Ontotext Life Sciences & Healthcare

Life Sciences, Pharmaceutical and Healthcare companies are faced with unique challenges – analysts and researchers need to quickly search massive document repositories to find very precise sets of information.  Lack of integrated data sources makes this a daunting task.   Complex terminology scattered throughout the documents is not semantically indexed.  The result is lost time and inaccurate search results.

Ontotext Life Sciences dramatically reduces the time it takes to discover relevant content using a unique blend of text mining, a knowledge base of terms, linked open data integration and highly contextual semantic search.    With Ontotext Life Sciences you can:

  • Extract meaning from biomedical text using more than 100 different semantic types.
  • Automatically recognize complex biomedical terms
  • Match and classify those terms to a semantically rich knowledge base with domain specific classifications.
  • Create more depth in your search by annotating the text with names, attributes and descriptions – either for the whole document or a snippet.

Linked Life Data

Ontotext’s Linked Life Data platform provides access to 25 public biomedical databases through a single access point.  The service allows writing of complex data analytical queries, answering complex bioinformatics questions such as ‘give me all human genes located in Y-chromosome with the known molecular interactions.’ You can try the service for free on the Linked Life Data Site.

Semantically Enriched Biomedical Data

An Example of Semantically Enriched Biomedical Data.

Identity Resolution & Semantic Knowledge Base 

Identity Resolution & Semantic Knowledge Base
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Semantic Knowledge Drives the Search

Integrate All Your Data

Document management systems in life sciences store many types of documents, drug assessments and other research.   But organizations are not able to search all the text while navigating across related data sources to get a complete picture.   Ontotext Life Sciences organizes all of the important entities referenced in clinical studies, research projects, product descriptions and target patient profiles inside our semantic repository, GraphDB. We link back to the originating documents to ensure you search the content store and semantically enriched facts at the same time.

Discover Relevant Information

Researchers can find relevant studies along with details on how they were designed.  The search process is instantaneous without the need to to filter through thousands of unrelated documents.  Your current portfolio of clinical trials and research is optimized for search and reuse.  Ontotext Life Sciences applies a comprehensive knowledge base of relevant terms extracted from your most important sources to uncover relevant information.

Text Mining and Annotation

With Ontotext Life Sciences, all of the unstructured and semi-structured data distributed across departmental systems can be processed using industry specific text mining.   Documents and sections within those documents contain large numbers of entities which need to be extracted, classified and annotated with additional meta data.  By classifying these entities your analysts can develop queries that search, key words, concepts and relationships between the facts. We enrich your data with additional knowledge that powers your search and the results.

Entity Recognition and Semantically Enriched Results

Once entities are extracted from your unstructured data, we match them to comprehensive data dictionaries allowing us to annotate the results with new knowledge. Semantic facts are created and stored in GraphDB.  Each entity originally identified in your documents is linked to these facts allowing you to maintain a connection to the original unstructured sources of data.  The result is consistency as data changes.  Synchronization across data sources equates to greater precision in search.   “Semantic Recall” delivers contextual results.

Comprehensive Annotation Types

Ontotext Life Sciences supports many annotation types including genes, malignancies, neoplasms, cell types, cell lines, DNA sequences, RNA sequences, sequence variants and more.  We use rules to link the entities to a valid Universal Resource Indicator (URI) inside GraphDB.  As we recognize entities, we auto-generate a value that combines the originating entity name with the name stored in GraphDB.

Standalone Applications or Integrated Services

Ontotext Life Sciences can be accessed as a standalone application, integrated into a larger solution, accessed as an annotation service or run in a distributed computing architecture using REST for large scale machine information extraction.

Additional Resources

The Latest White Paper from Ontotext: "The Truth About Triplestores"

Download Whitepaper

GraphDB: At Last, the Meaningful Database

 

Download Report

GraphDB Knowledge Path Series: Advanced Features

View the Series