Using Google Reverse Image Search to Decipher Biological Images

Jennifer L. Mamrosh1, David D. Moore1

1 Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas
Publication Name:  Current Protocols in Molecular Biology
Unit Number:  Unit 19.13
DOI:  10.1002/0471142727.mb1913s111
Online Posting Date:  July, 2015
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Abstract

Despite the range of tasks performed by biological image‐processing software, current versions cannot find matches for the image in question among the huge range of biological images that exist in the literature and elsewhere on the Internet. Google's Reverse Image Search is designed for this, and it is a simple, yet powerful tool that can be applied to decipher the contents of biological images. For images that contain unfamiliar or unknown elements, for example, Reverse Image Search can identify similar features in published images. Here we describe general guidelines for using this freely available tool to search published images in National Center for Biotechnology Information's (NCBI's) image database. These guidelines can be applied to a variety of types of biological images, including immunohistochemistry and electron microscopy, to facilitate straightforward and rapid searches using Google's Reverse Image Search. © 2015 by John Wiley & Sons, Inc.

Keywords: image analysis; reverse image search; unknown mechanism

     
 
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Table of Contents

  • Commentary
  • Literature Cited
  • Figures
     
 
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Materials

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Literature Cited

Literature Cited
  Eliceriri, K.W., Berthold, M.R., Goldberg, I.G., Ibanez, L., Manjunath, B.S., Martone, M.E., Murphy, R.F., Peng, H., Plant, A.L., Roysam, B., Stuurman, N., Swedlow, J.R., Tomancak, P., and Carpenter, A.E. 2012. Biological imaging software tools. Nat. Methods 9:697‐710.
  White, J.F. and Estensen, R.D. 1974. Selective labilization of specific granules in polymorphonuclear leukocytes by phorbol myristate acetate. Am. J. Pathol. 75:45‐60.
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