![]() In an effort to make software user-friendly, vendors have now started providing default options that may or may not apply to your dataset. Q: Do you think software tools have now become user-friendly enough to be used by biologists without much computational training?Ī: Rao: I think there is such a thing as being too user-friendly. You don’t necessarily need to work with an expert, unless it’s a particularly challenging problem. There are also online Q&A forums and e-mail lists for various software packages where you can get advice from people. Particularly in microscopy, one can always tell whether the software is doing a good job in identifying cells. With the large number of experiments being done, image analysis software can help save the timespent looking at the images, and it also lends a higher degree of accuracy and objectiveness to the analysis of the data.Īnother change is that, with the software tools becoming very user-friendly, a biologist can try and get started with image analysis on his or her own. While previously microscopy experiments were done on glass slides, now they are often done in multi-well plates in order to test multiple replicates, time points, and perturbations. ![]() Q: What changes do you expect to see going forward?Ī: Carpenter: The scale of experiments has and will continue to increase. Image analysis software has also matured in this timespan, making it feasible for any biologist, no matter their computational expertise, to quantify various types of images. In the past decade, it’s become common to quantify the images from microscopy, especially when publishing your data. You would choose a single, representative image from your experiments to publish in your paper, and that was the end of the story. Twenty years ago, when I was a student, microscopy images were used in a very qualitative way. Q: What kinds of changes have you seen in image analysis tools in recent years?Ī: Carpenter: Microscopy has been prevalent in a lot of different fields and extremely widespread across different types of labs for decades. ![]() At MD Anderson, he is working on using image analysis and machine learning methods to link image-derived phenotypes with genetic data across biological scale (i.e., single-cell, tissue, and radiology data).īy subscribing, you agree to receive email related to Lab Manager content and products. Rao received his PhD in electrical engineering and bioinformatics from the University of Michigan, specializing in transcriptional genomics. Prior to joining MD Anderson, he was a Lane Postdoctoral Fellow at Carnegie Mellon University, specializing in bioimage informatics. Arvind Rao has been an assistant professor in the Department of Bioinformatics and Computational Biology at the University of Texas MD Anderson Cancer Center since 2011. Carpenter received her PhD in cell biology from the University of Illinois, Urbana-Champaign, and completed her postdoctoral fellowship at the Whitehead Institute for Biomedical Research at MIT.ĭr. She collaborates with dozens of biomedical research groups around the world to help identify disease states, potential therapeutics, and gene function from microscopy images. Anne Carpenter leads the Imaging Platform at the Broad Institute of Harvard and MIT-a team of biologists and computer scientists who develop image analysis and data mining methods and software that are freely available to the public through the open-source CellProfiler project.
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