The tools that are used to study the data of social networking sites like Facebook and Twitter can also be used to identify the biomarkers in our bodies for diseases, including different types of cancer.
For the study, the researchers from Turkey viewed genes as actors or members of the social network and similarities between different genes were considered to be the connections between these actors. The team has demonstrated that their approach is effective in identifying biomarkers of three types of cancer: lymphoma, colon cancer and leukemia.
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"We showed how our approach is capable of effectively detecting cancer biomarkers out of high-dimensional genomic data," wrote Taylan Iyidogan and colleagues from TOBB University, in Ankara, Turkey.
Genomic databases can be vast, given that the human genome comprises some 20,000 genes, and so such an approach can, they suggest, dramatically decrease the number of features that must be analyzed to find useful biomarkers.
![3D Digital Breast Imaging Could Revolutionize Cancer Screening]( "3D Digital Breast Imaging Could Revolutionize Cancer Screening")
In community-based radiology practice, mammography screening with 3D digital breast tomosynthesis (DBT) yielded an increased overall cancer detection rate, lower recall rates and an increased detection rate for invasive cancer compared with 2D digital mammography (DM).
Once identified and understood, such biomarkers can then be tested for in screening programs for people at risk of a given disease or for diagnosis should they present with particular symptoms. "We combined clustering and classification into the developed framework to help in detecting the links between the various genes within the model and to validate the outcome, respectively," the researchers said.
The research was published in International Journal of Data Mining.
Source: IANS
3D Digital Breast Imaging Could Revolutionize Cancer Screening
In community-based radiology practice, mammography screening with 3D digital breast tomosynthesis (DBT) yielded an increased overall cancer detection rate, lower recall rates and an increased detection rate for invasive cancer compared with 2D digital mammography (DM).
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Once identified and understood, such biomarkers can then be tested for in screening programs for people at risk of a given disease or for diagnosis should they present with particular symptoms. "We combined clustering and classification into the developed framework to help in detecting the links between the various genes within the model and to validate the outcome, respectively," the researchers said.
The research was published in International Journal of Data Mining.
Source: IANS
People Usually Quit Smoking When Celebs Promote Cancer Screening
A new study suggests that while the start of a new year looks like a promising way to start off on a clean slate by quitting bad habits, it may not be as much of a powerful motivator as the motivation of a celebrity.
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