Computational approaches for drug repositioning and combination therapy design.
about
Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive reviewPREDICT: a method for inferring novel drug indications with application to personalized medicineNovel approach to meta-analysis of microarray datasets reveals muscle remodeling-related drug targets and biomarkers in Duchenne muscular dystrophyDrug repositioning by kernel-based integration of molecular structure, molecular activity, and phenotype dataGene Ontology and KEGG Pathway Enrichment Analysis of a Drug Target-Based Classification SystemPredicting drug target interactions using meta-path-based semantic network analysisEriocitrin ameliorates diet-induced hepatic steatosis with activation of mitochondrial biogenesis.Prediction of new drug indications based on clinical data and network modularity.Development of a Novel Zebrafish Model for Type 2 Diabetes Mellitus.Diet-induced obesity in zebrafish shares common pathophysiological pathways with mammalian obesity.Evolution of malignant glioma treatment: from chemotherapy to vaccines to viruses.Drug repositioning through incomplete bi-cliques in an integrated drug-target-disease network.Pathway-based drug repositioning using causal inference.Prediction of drug indications based on chemical interactions and chemical similarities.E2F8 promotes hepatic steatosis through FABP3 expression in diet-induced obesity in zebrafish.Drug repositioning for personalized medicine.Exploring the relationship between drug side-effects and therapeutic indicationsDrug repurposing and adverse event prediction using high-throughput literature analysis.Literature mining, ontologies and information visualization for drug repurposing.Integrating fragmented software applications into holistic solutions: focus on drug discovery.Realizing drug repositioning by adapting a recommendation system to handle the process.Introduction: 4th International Moscow Conference on Computational Molecular Biology MCCMB'09.Changing Trends in Computational Drug Repositioning.
P2860
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P2860
Computational approaches for drug repositioning and combination therapy design.
description
2010 nî lūn-bûn
@nan
2010年の論文
@ja
2010年学术文章
@wuu
2010年学术文章
@zh
2010年学术文章
@zh-cn
2010年学术文章
@zh-hans
2010年学术文章
@zh-my
2010年学术文章
@zh-sg
2010年學術文章
@yue
2010年學術文章
@zh-hant
name
Computational approaches for drug repositioning and combination therapy design.
@en
Computational approaches for drug repositioning and combination therapy design.
@nl
type
label
Computational approaches for drug repositioning and combination therapy design.
@en
Computational approaches for drug repositioning and combination therapy design.
@nl
prefLabel
Computational approaches for drug repositioning and combination therapy design.
@en
Computational approaches for drug repositioning and combination therapy design.
@nl
P2093
P2860
P1476
Computational approaches for drug repositioning and combination therapy design
@en
P2093
Anton Yuryev
Nikolai Daraselia
P2860
P304
P356
10.1142/S0219720010004732
P577
2010-06-01T00:00:00Z