Rockville, MD (PRWEB) January 25, 2006 -- Ariadne Genomics, Inc. today announced the release of MedScan ReaderT 1.0, a new category of desktop software that enables automated extraction of information from scientific text. This software, developed for a broad range of life science professionals and biomedical students, dramatically facilitates professional reading and reduces time spent on literature research.
MedScan Reader is the first commercially available product with the ability to read and digest thousands of abstracts or documents on the fly, summarize content, and provide an instant snapshot of relevant information. This user-friendly product is helpful for students, post-docs, professors and doctors specializing in various areas of the biomedical field. MedScan Reader understands a broad range of subjects, and can process documents on numerous aspects of protein function, biochemistry, cellular physiology and molecular pathology.
MedScan Reader is derived from MedScanT, Ariadne's well-established information extraction technology based on natural language processing (NLP). Over the past few years, MedScan has been deployed as an information extraction tool at a number of biotechnology and pharmaceutical companies. This product has also been used for the creation of Ariadne's ResNetT database, the core data source for PathwayStudio® (former PathwayAssist) pathway analysis software.
"For its ease of use and great time saving ability, MedScan Reader is a "must have" tool for any student, researcher or professional dealing with literature in the biomedical domain", commented Nikolai Daraselia, Senior Director of Research at Ariadne. "This tool is integrated with Ariadne's PathwayStudio® software for easy graphical representation of the summarized extracted information."
Experience in the global biomedical and bioinformatics industries leads Ariadne to believe that MedScan Reader is a crucial first step in the development of Semantic Web domain. MedScan Reader facilitates viewing and browsing the network of knowledge extracted from multiple biomedical web resources (PubMed, Google Scholar), and locally stored files, file catalogs and archives in different formats.