Open Source Bayesian Models. 3. Composite Models for Prediction of Binned Responses
about
Machine Learning Model Analysis and Data Visualization with Small Molecules Tested in a Mouse Model of Mycobacterium tuberculosis Infection (2014-2015).The Next Era: Deep Learning in Pharmaceutical Research.Collaborative drug discovery for More Medicines for Tuberculosis (MM4TB).Comparing and Validating Machine Learning Models for Mycobacterium tuberculosis Drug Discovery.
P2860
Open Source Bayesian Models. 3. Composite Models for Prediction of Binned Responses
description
2016 nî lūn-bûn
@nan
2016年の論文
@ja
2016年論文
@yue
2016年論文
@zh-hant
2016年論文
@zh-hk
2016年論文
@zh-mo
2016年論文
@zh-tw
2016年论文
@wuu
2016年论文
@zh
2016年论文
@zh-cn
name
Open Source Bayesian Models. 3. Composite Models for Prediction of Binned Responses
@ast
Open Source Bayesian Models. 3. Composite Models for Prediction of Binned Responses
@en
type
label
Open Source Bayesian Models. 3. Composite Models for Prediction of Binned Responses
@ast
Open Source Bayesian Models. 3. Composite Models for Prediction of Binned Responses
@en
prefLabel
Open Source Bayesian Models. 3. Composite Models for Prediction of Binned Responses
@ast
Open Source Bayesian Models. 3. Composite Models for Prediction of Binned Responses
@en
P2860
P356
P1476
Open Source Bayesian Models. 3. Composite Models for Prediction of Binned Responses
@en
P2093
Krishna Dole
Sean Ekins
P2860
P304
P356
10.1021/ACS.JCIM.5B00555
P50
P577
2016-01-11T00:00:00Z