IMole, a web based image retrieval system from biomedical literature. Issue 13 (17th June 2013)

• Record Type: Journal Article
• Authors: Giordano, Manuela; Natale, Massimo; Cornaz, Moreno; Ruffino, Andrea; Bonino, Dario; Bucci, Enrico M.
• Is Part Of: Electrophoresis. Volume 34:Issue 13(2013:Jul.)
• Page Start: 1965
• Page End: 1968
• Publication Date: 2013-06-17
• Subjects: Electrophoresis -- Periodicals; Electrophoresis -- Periodicals; 541.372
• DOI: 10.1002/elps.201300085
• Languages: English
• ISSNs: 0173-0835

Abstract

<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <p>iMole is a platform that automatically extracts images and captions from biomedical literature. Images are tagged with terms contained in figure captions by means of a sophisticate text‐mining tool. Moreover, iMole allows the user to upload directly their own images within the database and manually tag images by curated dictionary. Using iMole the researchers can develop a proper biomedical image database, storing the images extracted from paper of interest, image found on the web repositories, and their own experimental images. In order to show the functioning of the platform, we used iMole to build a 2DE database. Briefly, tagged 2DE gel images were collected and stored in a searchable 2DE gel database, available to users through an interactive web interface. Images were obtained by automatically parsing 16 608 proteomic publications, which yielded more than 16 500 images. The database can be further expanded by users with images of interest trough a manual uploading process. iMole is available with a preloaded set of 2DE gel data at <ext-link ext-link-type="uri" xlink:href="http://imole.biodigitalvalley.com" xlink:type="simple" xmlns:xlink="http://www.w3.org/1999/xlink">http://imole.biodigitalvalley.com</ext-link>.</p> </abstract>