title: ImageJ macros for the user-friendly analysis of soft-agar and wound-healing assays.
abstract: 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.
authors.affiliation: Laboratory of Experimental Genetics, General Biology Department - ICB, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
authors.forename: João Paulo Silva
authors.initials: JPS
authors.lastname: Nunes
authors.affiliation: Laboratory of Experimental Genetics, General Biology Department - ICB, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
authors.forename: Adriana Abalen Martins
authors.initials: AAM
authors.lastname: Dias
mesh_terms: D000362:Agar / Q000737:chemistry; D000465:Algorithms; D045744:Cell Line, Tumor; D057166:High-Throughput Screening Assays; D006801:Humans; D007091:Image Processing, Computer-Assisted; D009369:Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D012984:Software; D014945:Wound Healing
chemical_list: D000362:Agar
keywords: ImageJ; cancer; macro; soft-agar; wound-healing