Science Daily September 28, 2021 Researchers in the UK developed machine learning models that identify candidate zoonoses solely using signatures of host range encoded in viral genomes. Within a dataset of 861 viral species with known zoonotic status, their approach outperformed models based on the phylogenetic relatedness of viruses to known human-infecting viruses distinguishing high-risk viruses within families that contain a minority of human-infecting species. The model predictions suggested the existence of generalizable features of viral genomes that are independent of virus taxonomic relationships and that may preadapt viruses to infect humans. Their model reduced a second set of 645 […]
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Solution to century-old math problem could predict transmission of infectious diseases
Science Daily May 29, 2020 The diffusion equation models random movement and is one of the fundamental equations of physics. The analytic solution of the diffusion equation in finite domains, when time and space is continuous, has been known for a long time. However, the diffusion equation in finite space was not solved until now. Researchers in the UK used Chebyshev polynomials, and the method of images which is used to tackle electrostatic problems to construct the solution to the discrete diffusion equation in higher dimension from the one in lower dimensions. The solution could be used to accurately predict […]
Predicting terror activity before it happens
Science Daily October 7, 2019 Researchers at Northwestern University developed an early-warning model that predicts the future lethality of a group using only a handful of events that occur soon after it emerges. Using the first 10 to 20 attacks or the first 10 to 20% of a group’s lifetime, the model provides about 60% of the explanatory power as would having a group’s complete lifetime data. They considered terror organizations like a business whose product is lethality and predict their success in producing that product based on the diversity of weapons, their sophistication and attack capabilities. Using publicly available […]