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A new mathematical model of the structure of networks could help find new cancer drugs, speed up traffic flow and combat sexually transmitted disease.
Although the three challenges seem diverse, they all could benefit from a theory that helps to uncover unknown information about a network by analyzing its structure. The study was published in the journal Chaos.
Example - Links - Target - Cancer - Drug
An example of how filling in missing links could be useful is in choosing a genetic target for a cancer drug, said team member Michael Small, from the University of Western Australia.
"Say you have a network of genes that are somehow connected, and there are some known drug targets. But if you don't know all the genes, you would like to make guesses at information that you don't have to work out what might be other likely targets to investigate," Small said.
Link - Prediction - Types - Networks - Researchers
Successful link prediction algorithms already exist for certain types of networks, but the researchers analyzed differently structured networks to come up with their alternative algorithm.
An example of traditional link prediction might be a social network suggesting friends with which to connect. Two people who share a friend are likely to themselves be friends with a direct connection. Adding this third connection creates a triangle, which is a structure where existing algorithms focus.
Contrast - Authors
In contrast, the authors...
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