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Everything about Truncation selection
Method of selection in selective breeding
Truncation selection is a selection method in selective breeding and in evolutionary algorithms from computer science, which selects a certain share of fittest individuals from a population for reproduction in the next generation. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Truncation selectionA 5-minute orientation
- Skim a recent paper: Selection and truncation of aptamers as fluorescence sensing platforms for selective and sensitive detection of nitrofurazoneInfluential work since 2022
- Pick up a classic book: Loss ModelsThe most-reprinted book on the subject
- Read the landmark paper: Efficiency of truncation selectionCited 147 times
- Go sideways: Tournament selectionA closely related topic
- Go sideways: Selection (evolutionary algorithm)A closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Efficiency of truncation selection
Accuracy Loss Due to Selection Bias in Cohort Studies with Left Truncation
Theoretical Consequences of Truncation Selection Based on the Individual Phenotype
Truncation, Randomization, and Selection
Truncation of the TPR domain of OGT alters substrate and glycosite selection
Prediction of Genetic Response to Truncation Selection Across Generations
Truncation Number Selection of Harmonic State-Space Model Based on the Floquet Characteristic Exponent
Negative selection pressure against premature protein truncation is reduced by alternative splicing and diploidy
🆕 Influential since 2022
Selection and truncation of aptamers as fluorescence sensing platforms for selective and sensitive detection of nitrofurazone
Selection, truncation and fluorescence polarization based aptasensor for Weissella viridescens detection
A selection criterion of small load truncation level based on the principle of same distribution of fatigue life
Reliable truncation parameter selection and model order estimation for stochastic subspace identification
Robust Automated Truncation Point Selection for Molecular Simulations
📚 Books worth reading
Loss ModelsStuart A. Klugman · 2009
Introduction to econometricsG. S. Maddala, Kajal Lahiri · 1988
Linux System ProgrammingRobert Love · 2007
TCP/IP IllustratedW. Richard Stevens, Kevin R. Fall · 1993
Neuro-fuzzy and soft computingJyh-Shing Roger Jang, Chuen-Tsai Sun · 1996
Power System Coherency and Model ReductionJoe H. Chow · 2013
Dionysian ShawMichel W. Pharand · 2004
Programming Game AI by ExampleMat Buckland · 2004
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
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