Modelling of compound combination effects and applications to efficacy and toxicity: state-of-the-art, challenges and perspectives
about
Synergy Maps: exploring compound combinations using network-based visualizationThe Role of Interaction Model in Simulation of Drug Interactions and QT ProlongationCancer network activity associated with therapeutic response and synergism.Advances in computational approaches in identifying synergistic drug combinations.Looking beyond the cancer cell for effective drug combinations.Interactions between phytochemicals from fruits and vegetables: Effects on bioactivities and bioavailability.Predictive approaches for drug combination discovery in cancer.Collaborative drug discovery for More Medicines for Tuberculosis (MM4TB).Editorial: Computational and Experimental Approaches in Multi-target Pharmacology.Towards natural mimetics of metformin and rapamycin.DeepSynergy: Predicting anti-cancer drug synergy with Deep Learning.Development of a 4-aminopyrazolo[3,4-d]pyrimidine-based dual IGF1R/Src inhibitor as a novel anticancer agent with minimal toxicity.A systematic and prospectively validated approach for identifying synergistic drug combinations against malaria.Using Machine Learning to Predict Synergistic Antimalarial Compound Combinations With Novel StructuresModeling the impact of drug interactions on therapeutic selectivity
P2860
Q27902355-74BA97A7-7689-429E-9190-AD830CF336EFQ28077218-6CAECF29-BB56-425B-99E6-02CFD44862D2Q37199267-3FB5D3D9-CDD5-4CE4-B017-FA43C47A42C3Q38687343-777923FA-16FB-4F83-B390-F3FFC03F241AQ38728970-605DD474-4B2B-4B99-8268-DA4545DD530DQ38791590-861DB83C-F8DC-4650-8932-0C790B59FD2DQ39018410-A1ECB9FE-46CF-44A8-8B36-F7CEBE6DEFC1Q39019116-0AC66FA4-CD4A-4E78-8E3D-1A3611560D1FQ42333457-ADAC0A9F-D816-45ED-8DFD-7A91A538F9C2Q47140599-4AEA7A29-A603-4FE0-BB7E-67BB853D9C22Q47290651-D2D983F9-9327-42DD-8D5E-4C8D93477FF6Q49887912-137DDEA3-FD24-40E0-BA1C-C5B1578C8D61Q52593425-806FB908-422F-4C8B-BCD5-4830A858CD82Q58586909-F64E6572-CC6E-4249-A032-6502C0D9579AQ58701229-8F3168F5-4350-4DDF-BD10-A15D9162A99E
P2860
Modelling of compound combination effects and applications to efficacy and toxicity: state-of-the-art, challenges and perspectives
description
2016 nî lūn-bûn
@nan
2016 թուականի Փետրուարին հրատարակուած գիտական յօդուած
@hyw
2016 թվականի փետրվարին հրատարակված գիտական հոդված
@hy
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
name
Modelling of compound combinat ...... t, challenges and perspectives
@ast
Modelling of compound combinat ...... t, challenges and perspectives
@en
Modelling of compound combinat ...... t, challenges and perspectives
@nl
type
label
Modelling of compound combinat ...... t, challenges and perspectives
@ast
Modelling of compound combinat ...... t, challenges and perspectives
@en
Modelling of compound combinat ...... t, challenges and perspectives
@nl
prefLabel
Modelling of compound combinat ...... t, challenges and perspectives
@ast
Modelling of compound combinat ...... t, challenges and perspectives
@en
Modelling of compound combinat ...... t, challenges and perspectives
@nl
P2093
P50
P3181
P1433
P1476
Modelling of compound combinat ...... t, challenges and perspectives
@en
P2093
Daniel J Mason
Krishna C Bulusu
Murat Cokol
Rajarshi Guha
Richard P I Lewis
Yasaman Kalantar Motamedi
P304
P3181
P356
10.1016/J.DRUDIS.2015.09.003
P407
P577
2016-02-01T00:00:00Z