A Computational Approach for Identifying Synergistic Drug Combinations.
about
Improving the efficacy-safety balance of polypharmacology in multi-target drug discovery.Prediction of Effective Drug Combinations by an Improved Naïve Bayesian Algorithm.In silico drug combination discovery for personalized cancer therapy.Chemical Genetic Screens Identify Kinase Inhibitor Combinations that Target Anti-Apoptotic Proteins for Cancer Therapy.Systems modelling of the EGFR-PYK2-c-Met interaction network predicts and prioritizes synergistic drug combinations for triple-negative breast cancer.Using Machine Learning to Predict Synergistic Antimalarial Compound Combinations With Novel Structures
P2860
A Computational Approach for Identifying Synergistic Drug Combinations.
description
2017 nî lūn-bûn
@nan
2017年の論文
@ja
2017年論文
@yue
2017年論文
@zh-hant
2017年論文
@zh-hk
2017年論文
@zh-mo
2017年論文
@zh-tw
2017年论文
@wuu
2017年论文
@zh
2017年论文
@zh-cn
name
A Computational Approach for Identifying Synergistic Drug Combinations.
@ast
A Computational Approach for Identifying Synergistic Drug Combinations.
@en
type
label
A Computational Approach for Identifying Synergistic Drug Combinations.
@ast
A Computational Approach for Identifying Synergistic Drug Combinations.
@en
prefLabel
A Computational Approach for Identifying Synergistic Drug Combinations.
@ast
A Computational Approach for Identifying Synergistic Drug Combinations.
@en
P2093
P2860
P1476
A Computational Approach for Identifying Synergistic Drug Combinations.
@en
P2093
David F Stern
James Platt
Kaitlyn M Gayvert
Marcus W Bosenberg
P2860
P304
P356
10.1371/JOURNAL.PCBI.1005308
P577
2017-01-13T00:00:00Z