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https://olympias.lib.uoi.gr/jspui/handle/123456789/9298Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Janga, S. C. | en |
| dc.contributor.author | Tzakos, A. | en |
| dc.date.accessioned | 2015-11-24T16:48:17Z | - |
| dc.date.available | 2015-11-24T16:48:17Z | - |
| dc.identifier.issn | 1742-2051 | - |
| dc.identifier.uri | https://olympias.lib.uoi.gr/jspui/handle/123456789/9298 | - |
| dc.rights | Default Licence | - |
| dc.subject | Drug Delivery Systems/*methods | en |
| dc.subject | Drug Discovery/*methods | en |
| dc.subject | Genomics/*methods | en |
| dc.title | Structure and organization of drug-target networks: insights from genomic approaches for drug discovery | en |
| heal.type | journalArticle | - |
| heal.type.en | Journal article | en |
| heal.type.el | Άρθρο Περιοδικού | el |
| heal.identifier.primary | 10.1039/B908147j | - |
| heal.identifier.secondary | http://www.ncbi.nlm.nih.gov/pubmed/19763339 | - |
| heal.identifier.secondary | http://pubs.rsc.org/en/Content/ArticleLanding/2009/MB/b908147j | - |
| heal.language | en | - |
| heal.access | campus | - |
| heal.recordProvider | Πανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Χημείας | el |
| heal.publicationDate | 2009 | - |
| heal.abstract | Recent years have seen an explosion in the amount of "omics" data and the integration of several disciplines, which has influenced all areas of life sciences including that of drug discovery. Several lines of evidence now suggest that the traditional notion of "one drug-one protein" for one disease does not hold any more and that treatment for most complex diseases can best be attempted using polypharmacological approaches. In this review, we formalize the definition of a drug-target network by decomposing it into drug, target and disease spaces and provide an overview of our understanding in recent years about its structure and organizational principles. We discuss advances made in developing promiscuous drugs following the paradigm of polypharmacology and reveal their advantages over traditional drugs for targeting diseases such as cancer. We suggest that drug-target networks can be decomposed to be studied at a variety of levels and argue that such network-based approaches have important implications in understanding disease phenotypes and in accelerating drug discovery. We also discuss the potential and scope network pharmacology promises in harnessing the vast amount of data from high-throughput approaches for therapeutic advantage. | en |
| heal.publisher | Royal Society of Chemistry | en |
| heal.journalName | Mol Biosyst | en |
| heal.journalType | peer reviewed | - |
| heal.fullTextAvailability | TRUE | - |
| Appears in Collections: | Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά). ΧΗΜ | |
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