ArticleGenetica2023
Methods for two nonstandard problems arising from the Luria-Delbrück experiment.
Article in Genetica, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- The unique role ofmBio · 2026Article
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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The fluctuation experiment, devised by Luria and Delbrück in 1943, remains the method of choice for measuring microbial mutation rates in the laboratory. While most inference problems commonly encountered in a fluctuation experiment can be tackled by existing standard algorithms, investigators from time to time run into nonstandard problems not amenable to any existing algorithms. A major obstacle to solving these nonstandard problems is the construction of confidence intervals for mutation rates. This note describes methods for two important categories of nonstandard problems, namely, pooling data from separate experiments and analyzing grouped mutant count data, focusing on the construction of likelihood ratio confidence intervals. In addition to illustrative examples using real-world data, simulation results are presented to help assess the proposed methods.
Indexed as
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.