title: Using Google Reverse Image Search to Decipher Biological Images.
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.
authors.affiliation: Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas.
authors.forename: Jennifer L
authors.initials: JL
authors.lastname: Mamrosh
authors.affiliation: Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas.
authors.forename: David D
authors.initials: DD
authors.lastname: Moore
mesh_terms: D019295:Computational Biology / Q000379:methods*; D016206:Databases, Bibliographic; D016208:Databases, Factual; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D057386:Search Engine / Q000379:methods*
keywords: image analysis; reverse image search; unknown mechanism