ArticleScientific reports2017
Use of Fibonacci numbers in lipidomics - Enumerating various classes of fatty acids.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Evaluation of Surface-Induced Dissociation Ion Mobility-Mass Spectrometry for Lipid Structural Characterization.Journal of the American Society for Mass Spectrometry · 2024Article
- New Frontiers in Lipidomics Analyses using Structurally Selective Ion Mobility-Mass Spectrometry.Trends in analytical chemistry : TRAC · 2019Article
- A New Solution Concept for the Ultimatum Game leading to the Golden Ratio.Scientific reports · 2017Article
- Golden Gait: An Optimization Theory Perspective on Human and Humanoid Walking.Frontiers in neurorobotics · 2017Article
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Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
In lipid biochemistry, a fundamental question is how the potential number of fatty acids increases with their chain length. Here, we show that it grows according to the famous Fibonacci numbers when cis/trans isomerism is neglected. Since the ratio of two consecutive Fibonacci numbers tends to the Golden section, 1.618, organisms can increase fatty acid variability approximately by that factor per carbon atom invested. Moreover, we show that, under consideration of cis/trans isomerism and/or of modification by hydroxy and/or oxo groups, diversity can be described by generalized Fibonacci numbers (e.g. Pell numbers). For the sake of easy comprehension, we deliberately build the proof on the recursive definitions of these number series. Our results should be of interest for mass spectrometry, combinatorial chemistry, synthetic biology, patent applications, use of fatty acids as biomarkers and the theory of evolution. The recursive definition of Fibonacci numbers paves the way to construct all structural formulas of fatty acids in an automated way.
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