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biological objects and features in images, particularly those obtained through [[Fluorescence microscope|fluorescence microscopy]].
 
Distributions are available for [[Microsoft Windows]], the [[classic Mac OS]], [[macOS]], and [[Linux]]. The [[source code]] for CellProfiler is freely available<ref>{{cite web |url=https://github.com/CellProfiler/CellProfiler/wiki |title=CellProfiler wiki|author=<!--Not stated--> |date= December 2016 |website=[[Github]]}}</ref>. CellProfiler is developed by the [[Broad Institute|Broad Institute's]] Imaging Platform.<ref>{{cite web |url=http://www.broadinstitute.org/science/platforms/imaging/imaging-platform |title=Imaging Platform|author=<!--Not stated--> |date= 2018 |website=[[Broad Institute]]}}</ref>
 
==Features==
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A wide variety of measurements can be generated for each identified cell or subcellular compartment, including [[Morphology (biology)|morphology]], intensity, and [[Texture (visual arts)|texture]] among others. These measurements are accessible by using built-in viewing and plotting data tools, exporting in a [[Comma-separated values|comma-delimited]] [[spreadsheet]] format,<ref>{{Cite web|url=http://d1zymp9ayga15t.cloudfront.net/CPmanual/ExportToSpreadsheet.html|title=ExportToSpreadsheet|website=d1zymp9ayga15t.cloudfront.net|access-date=2016-08-29}}</ref> or importing into a [[MySQL]] or [[SQLite]] database.<ref>{{Cite web|url=http://d1zymp9ayga15t.cloudfront.net/CPmanual/ExportToDatabase.html|title=ExportToDatabase|website=d1zymp9ayga15t.cloudfront.net|access-date=2016-08-29}}</ref>
 
CellProfiler interfaces with the high-performance scientific libraries [[NumPy]] and [[SciPy]] for many mathematical operations, the Open Microscopy Environment<ref>{{cite web |url=http://openmicroscopy.org |title=Open Microscopy Environment |author=<!--Not stated--> |access-date=2018-05-07}}</ref> Consortium’s Bio-Formats library for reading more than 100 image file formats, [[ImageJ]] for use of plugins and macros, and [[ilastik]] for pixel-based classification.<ref>{{Cite web|url=https://github.com/CellProfiler/CellProfiler/wiki/How-to-use-Pixel-Classification-in-CellProfiler|title=CellProfiler/CellProfiler|website=GitHub|access-date=2016-08-29}}</ref> While designed and optimized for large numbers of two-dimensional images (the most common high-content screening image format), CellProfiler supports analysis of small-scale experiments and [[Time-lapse microscopy|time-lapse]] movies.<ref>{{Cite journal|last=Bray|first=Mark-Anthony|last2=Carpenter|first2=Anne E.|date=2015-01-01|title=CellProfiler Tracer: exploring and validating high-throughput, time-lapse microscopy image data|journal=BMC Bioinformatics|volume=16|pages=368|doi=10.1186/s12859-015-0759-x|issn=1471-2105|pmc=4634901|pmid=26537300}}</ref>
 
==History==
CellProfiler was released in December 2005 by scientists from the [[Whitehead Institute for Biomedical Research]] and [[Massachusetts Institute of Technology]].<ref name="cp">{{Cite journal|title=What Is the Key Best Practice for Collaborating with a Computational Biologist?|url=https://dx.doi.org/10.1016/j.cels.2016.07.006|journal=Cell Systems|volume=3|issue=1|pages=7–11|doi=10.1016/j.cels.2016.07.006}}</ref> It is currently developed and maintained by the Carpenter Lab at the Imaging Platform of the [[Broad Institute]].<ref>{{cite web |url=http://www.broadinstitute.org/~anne/ |title=The Carpenter Lab |author=<!--Not stated--> |date=2018}}</ref>
 
Originally developed in [[MATLAB]],<ref name="cp" /> it was re-written in [[Python (programming language)|Python]] and released as CellProfiler 2.0 in 2010.<ref name="cp2" /> Version 3.0, supporting volumetric analysis of 3D image stacks and optional deep learning modules, was released in October 2017.<ref>{{cite web |url=https://blog.cellprofiler.org/2017/10/16/cellprofiler-3-0-release-faster-better-and-3d/ |title=CellProfiler 3.0 release: faster, better, and 3D |author=Carpenter, AE |date=2017-10-16 |website= CellProfiler Blog}}</ref>
 
==Community==