| scholarly article | Q13442814 |
| P50 | author | Sebastian Matuszewski | Q57567883 |
| Ana-Hermina Ghenu | Q57656821 | ||
| Jeffrey D. Jensen | Q40513972 | ||
| Claudia Bank | Q57548171 | ||
| P2093 | author name string | Marcel E Hildebrandt | |
| P2860 | cites work | Fitness effects of advantageous mutations in evolving Escherichia coli populations | Q22066182 |
| Experimental illumination of a fitness landscape | Q22066261 | ||
| Fitness and its role in evolutionary genetics | Q22122004 | ||
| The distribution of fitness effects of new mutations | Q22122013 | ||
| The genetic theory of adaptation: a brief history | Q22122021 | ||
| An empirical test of the mutational landscape model of adaptation using a single-stranded DNA virus | Q22122043 | ||
| The pattern of neutral molecular variation under the background selection model | Q24533194 | ||
| A Programmable Dual-RNA-Guided DNA Endonuclease in Adaptive Bacterial Immunity | Q24669850 | ||
| Optimization of affinity, specificity and function of designed influenza inhibitors using deep sequencing | Q27679309 | ||
| Comprehensive Sequence-Flux Mapping of a Levoglucosan Utilization Pathway in E. coli | Q27702148 | ||
| Systematic identification of H274Y compensatory mutations in influenza A virus neuraminidase by high-throughput screening | Q30423620 | ||
| Systematic exploration of ubiquitin sequence, E1 activation efficiency, and experimental fitness in yeast | Q30584192 | ||
| Effects of new mutations on fitness: insights from models and data | Q30828514 | ||
| A general multivariate extension of Fisher's geometrical model and the distribution of mutation fitness effects across species | Q33342879 | ||
| An approximate bayesian estimator suggests strong, recurrent selective sweeps in Drosophila | Q33370545 | ||
| What can we learn about the distribution of fitness effects of new mutations from DNA sequence data? | Q33544082 | ||
| A comprehensive, high-resolution map of a gene's fitness landscape | Q33654337 | ||
| High-resolution mapping of protein sequence-function relationships | Q33658465 | ||
| Evolution in health and medicine Sackler colloquium: Genetic architecture of a complex trait and its implications for fitness and genome-wide association studies | Q33844411 | ||
| A simple stochastic gene substitution model | Q71016135 | ||
| Bayesian analysis suggests that most amino acid replacements in Drosophila are driven by positive selection | Q34303973 | ||
| Fitness analyses of all possible point mutations for regions of genes in yeast | Q34313305 | ||
| A systematic survey of an intragenic epistatic landscape. | Q34740848 | ||
| Latent effects of Hsp90 mutants revealed at reduced expression levels | Q34795559 | ||
| Deep mutational scanning: a new style of protein science | Q35541240 | ||
| The evolutionarily stable distribution of fitness effects | Q35579831 | ||
| High-resolution sequence-function mapping of full-length proteins | Q35581370 | ||
| A method for inferring the rate of occurrence and fitness effects of advantageous mutations | Q35620399 | ||
| Distribution of mutational fitness effects and of epistasis in the 5' untranslated region of a plant RNA virus | Q35862886 | ||
| Theories of adaptation: what they do and don't say. | Q36120420 | ||
| TALENs: a widely applicable technology for targeted genome editing | Q36540717 | ||
| Analyses of the effects of all ubiquitin point mutants on yeast growth rate | Q36736277 | ||
| High-frequency genome editing using ssDNA oligonucleotides with zinc-finger nucleases | Q36744028 | ||
| Capturing the mutational landscape of the beta-lactamase TEM-1. | Q37088726 | ||
| Local fitness landscape of the green fluorescent protein | Q37142510 | ||
| High-throughput analysis of in vivo protein stability | Q37289446 | ||
| Model of effectively neutral mutations in which selective constraint is incorporated | Q37337060 | ||
| Deep mutational scanning of an RRM domain of the Saccharomyces cerevisiae poly(A)-binding protein | Q37365341 | ||
| Shifting fitness landscapes in response to altered environments. | Q37373507 | ||
| A bayesian MCMC approach to assess the complete distribution of fitness effects of new mutations: uncovering the potential for adaptive walks in challenging environments | Q37628802 | ||
| The fates of mutant lineages and the distribution of fitness effects of beneficial mutations in laboratory budding yeast populations | Q37696346 | ||
| The Utility of Fisher's Geometric Model in Evolutionary Genetics | Q38689208 | ||
| Quantifying and understanding the fitness effects of protein mutations: Laboratory versus nature | Q38787151 | ||
| A Balance between Inhibitor Binding and Substrate Processing Confers Influenza Drug Resistance | Q38812500 | ||
| The fitness landscape of a tRNA gene. | Q41787386 | ||
| The distribution of fitness effects in an uncertain world | Q41914227 | ||
| Cost of antibiotic resistance and the geometry of adaptation. | Q42113492 | ||
| Network of epistatic interactions within a yeast snoRNA. | Q42130432 | ||
| A comprehensive biophysical description of pairwise epistasis throughout an entire protein domain | Q42551296 | ||
| Comprehensive mutational scanning of a kinase in vivo reveals substrate-dependent fitness landscapes | Q42790330 | ||
| Evolution of clonal populations approaching a fitness peak. | Q43101601 | ||
| The fitness effect of mutations across environments: a survey in light of fitness landscape models. | Q51714236 | ||
| THE POPULATION GENETICS OF ADAPTATION: THE DISTRIBUTION OF FACTORS FIXED DURING ADAPTIVE EVOLUTION. | Q53762739 | ||
| The fate of competing beneficial mutations in an asexual population. | Q54262235 | ||
| Fitness effects of fixed beneficial mutations in microbial populations. | Q54541810 | ||
| P433 | issue | 1 | |
| P407 | language of work or name | English | Q1860 |
| P921 | main subject | statistics | Q12483 |
| deep mutational scanning | Q105275188 | ||
| P1104 | number of pages | 11 | |
| P304 | page(s) | 77-87 | |
| P577 | publication date | 2016-07-13 | |
| P1433 | published in | Genetics | Q3100575 |
| P1476 | title | A statistical guide to the design of deep mutational scanning experiments | |
| P478 | volume | 204 |
| Q38636539 | A statistical framework for analyzing deep mutational scanning data |
| Q36324044 | Deep mutational scanning identifies sites in influenza nucleoprotein that affect viral inhibition by MxA |
| Q92557987 | Deep2Full: Evaluating strategies for selecting the minimal mutational experiments for optimal computational predictions of deep mutational scan outcomes |
| Q93060625 | MPRAnalyze: statistical framework for massively parallel reporter assays |
| Q59049673 | Pairwise and higher-order genetic interactions during the evolution of a tRNA |
| Q90244482 | Recent insights into the genotype-phenotype relationship from massively parallel genetic assays |
| Q58914585 | The fitness landscape of the codon space across environments |
| Q38825473 | The power of multiplexed functional analysis of genetic variants. |
| Q58553921 | Unbiased Fitness Estimation of Pooled Barcode or Amplicon Sequencing Studies |
| Q45945774 | Variant Interpretation: Functional Assays to the Rescue. |
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