Using information from historical high-throughput screens to predict active compounds.
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Filtered circular fingerprints improve either prediction or runtime performance while retaining interpretabilityMetMaxStruct: A Tversky-Similarity-Based Strategy for Analysing the (Sub)Structural Similarities of Drugs and Endogenous MetabolitesData-driven approaches used for compound library design, hit triage and bioactivity modeling in high-throughput screening.A Multimodal Data Analysis Approach for Targeted Drug Discovery Involving Topological Data Analysis (TDA).Open Source Bayesian Models. 3. Composite Models for Prediction of Binned ResponsesbioassayR: Cross-Target Analysis of Small Molecule Bioactivity.Assessment of the classification abilities of the CNS multi-parametric optimization approach by the method of logistic regression.Physicochemical property profile for brain permeability: comparative study by different approaches.CNS Multiparameter Optimization Approach: Is it in Accordance with Occam's Razor Principle?Using Machine Learning to Predict Synergistic Antimalarial Compound Combinations With Novel Structures
P2860
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P2860
Using information from historical high-throughput screens to predict active compounds.
description
2014 nî lūn-bûn
@nan
2014年の論文
@ja
2014年学术文章
@wuu
2014年学术文章
@zh
2014年学术文章
@zh-cn
2014年学术文章
@zh-hans
2014年学术文章
@zh-my
2014年学术文章
@zh-sg
2014年學術文章
@yue
2014年學術文章
@zh-hant
name
Using information from historical high-throughput screens to predict active compounds.
@en
Using information from historical high-throughput screens to predict active compounds.
@nl
type
label
Using information from historical high-throughput screens to predict active compounds.
@en
Using information from historical high-throughput screens to predict active compounds.
@nl
prefLabel
Using information from historical high-throughput screens to predict active compounds.
@en
Using information from historical high-throughput screens to predict active compounds.
@nl
P356
P1476
Using information from historical high-throughput screens to predict active compounds.
@en
P2093
Jeremy L Jenkins
P304
P356
10.1021/CI500190P
P577
2014-06-26T00:00:00Z