R
Rasmus Nielsen
Researcher at University of California, Berkeley
Publications - 594
Citations - 96106
Rasmus Nielsen is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Population & Selection (genetic algorithm). The author has an hindex of 135, co-authored 556 publications receiving 84898 citations. Previous affiliations of Rasmus Nielsen include National Research University – Higher School of Economics & Griffith University.
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Single-locus tests of microsatellite evolution: multi-step mutations and constraints on allele size.
Rasmus Nielsen,Per J. Palsbøll +1 more
TL;DR: Simulation procedures as well as a recently developed likelihood method used for testing hypotheses regarding microsatellite evolution revealed that the tests for the detection of multi-step mutations in general have some power, whereas Tests for the presence of constraints on the repeat number have only very limited power.
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Bayesian estimation of the number of inversions in the history of two chromosomes.
TL;DR: A Bayesian approach to the problem of inferring the history of inversion separating homologous chromosomes from two different species shows that the most likely number of inversions in some cases is considerably larger than estimates obtained based on the parsimony inferred number ofInversions.
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CHecklist for statistical Assessment of Medical Papers: the CHAMP statement
Mohammad Ali Mansournia,Gary S. Collins,Rasmus Nielsen,Maryam Nazemipour,Nicholas P. Jewell,Douglas G. Altman,Michael J. Campbell +6 more
TL;DR: Despite efforts to improve the statistical quality of research articles in medical journals, serious statistical errors or deficiencies in the design, analysis, reporting and interpretation still occur, even in highly ranked journals as discussed by the authors.
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Do Aquaculture Farmers Have an Incentive to Maintain Good Water Quality? The Case of Small-Scale Shrimp Farming in Indonesia
TL;DR: In this article, the authors analyzed the incentives for farmers to maintain good water quality by identifying whether technical efficiency increases with improved water quality, which may also positively affect the surrounding environment, reducing the risk of eutrophication in downstream river systems.
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Validity of Self-Reported Running Distance.
TL;DR: The mean running distance (km) is similar between self-reporting and GPS measurements, however, researchers should consider using GPS measurements in favor of subjective reporting of running distance because of considerable variation on an individual level.