Case studies, datasheets, documentation & analyst reports on semantic search and text mining in life sciences available for download
Featured Report: "Semantic Software Technologies: Landscape of High Value Applications for the Enterprise"
This study, published by Gilbane Group, a division of Outsell Inc, covers areas including: the growing need for semantic software to meaningfully manage the rapidly increasing volumes of unstructured data and information; the various solutions available and how these are improving and maturing; and an overview of the tangible benefits seen by adopters of these technologies. The Linguamatics Deep Dive, by the same author, highlights Linguamatics' leadership position in the life sciences market with I2E.
Gilbane Semantic Software Technologies Study
Gilbane Linguamatics Deep Dive
I2E Case Studies: Text Mining for Life Science
These case studies show how I2E has been used to capture valuable information from life sciences literature in a number of important application areas, saving time and increasing productivity
Creating a Target Selection Framework with Linguamatics I2E at AstraZeneca
A case study from Pfizer RTC where I2E was used for target prioritization.
Two specific case studies from AstraZeneca and Biowisdom covering the reconstruction of a biological pathway and the identification of nuclear co-factors.
Text mining in a biotech setting at Syntaxin
Interactive Information Extraction (I2E) can be used in diverse application areas such as systems biology, biomarker detection, safety/tox and drug repositioning in pharmaceutical R&D to key opinion leader, sentiment and competitive analysis for business intelligence. I2E's powerful NLP capabilities mine large collections of documents, extracting relevant facts and relationships from unstructured and semi-structured content such as scientific papers, internal project reports, patent documents, or news feeds.
Linguamatics I2E: Solution Overview
I2E OnDemand Datasheet
I2E Pipeline Pilot Components Datasheet
Linguamatics in Healthcare
I2E ChiKEL (Chemically Informed Knowledge Extraction from Literature)
Insights and Intelligence from Text using Linguamatics I2E (white paper)
Business and research organizations face a huge challenge to unlock the meaning within text to inform business critical decision making. This white paper describes how Linguamatics I2E Linguamatics is at the forefront of a new generation of knowledge discovery technology.
CALBC Silver Standard Corpus
Rebholz-Schuhmann et al.
Journal of Bioinformatics and Computational Biology, Vol. 8, Issue 1, pp. 163-179 (2010)
Protein-Protein Interactions from Published Literature
Using Linguamatics I2E
Bandy, J., Milward, D., McQuay, S. Methods Mol. Biol. 2009
Mapping similarities in mTOR pathway perturbations in mouse lupus nephritis models and human lupus nephritis
Padmalatha S Reddy, Holly M Legault et al.
Arthritis Research & Therapy 2008 (doi:10.1186/ar2541)
Identifying and classifying biomedical perturbations in text
Raul Rodriguez-Esteban; Phoebe M. Roberts; Matthew E. Crawford
Nucleic Acids Research 2008 (doi: 10.1093/nar/gkn986)
Early Identification of Potential Drug Safety Issues from Diverse Literature Resources
Sarah J McQuay
Text Data Mining using Interactive Information Extraction
David Milward and Paul Milligan
BioLINK SIG Text Mining Workshop, ISMB/ECCB 2007
Flexible Text Mining Strategies for Drug Discovery
David Milward et al.
Proc. Second International Symposium on Semantic Mining in BioMedicine (SMBM 2006), pp. 101-104
Text Mining: getting more value from literature resources
Drug Discovery Today, Vol. 10, Issue 6, pp. 377-379 (15 March 2005)
Ontology-based Interactive Information Extraction from Scientific Abstracts
David Milward et al.
BioLINK SIG Text Mining Workshop, ISMB/ECCB 2004
Automatic Extraction of Protein Interactions from Scientific Abstracts
James Thomas et al.
Pacific Symposium on Biocomputing 2000
From Information Retrieval to Information Extraction
David Milward and James Thomas
ACL 2000 Workshop on Recent Advances in Natural Language Processing and Information Retrieval