Open Access Software2006CarpenteretVolume al. 7, Issue 10, Article R100 CellProfiler: image analysis software for identifying and quantifying comment cell phenotypes Anne E Carpenter*, Thouis R Jones*†, Michael R Lamprecht*, Colin Clarke*†, In Han Kang†, Ola Friman‡, David A Guertin*, Joo Han Chang*, Robert A Lindquist*, Jason Moffat*, Polina Golland† and David M Sabatini*§ reviews Addresses: *Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA. †Computer Sciences and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02142, USA. ‡Department of Radiology, Brigham and Women's Hospital, Boston, MA 02115, USA. §Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA. Correspondence: David M Sabatini. Email:
[email protected] Published: 31 October 2006 Received: 15 September 2006 Accepted: 31 October 2006 reports Genome Biology 2006, 7:R100 (doi:10.1186/gb-2006-7-10-r100) The electronic version of this article is the complete one and can be found online at http://genomebiology.com/2006/7/10/R100 © 2006 Carpenter et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. deposited research Cell<p>CellProfiler, image analysis the software first free, open-source system for flexible and high-throughput cell image analysis is described.</p> Abstract Biologists can now prepare and image thousands of samples per day using automation, enabling chemical screens and functional genomics (for example, using RNA interference). Here we describe the first free, open-source system designed for flexible, high-throughput cell image analysis, research refereed CellProfiler.