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ImageJ macros for the user-friendly analysis of soft-agar and wound-healing assays
Author(s) -
João Paulo Silva Nunes,
Adriana Abalen Martins Dias
Publication year - 2017
Publication title -
biotechniques
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.617
H-Index - 131
eISSN - 1940-9818
pISSN - 0736-6205
DOI - 10.2144/000114535
Subject(s) - computer science , macro , robustness (evolution) , software , data mining , artificial intelligence , computational biology , biology , operating system , programming language , biochemistry , gene
Recent advances in biological imaging techniques and the enormous amount of data they generate call for the development of computational tools for efficient and reliable high-throughput analysis. Several software applications with this functionality are available, and one of the most commonly used is ImageJ. Here, we present two independent macros (WH_NJ and SA_NJ) for automating and facilitating the analysis of images acquired from two in vitro assays frequently used in cancer studies and drug screening: the wound-healing and soft-agar assays. These two algorithms combine, in a single command, the steps required for the individual analysis of each image using ImageJ. WH_NJ and SA_NJ allow fast, reproducible data analysis without the experimental bias inherent in manual analyses, thus guaranteeing the robustness and reliability of the results.

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