Probabilistic data networks

Human mobility influences the spatial distribution of infectious diseases such as HIV. Here, the authors use call data records from mobile phones to model HIV networks in Namibia and estimate that ~40% of the risk of HIV acquisition is driven by mobility.

Our understanding of the function of many transcripts is still incomplete, limiting the interpretability of transcriptomic data. Here the authors use consensus-independent component analysis, together with a guilt-by-association approach, to improve the prediction of gene function.

Individuals seeking post-exposure prophylaxis (PEP) for HIV may represent an important risk group for future HIV infection. Here the authors find HIV infections at long-term follow-up in 22 of 348 men who have sex with men, and 0 of 623 other PEP seekers.