Stochastic Fate Selection in HIV-Infected Patients | Zendy

Ariel D. Weinberger | Zendy; Leor S. Weinberger | Zendy

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Stochastic Fate Selection in HIV-Infected Patients

Author(s) -

Ariel D. Weinberger,

Leor S. Weinberger

Publication year - 2013

Publication title -

cell

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 26.304

H-Index - 776

eISSN - 1097-4172

pISSN - 0092-8674

DOI - 10.1016/j.cell.2013.09.039

Subject(s) - biology , selection (genetic algorithm) , human immunodeficiency virus (hiv) , virology , probabilistic logic , phenotype , computational biology , genetics , gene , computer science , machine learning , artificial intelligence

Classic studies proposed that stochastic variability ("noise") can drive biological fate switching, enhancing evolutionary success. Now, Ho et al. report that HIV's reactivation from dormant (latently infected) patient cells-the major barrier to an HIV cure-is inherently stochastic. Eradicating an incompletely inducible (probabilistic) viral phenotype will require inventive approaches.

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