scholarly article | Q13442814 |
P8978 | DBLP publication ID | journals/bmcsb/ChenLYYL15 |
P6179 | Dimensions Publication ID | 1021324036 |
P356 | DOI | 10.1186/S12918-015-0202-Y |
P932 | PMC publication ID | 4574089 |
P698 | PubMed publication ID | 26377814 |
P5875 | ResearchGate publication ID | 282040655 |
P2093 | author name string | Xi Liu | |
Peng Lu | |||
Di Chen | |||
Hongjun Yang | |||
Yiping Yang | |||
P2860 | cites work | Systems Pharmacology: Network Analysis to Identify Multiscale Mechanisms of Drug Action | Q26824166 |
Comparative analysis of the omics technologies used to study antimonial, amphotericin B, and pentamidine resistance in leishmania | Q27009505 | ||
Combination therapy with clopidogrel and aspirin: can the CURE results be extrapolated to cerebrovascula patients? | Q28191858 | ||
Prediction of drug combinations by integrating molecular and pharmacological data | Q28478623 | ||
Multi-target drugs: the trend of drug research and development | Q28480888 | ||
Systems modeling of anti-apoptotic pathways in prostate cancer: psychological stress triggers a synergism pattern switch in drug combination therapy | Q28536000 | ||
Computational analyses of synergism in small molecular network motifs | Q28541174 | ||
Synergistic and antagonistic drug combinations depend on network topology | Q28542101 | ||
Network-based drug discovery by integrating systems biology and computational technologies | Q28677268 | ||
Network motifs: simple building blocks of complex networks | Q29547340 | ||
The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease | Q29547614 | ||
Theoretical basis, experimental design, and computerized simulation of synergism and antagonism in drug combination studies | Q29616780 | ||
Drug combination studies and their synergy quantification using the Chou-Talalay method | Q29617422 | ||
Models of signalling networks – what cell biologists can gain from them and give to them | Q30413382 | ||
Combinatorial drug screening identifies compensatory pathway interactions and adaptive resistance mechanisms | Q30418057 | ||
Getting started in biological pathway construction and analysis. | Q33332472 | ||
U.S. Food and drug administration approval: obinutuzumab in combination with chlorambucil for the treatment of previously untreated chronic lymphocytic leukemia | Q33415277 | ||
A formal model for analyzing drug combination effects and its application in TNF-alpha-induced NFkappaB pathway | Q33563358 | ||
Chemogenomic profiling predicts antifungal synergies. | Q33668319 | ||
A systems biology approach to identify effective cocktail drugs | Q33692329 | ||
Use of transcriptomics in understanding mechanisms of drug-induced toxicity | Q33909001 | ||
An enhanced Petri-net model to predict synergistic effects of pairwise drug combinations from gene microarray data | Q33936078 | ||
Network target for screening synergistic drug combinations with application to traditional Chinese medicine | Q33937467 | ||
Discovering causal signaling pathways through gene-expression patterns | Q33957823 | ||
PPI network analysis of mRNA expression profile of ezrin knockdown in esophageal squamous cell carcinoma | Q34003617 | ||
Aggrenox: a fixed-dose combination of aspirin and dipyridamole | Q34093604 | ||
Modeling gene regulatory network motifs using Statecharts | Q34248010 | ||
Comparing different ODE modelling approaches for gene regulatory networks. | Q51803503 | ||
The problem of synergism and antagonism of combined drugs | Q73248616 | ||
A mathematical model of combination therapy using the EGFR signaling network | Q81460123 | ||
DCDB: drug combination database | Q82329206 | ||
Mechanisms of drug combinations: interaction and network perspectives | Q83265745 | ||
NetCAD: a network analysis tool for coronary artery disease-associated PPI network | Q85477861 | ||
Novel HIV-1 treatment Stribild™ gains regulatory approval | Q85647393 | ||
Exploring drug combinations in genetic interaction network | Q34272629 | ||
Polypharmacology: drug discovery for the future | Q34319906 | ||
Comparative transcriptomics and metabolomics in a rhesus macaque drug administration study. | Q34521873 | ||
Proof of Concept: Network and Systems Biology Approaches Aid in the Discovery of Potent Anticancer Drug Combinations | Q34684352 | ||
When does 2 plus 2 equal 5? A review of antimicrobial synergy testing | Q35036156 | ||
Network Modeling of MDM2 Inhibitor-Oxaliplatin Combination Reveals Biological Synergy in wt-p53 solid tumors | Q35640255 | ||
Systematic exploration of synergistic drug pairs | Q35682094 | ||
