An automated tool for obtaining QSAR-ready series of compounds using semantic web technologies

López-Massaguer, Oriol; Sanz, Ferrán; Pastor, Manuel

doi:10.1093/bioinformatics/btx566

Cited by 4 publications

(1 citation statement)

References 13 publications

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“…This work has subsequently been extended by Miller et al [74] to use WikiPathways data [61] (which is a database of biological pathways). López-Massaguer [75] used data extracted from Open PHACTS in their work to obtain QSAR-ready compounds using semantic web technologies.…”

Section: Semantic Search Engines For Drug Discoverymentioning

confidence: 99%

A new wave of innovation in Semantic web tools for drug discovery

Kanza

Frey

2019

Expert Opinion on Drug Discovery

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Introduction: The use of semantic web technologies to aid drug discovery has gained momentum over recent years. Researchers in this domain have realized that semantic web technologies are key to dealing with the high levels of data for drug discovery. These technologies enable us to represent the data in a formal, structured, interoperable and comparable way, and to tease out undiscovered links between drug data (be it identifying new drug-targets or relevant compounds, or links between specific drugs and diseases). Areas covered: This review focuses on explaining how semantic web technologies are being used to aid advances in drug discovery. The main types of semantic web technologies are explained, outlining how they work and how they can be used in the drug discovery process, with a consideration of how the use of these technologies has progressed from their initial usage. Expert opinion: The increased availability of shared semantic resources (tools, data and importantly the communities) have enabled the application of semantic web technologies to facilitate semantic (context dependent) search across multiple data sources, which can be used by machine learning to produce better predictions by exploiting the semantic links in knowledge graphs and linked datasets.

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Section: Semantic Search Engines For Drug Discoverymentioning

confidence: 99%