Mining Chemical Activity Status from High-Throughput Screening Assays
about
DRABAL: novel method to mine large high-throughput screening assays using Bayesian active learningDASPfind: new efficient method to predict drug–target interactionsbioassayR: Cross-Target Analysis of Small Molecule Bioactivity.DDR: Efficient computational method to predict drug-target interactions using graph mining and machine learning approaches.A desirability-based multi objective approach for the virtual screening discovery of broad-spectrum anti-gastric cancer agents.DPubChem: a web tool for QSAR modeling and high-throughput virtual screening.DANNP: an efficient artificial neural network pruning tool
P2860
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P2860
Mining Chemical Activity Status from High-Throughput Screening Assays
description
2015 nî lūn-bûn
@nan
2015 թուականին հրատարակուած գիտական յօդուած
@hyw
2015 թվականին հրատարակված գիտական հոդված
@hy
2015年の論文
@ja
2015年論文
@yue
2015年論文
@zh-hant
2015年論文
@zh-hk
2015年論文
@zh-mo
2015年論文
@zh-tw
2015年论文
@wuu
name
Mining Chemical Activity Status from High-Throughput Screening Assays
@ast
Mining Chemical Activity Status from High-Throughput Screening Assays
@en
Mining Chemical Activity Status from High-Throughput Screening Assays
@nl
type
label
Mining Chemical Activity Status from High-Throughput Screening Assays
@ast
Mining Chemical Activity Status from High-Throughput Screening Assays
@en
Mining Chemical Activity Status from High-Throughput Screening Assays
@nl
prefLabel
Mining Chemical Activity Status from High-Throughput Screening Assays
@ast
Mining Chemical Activity Status from High-Throughput Screening Assays
@en
Mining Chemical Activity Status from High-Throughput Screening Assays
@nl
P2093
P2860
P50
P3181
P1433
P1476
Mining Chemical Activity Status from High-Throughput Screening Assays
@en
P2093
Moataz Afeef
Othman Soufan
Valentin Rodionov
P2860
P304
P3181
P356
10.1371/JOURNAL.PONE.0144426
P407
P577
2015-01-01T00:00:00Z