A systems analysis of mutational effects in HIV-1 protease and reverse transcriptase
By Trevor Hinkley, Joao Martins, Colombe Chappey, Mojgan Haddad, Eric W. Stawiski, Jeannette M. Whitcomb, Christos J. Petropoulos, Sebastian Bonhoeffer. 2011
184 citations recorded by the source corpus.
Subfields: Emergency Medicine, Infectious Diseases, Virology
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In Infectious Diseases
Citations in the corpus
- Deep mutational scanning of an RRM domain of the Saccharomyces cerevisiae poly(A)-binding protein (2013, background): “Specific residues and mutations serve as hot spots for epistatic interaction (Hinkley et al. 2011; Araya et al. 2012).”
- Inferring the shape of global epistasis (2018, background): “One obvious way to incorporate epistasis into this additive model is by including explicit terms for interactions between each pair of sites and possibly higher-order interactions as well (7, 8).”
- Inferring fitness landscapes by regression produces biased estimates of epistasis (2014, methodology): “(49) used a form of penalized linear regression to avoid overfitting their data.”
- Enrich: software for analysis of protein function by enrichment and depletion of variants (2011, background): “Enrich includes detailed documentation as well as a small example dataset.”
- A fundamental protein property, thermodynamic stability, revealed solely from large-scale measurements of protein function (2012, background): “Recently, a large-scale analysis of epistasis in the HIV protease described a geographic enrichment of epistasis (27).”
- Pervasive pairwise intragenic epistasis among sequential mutations in TEM-1 β-lactamase (2019, background): “For example, examination of the fitness effects of multiple mutations from ancestral sequences of Hsp90 [9], and computational prediction epistatic effects from large fitness datasets for naturally-occurring mutations HIV-1 protease and reverse transcriptase [10] provide evidence that epistasis shap”
- Adaptation in protein fitness landscapes is facilitated by indirect paths (2016, methodology): “To impute the fitness of these missing variants, we performed regularized 584 regression on fitness values of observed variants using the following model [40, 55]: 585”