Literature DB >> 11125130

The life sciences Global Image Database (GID).

E Gonzalez-Couto1, B Hayes, A Danckaert.   

Abstract

Although a vast amount of life sciences data is generated in the form of images, most scientists still store images on extremely diverse and often incompatible storage media, without any type of metadata structure, and thus with no standard facility with which to conduct searches or analyses. Here we present a solution to unlock the value of scientific images. The Global Image Database (GID) is a web-based (http://www.gwer.ch/qv/gid/gid.ht m ) structured central repository for scientific annotated images. The GID was designed to manage images from a wide spectrum of imaging domains ranging from microscopy to automated screening. The annotations in the GID define the source experiment of the images by describing who the authors of the experiment are, when the images were created, the biological origin of the experimental sample and how the sample was processed for visualization. A collection of experimental imaging protocols provides details of the sample preparation, and labeling, or visualization procedures. In addition, the entries in the GID reference these imaging protocols with the probe sequences or antibody names used in labeling experiments. The GID annotations are searchable by field or globally. The query results are first shown as image thumbnail previews, enabling quick browsing prior to original-sized annotated image retrieval. The development of the GID continues, aiming at facilitating the management and exchange of image data in the scientific community, and at creating new query tools for mining image data.

Mesh:

Year:  2001        PMID: 11125130      PMCID: PMC29843          DOI: 10.1093/nar/29.1.336

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  5 in total

1.  The BioImage Database Project: organizing multidimensional biological images in an object-relational database.

Authors:  J M Carazo; E H Stelzer
Journal:  J Struct Biol       Date:  1999 Apr-May       Impact factor: 2.867

2.  A framework for querying a database for structural information on 3D images of macromolecules: A web-based query-by-content prototype on the BioImage macromolecular server.

Authors:  P A de Alarcón; A Gupta; J M Carazo
Journal:  J Struct Biol       Date:  1999 Apr-May       Impact factor: 2.867

3.  Databasing the brain.

Authors:  M Chicurel
Journal:  Nature       Date:  2000-08-24       Impact factor: 49.962

4.  Automated recognition of patterns characteristic of subcellular structures in fluorescence microscopy images.

Authors:  M V Boland; M K Markey; R F Murphy
Journal:  Cytometry       Date:  1998-11-01

5.  Large-scale analysis of the yeast genome by transposon tagging and gene disruption.

Authors:  P Ross-Macdonald; P S Coelho; T Roemer; S Agarwal; A Kumar; R Jansen; K H Cheung; A Sheehan; D Symoniatis; L Umansky; M Heidtman; F K Nelson; H Iwasaki; K Hager; M Gerstein; P Miller; G S Roeder; M Snyder
Journal:  Nature       Date:  1999-11-25       Impact factor: 49.962

  5 in total

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