Elsevier, a global leader in information analytics, has launched EmBiology, a research tool that provides unparalleled insights into biological activities, thereby accelerating drug discovery. EmBiology is powered by Elsevier's Biology Knowledge Graph, which draws on more than 7.2 million full-text journal articles, 34.5 million abstracts, and 430,000 clinical trials from Elsevier content and third-party publishers. This comprehensive landscape of biological relationships empowers researchers to gain a rapid understanding of disease biology and focus on critical evidence.
Researchers working in drug discovery and development will be able to intuitively explore biological relationships and concepts to improve drug target and biomarker identification and prioritization. The depth and reliability of EmBiology's data will enable more confident decision-making about what targets to pursue and how to modulate the disease process. The resulting knowledge graph includes 1.4 million entities connected by 15.7 million relationships to enable deep insights from a broad range of literature, with more added weekly.
EmBiology automates data curation with technology that transforms unstructured text into structured information. The tool surfaces relationship information, including directionality and effect, for a wide range of subject areas, including expression, biomarkers, and regulation. Results are displayed in a Sankey diagram that visually facilitates understanding of disease development, progression, and drug responsiveness, whatever the researchers' level of data skills. Users can also apply filters to narrow down their research questions and rapidly confirm their experimental hypotheses for new drug targets, biomarkers, and drug repurposing projects.
Elsevier has a longstanding reputation as a leader in managing and disseminating scientific information and classifying life science data. A team of subject matter experts developed and refined their Biology Knowledge Graph over a period of more than 20 years. EmBiology is built on this powerful data model, so that researchers can get precise answers to their questions without worrying about structuring data.
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