How do you scan millions of publications, patents, reports and any other document type to get at the information you need most?
More and more of the fundamental science content critical to the innovation process is locked up inside electronic documents.
TERMite (TERM identification, tagging & extraction) is the ultra-fast named entity recognition (NER) and extraction engine at the heart of our semantic analytics software suite.
Coupled with our hand-curated VOCabs, it can recognise and extract relevant terms found in scientific text transforming unstructured content into rich, machine-readable data.
Information Professionals
You Are: A life science professional who’s job involves hunting for key facts in literature, patents, grants and internal documents.
We Offer: The ability to data-mine millions of documents to identify critical mentions and relationships.
Enterprise Search
You Are: A company wishing to make its internal search portals more accurate.
We Offer: The ability to enhance your existing search tool to find key biological entities more accurately, making your users happier and more productive!
Solution Provider
You Are: Anyone who produces textual content in the life-sciences or supplies IT systems that contain such text within them (ELNs, Project Management Tools, Industry Databases etc.)
We Offer: The opportunity to enrich your content for search, navigation and significantly increase the value to your consumers.
As a Software-as-a-Service (SaaS) solution, deployment of TERMite has never been simpler. Users benefit from the latest features through seamless product upgrades, as well as with expanded infrastructure support. You will have the freedom to run one- off analyses in the user interface, or embed TERMite into your analysis workflow to harness its full potential. For more details take a look at our SaaS FAQs.
Latest features of TERMite
The latest TERMite 6.4 release has a number of features and updates aimed at making your research smarter and faster. The latest features include:
- Access up to 23 NER machine learning models
- Bundle Editor – Create and manage your advanced TExpress pattern searches queries
- TERMite- CENtree one click – Edit publicly available ontologies in CENtree and upload these easily into TERMite
- New Security Manager – Assign and use roles to control access to your TERMite domains
- Vocab hot-reloading – Set your TERMite server to scan for the latest updates
- Enhanced Server monitor tool
- Regular expressions as synonyms
- Parallelisation in Java API
- Improved python support
- Parallel server-batch mode
- Enhanced scripting support
Get in touch with the team to learn more or download the TERMite datasheet.
VOCabs – Premade Expert Ontologies
Computational approaches help to sift through and identify relevant material from multiple sources but struggle to deal with the ambiguity of scientific literature. Multiple terms can be used to describe the same topic making any keyword search difficult.
Our high-quality vocabularies and ontologies provide the critical foundation which enables SciBite’s TERMite engine to accurately detect important topics within biomedical text.
Each vocabulary is enhanced by a combination of our in-house and experienced hands-on ontologists and biocurators and our proprietary ontology enrichment software.
Our VOCabs cover many more topics in far greater depth than any publicly available ontologies such as MeSH, Uniprot and MeDDRA.
If you’re not using SciBite VOCabs, you’re not going to capture the information your users need.
Get in touch with the team to learn more or download the VOCabs datasheet.
Key product highlights
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Rapid Start-Up
Get up-and-running quickly, with no pre-indexing or complex set-up required
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Robust
Enterprise-grade and scalable to billions of documents, with the ability to run large-scale document processing on systems such as Hadoop
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Accurate
Precisely tag and disambiguate scientific terms in unstructured scientific text using SciBite’s VOCabs containing >20 million synonyms across >80 Life Science topics including genes, drugs, diseases, adverse events
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Ultra-Fast
Process millions of documents such as the entire Medline database, or large numbers of patent or internal documents in minutes
Want to learn more about TERMite?
Get in touch with us to find out how we can transform your data
Contact usUse cases
Biomarker discovery in literature
[Use Case]
The identification and application of biomarkers in basic and clinical research is almost a mandatory process in any productive pipeline of a pharmaceutical organisation. Validated biomarkers play a crucial role in the prediction of clinical outcome and support the translation from candidate discovery to successful clinical treatment.
A wealth of valuable biomarker-related information is available in the biomedical literature. However, the process of discovering and validating new biomarkers depends on the ability to extract insight from this resource effectively.
SciBite uses semantic enrichment to unlock the value of unstructured text and simplify the identification of new potential biomarker leads from scientific text.
Eliminating the data preparation burden
[Use case]
For most pharmaceutical companies, extracting insight from heterogeneous and ambiguous data remains a challenge. The era of data-driven R&D is motivating investment in technologies such as machine learning to provide deeper insights into new drug development strategies.
The quality of data directly impacts the accuracy and reliability of the results of computational approaches. However, the work required to achieve clean, high-quality data can be costly, often prohibitively so, requiring data scientists to spend the majority of their time as ‘data janitors’, rather than actually analyzing data.
SciBite provides an integrated, cost-effective solution to significantly reduce the time and cost associated with the process of data cleansing, normalization and annotation. The output ensures that downstream integration and discovery activities are based on high-quality, contextualized data.
