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Imaging algorithms may help cure cancer

My research is in computational biology — that's right, I get to sit in front of the computer all day, and write code or solve equations to my heart's desire. I recently was trying to explain my work to an acquaintance, who promptly responded with a, 'Oh, so you don't do any experiments and you won't be curing cancer anytime soon.' Turns out that this is not true at all. Here, I want to share a very interesting approach to the use of computation in imaging cancer cells and the insights obtained from this study.

Cancer cells are very invasive, that is, they like to move from their site of origin to other locations. Indeed, the signaling pathways involved in cell motility have a higher level of activity in cancer cells.

In a recent article in the journal Cancer Research, researchers used computational methods to reconstruct 3-D images of gliomas (a type of tumor that starts in the brain or spine). Using this technology, the group was not only able to obtain images of how the tumor developed but was also able to obtain in-depth information on how the cells were dispersed in different cell lines. In the authors' own words, the imaging and 3-D reconstruction techniques were crucial for obtaining the insight into tumor growth and this breakthrough was not possible with the previous imaging techniques.

My line of work is not in cancer research; but as I read the article and the comments it received, my conviction that experimentalists and computational scientists need to work together to achieve big breakthroughs was only reaffirmed. Together, we just might cure cancer sooner rather than later.

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