Small Molecules Tested in a Mouse Model of Mycobacterium tuberculosis Infection (2014-2015).Molecular processes that drive cigarette smoke-induced epithelial cell fate of the lung.Small molecules with antiviral activity against the Ebola virusCombining computational methods for hit to lead optimization in Mycobacterium tuberculosis drug discovery.Bayesian models for screening and TB Mobile for target inference with Mycobacterium tuberculosis.Machine learning models identify molecules active against the Ebola virus in vitroEvolution of a thienopyrimidine antitubercular relying on medicinal chemistry and metabolomics insights.Open Source Bayesian Models. 3. Composite Models for Prediction of Binned ResponsesPredictive modeling targets thymidylate synthase ThyX in Mycobacterium tuberculosisAn FtsZ-targeting prodrug with oral antistaphylococcal efficacy in vivoThe Next Era: Deep Learning in Pharmaceutical Research.Collaborative drug discovery for More Medicines for Tuberculosis (MM4TB).Antimycobacterial Metabolism: Illuminating Mycobacterium tuberculosis Biology and Drug Discovery.Computational models for neglected diseases: gaps and opportunities.Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Data Sets.Addressing the Metabolic Stability of Antituberculars through Machine Learning.Novel Pyrimidines as Antitubercular Agents.Comparing and Validating Machine Learning Models for Mycobacterium tuberculosis Drug Discovery.
P2860
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P2860
Bayesian models leveraging bioactivity and cytotoxicity information for drug discovery.
description
2013 nî lūn-bûn
@nan
2013 թուականի Մարտին հրատարակուած գիտական յօդուած
@hyw
2013 թվականի մարտին հրատարակված գիտական հոդված
@hy
2013年の論文
@ja
2013年論文
@yue
2013年論文
@zh-hant
2013年論文
@zh-hk
2013年論文
@zh-mo
2013年論文
@zh-tw
2013年论文
@wuu
name
Bayesian models leveraging bioactivity and cytotoxicity information for drug discovery.
@ast
Bayesian models leveraging bioactivity and cytotoxicity information for drug discovery.
@en
Bayesian models leveraging bioactivity and cytotoxicity information for drug discovery.
@nl
type
label
Bayesian models leveraging bioactivity and cytotoxicity information for drug discovery.
@ast
Bayesian models leveraging bioactivity and cytotoxicity information for drug discovery.
@en
Bayesian models leveraging bioactivity and cytotoxicity information for drug discovery.
@nl
prefLabel
Bayesian models leveraging bioactivity and cytotoxicity information for drug discovery.
@ast
Bayesian models leveraging bioactivity and cytotoxicity information for drug discovery.
@en
Bayesian models leveraging bioactivity and cytotoxicity information for drug discovery.
@nl
P2093
P2860
P1476
Bayesian models leveraging bioactivity and cytotoxicity information for drug discovery.
@en
P2093
Anne J Lenaerts
Barry A Bunin
Joel S Freundlich
Lisa K Woolhiser
Marilyn Ekonomidis
Meliza Talaue
Mi-Sun Koo
Nancy Connell
Robert C Reynolds
P2860
P304
P356
10.1016/J.CHEMBIOL.2013.01.011
P577
2013-03-01T00:00:00Z