Literature DB >> 23592298

iMole, a web based image retrieval system from biomedical literature.

Manuela Giordano1, Massimo Natale, Moreno Cornaz, Andrea Ruffino, Dario Bonino, Enrico M Bucci.   

Abstract

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 http://imole.biodigitalvalley.com.
© 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  2D electrophoresis; Image database; Meta-analysis; Text mining; Web application

Mesh:

Year:  2013        PMID: 23592298     DOI: 10.1002/elps.201300085

Source DB:  PubMed          Journal:  Electrophoresis        ISSN: 0173-0835            Impact factor:   3.535


  4 in total

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Authors:  Raffaele Fronza; Alessandro Vasciaveo; Alfredo Benso; Manfred Schmidt
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Review 3.  Mining biomedical images towards valuable information retrieval in biomedical and life sciences.

Authors:  Zeeshan Ahmed; Saman Zeeshan; Thomas Dandekar
Journal:  Database (Oxford)       Date:  2016-08-18       Impact factor: 3.451

4.  TilGAN: GAN for Facilitating Tumor-Infiltrating Lymphocyte Pathology Image Synthesis With Improved Image Classification.

Authors:  Monjoy Saha; Xiaoyuan Guo; Ashish Sharma
Journal:  IEEE Access       Date:  2021-05-28       Impact factor: 3.367

  4 in total

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