What diseases does this gene impact?

Does this drug have any effect on a particular disease?

Who or which organization has the most expertise and IP in a specific therapeutic area?

While such questions befuddle traditional Search engines, DisKoveror's Content Informatics platform was designed for this.

Life Sciences is an information intensive domain where actionable knowledge is often embedded in technical abstracts, reports, theses, lab workbooks etc. Efficient access to such knowledge generates sizeable time and cost savings thus playing a vital role in the success of every Drug Discovery & Development programs. New ways to speed up the handling of unstructured data are essential to helping a company or a research team reach their goals. Text Mining technology is a very effective means of getting control of an organization's unstructured data.

The 3-steps to Actionable Hypothesis - Discover, Analyze, Visualize, as provided by DisKoveror Text Mining Platform promotes the identification of critical information and relationships between superficially distinct pieces of information. Based on years of research in Machine Learning, Natural Language Processing, Ontologies and BioInformatics, our deep discovery tool unearths concepts, bio-entities and relationships between them to speed up decision making.

Benefits

Enhance Productivity on Drug Discovery through Bio-Entity Relationship Mining Research Trend Analysis to identify areas of Opportunities, Alliances & Competition Semantic & Context-Sensitive Discovery Theme-based Dynamic Knowledge Clustering Improve Relevance through Customizable User Profiles Integration with Medline, USPTO, Clinical Trials, Google Scholar Federated Ontology integration Community-driven product development that ensures rapid innovation, enhanced usability & low TCO