Biological network motif detection: principles and practice | Q35803911 | ||
The efficiency of multi-target drugs: the network approach might help drug design | Q36088532 | ||
Multi-target therapeutics: when the whole is greater than the sum of the parts | Q36697412 | ||
Models from experiments: combinatorial drug perturbations of cancer cells | Q36930517 | ||
A pathway-based view of human diseases and disease relationships | Q37073294 | ||
Prediction of effective drug combinations by chemical interaction, protein interaction and target enrichment of KEGG pathways | Q37191078 | ||
Synergistic combinations of signaling pathway inhibitors: mechanisms for improved cancer therapy | Q37227994 | ||
Predicting cooperative drug effects through the quantitative cellular profiling of response to individual drugs | Q37620395 | ||
Network quantification of EGFR signaling unveils potential for targeted combination therapy. | Q37660498 | ||
Functional motifs in biochemical reaction networks. | Q37670151 | ||
Drug synergy screen and network modeling in dedifferentiated liposarcoma identifies CDK4 and IGF1R as synergistic drug targets. | Q37723910 | ||
Systems biology approaches and tools for analysis of interactomes and multi-target drugs | Q37786268 | ||
Systems approaches and algorithms for discovery of combinatorial therapies | Q37787998 | ||
Exploring the Genomes of Cancer Cells: Progress and Promise | Q37857590 | ||
Quantitative Methods for Assessing Drug Synergism | Q38022020 | ||
Applying systems biology in drug discovery and development | Q38101235 | ||
Systems biology in drug discovery and development | Q38152172 | ||
Toward a road map for global -omics: a primer on -omic technologies | Q38269544 | ||
The PPI network and cluster ONE analysis to explain the mechanism of bladder cancer | Q38491185 | ||
Topotecan and Doxorubicin Combination to Treat Recurrent Ovarian Cancer: The Influence of Drug Exposure Time and Delivery Systems to Achieve Optimum Therapeutic Activity | Q39213306 | ||
Systems-pharmacology dissection of a drug synergy in imatinib-resistant CML. | Q39268913 | ||
Antitumour effect of combination treatment with Sabarubicin (MEN 10755) and cis-platin (DDP) in human lung tumour xenograft | Q40044789 | ||
DrugComboRanker: drug combination discovery based on target network analysis | Q40749664 | ||
Large-scale exploration and analysis of drug combinations. | Q41455882 | ||
A Critical Role for Immune System Response in Mediating Anti-influenza Drug Synergies Assessed by Mechanistic Modeling | Q41745036 | ||
In vitro evaluation of a new drug combination against clinical isolates belonging to the Mycobacterium abscessus complex | Q41755797 | ||
Signal transduction network motifs and biological memory | Q42065933 | ||
Multi-omic landscape of rheumatoid arthritis: re-evaluation of drug adverse effects | Q42975335 | ||
Use of the recommended drug combination for secondary prevention after a first occurrence of acute coronary syndrome in France. | Q45371516 | ||
Network-based target ranking for polypharmacological therapies. | Q48013558 | ||
Hybrid modeling of the crosstalk between signaling and transcriptional networks using ordinary differential equations and multi-valued logic | Q48017807 | ||
The dynamics of p53 in single cells: physiologically based ODE and reaction-diffusion PDE models | Q50231706 | ||
P275 | copyright license | Creative Commons Attribution 4.0 International | Q20007257 |
P6216 | copyright status | copyrighted | Q50423863 |
P921 | main subject | systems biology | Q815297 |
P304 | page(s) | 56 | |
P577 | publication date | 2015-09-16 | |
P1433 | published in | BMC Systems Biology | Q4835949 |
P1476 | title | Systematic synergy modeling: understanding drug synergy from a systems biology perspective | |
P478 | volume | 9 |
Q39433962 | Bacteriocin-Antimicrobial Synergy: A Medical and Food Perspective. |
Q52643927 | CISNE: An accurate description of dose-effect and synergism in combination therapies. |
Q39016850 | Current Trends in Multidrug Optimization |
Q52344630 | Facilitating Anti-Cancer Combinatorial Drug Discovery by Targeting Epistatic Disease Genes |
Q64235722 | Synergistic drug combinations prediction by integrating pharmacological data |
Q64102412 | Synergy from gene expression and network mining (SynGeNet) method predicts synergistic drug combinations for diverse melanoma genomic subtypes |
Q37581711 | Transcriptome and network analyses in Saccharomyces cerevisiae reveal that amphotericin B and lactoferrin synergy disrupt metal homeostasis and stress response |
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