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Digital Lance works with partners and clients on entrepreneurial projects and consulting services in text analytics data mining machine learning recommendation knowledge discovery and computational analysis Products and solutions include hosted, web-based and stand-alone applications.

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Products

The Electronic Library Catalog (eLCe) is an easy to use and manage, hosted book catalog, targeted to the needs of corporate libraries. Includes direct user to user borrowing, book recommendations, view of new library additions, and more. Uses Amazon to seamlessly integrate book ordering functionality.

URL: http://elce.us

The Drug Regulatory Documents Service (DRD) facilitates easier access to public drug filing information, making it easy to download OCR-ed, fully searchable PDFs for both the FDA (US Food & Drug Administration) and EMA (European Medicines Agency).

URL: http://drugregdocs.com

Ancient Arcana

At SeeqPod, Inc., ca. 2008, Digital Lance developed novel recommendation techniques applied in music and media discovery, as well as other vertical domains.

At Oracle Life Sciences, ca. 2005, Digital Lance developed biomedical focused demos (See Oracle Life Sciences Platform Sample Code):

  • Oracle BLAST Demo - Innovative approach allowed target and query sequence lists to be selected dynamically based on annotation metadata.
  • MEDLINE Text Mining Demo - A complete browser-based analysis pipeline of PubMed records including search, clustering, interactive document classification, feature extraction, NLP functional phrase extraction and visualization.

At AstraZeneca, ca. 2003, Digital Lance developed:

  • SureGene - a large scale, literature-based, gene name disambiguation strategy and system.
  • PLIMS - a web-based project literature management system, allowing shared access to an autoupdating project knowledge base with multi-level annotation capability.

Current Projects

Digital Lance is actively involved in a number of projects including a startup venture in information management, currently in stealth mode.

Computational modeling of nuclear reactor thermal-hydraulics during transients and accidents. The objective of the project is to develop computational models of flow and heat transfer phenomena for the analysis of reactor response over a broad range of transient and accident conditions. The work includes model encoding using the Python programming language, computer implementation and testing.

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Fun with Amazon Books

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