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      Network-based Approaches in Pharmacology

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          Most cited references53

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          Is Open Access

          DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants

          The information about the genetic basis of human diseases lies at the heart of precision medicine and drug discovery. However, to realize its full potential to support these goals, several problems, such as fragmentation, heterogeneity, availability and different conceptualization of the data must be overcome. To provide the community with a resource free of these hurdles, we have developed DisGeNET (http://www.disgenet.org), one of the largest available collections of genes and variants involved in human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype–phenotype relationships. The information is accessible through a web interface, a Cytoscape App, an RDF SPARQL endpoint, scripts in several programming languages and an R package. DisGeNET is a versatile platform that can be used for different research purposes including the investigation of the molecular underpinnings of specific human diseases and their comorbidities, the analysis of the properties of disease genes, the generation of hypothesis on drug therapeutic action and drug adverse effects, the validation of computationally predicted disease genes and the evaluation of text-mining methods performance.
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            Multicomponent therapeutics for networked systems.

            Therapeutic regimens that comprise more than one active ingredient are commonly used in clinical medicine. Despite this, most drug discovery efforts search for drugs that are composed of a single chemical entity. A focus in the early drug discovery process on identifying and optimizing the activity of combinations of molecules can result in the identification of more effective drug regimens. A systems perspective facilitates an understanding of the mechanism of action of such drug combinations.
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              Global mapping of pharmacological space.

              We present the global mapping of pharmacological space by the integration of several vast sources of medicinal chemistry structure-activity relationships (SAR) data. Our comprehensive mapping of pharmacological space enables us to identify confidently the human targets for which chemical tools and drugs have been discovered to date. The integration of SAR data from diverse sources by unique canonical chemical structure, protein sequence and disease indication enables the construction of a ligand-target matrix to explore the global relationships between chemical structure and biological targets. Using the data matrix, we are able to catalog the links between proteins in chemical space as a polypharmacology interaction network. We demonstrate that probabilistic models can be used to predict pharmacology from a large knowledge base. The relationships between proteins, chemical structures and drug-like properties provide a framework for developing a probabilistic approach to drug discovery that can be exploited to increase research productivity.
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                Author and article information

                Journal
                Molecular Informatics
                Mol. Inf.
                Wiley
                18681743
                October 2017
                October 2017
                July 10 2017
                : 36
                : 10
                : 1700048
                Affiliations
                [1 ]Université Paris Diderot - Inserm UMR-S973; MTi, 75205; Paris Cedex 13 75013 Paris France
                [2 ]Institut de Recherche Servier; 125 Chemin de Ronde 78290 Croissy-sur-Seine France
                Article
                10.1002/minf.201700048
                28692140
                47fd58c6-fb35-45a8-9246-abe7a8d2b865
                © 2017

                http://doi.wiley.com/10.1002/tdm_license_1.1

                http://onlinelibrary.wiley.com/termsAndConditions#vor

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