HIV-1 fitness landscape models for indinavir treatment pressure using observed evolution in longitudinal sequence data are predictive for treatment failure.
We previously modeled the in vivo evolution of human immunodeficiency virus-1 (HIV-1) under drug selective pressure from cross-sectional viral sequences. These fitness landscapes (FLs) were made by using first a Bayesian network (BN) to map epistatic substitutions, followed by scaling the fitness la...
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| Format: | article |
| Language: | und |
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2021
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| Online Access: | http://hdl.handle.net/10362/116960 |
| Country: | Portugal |
| Oai: | oai:run.unl.pt:10362/116960 |