Social success of perfumes

Vasiliauskaite, Vaiva; Evans, T. S.

doi:10.1371/journal.pone.0218664

Cited by 7 publications

(5 citation statements)

References 29 publications

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“…In captive forest musk deer populations, we observed that, during the period when musk is formed in the males’ musk sac, it can be divided into different categories. Musk has previously been added to perfumes and cosmetics as an advanced fauna natural perfume [ 35 – 37 ]. However, abnormal musk has a bad smell that might make people feel uncomfortable and is, therefore, not qualified to be used as a perfume material ( Fig 3 ).…”

Section: Discussionmentioning

confidence: 99%

Study of compositions of musks in different types secreted by forest musk deer (Moschus berezovskii)

et al. 2021

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Musk is a secretion of the forest musk deer (Moschus berezovskii). Normal musk is a brown solid secretion with a light fragrance. In this study, abnormal types of musk, namely, white and black musks, were discovered during the musk collection process. Researchers have long been concerned with the components of musk. Herein, GC-MS, headspace solid-phase microextraction (HS-SPME), and nonmetric multidimensional scaling (NMDS) were used to analyze the nonpolar organic components, volatile organic components, and sample similarities among different musks, respectively. Abundant steroid hormones and proteins were also found in the musk. The steroid hormone concentrations were detected using a radioimmunoassay (RIA). Proteins in the samples were hydrolyzed and the amino acids concentrations were detected. The steroid hormone and amino acid concentrations in white musk were significantly lower than in normal and black musks (p<0.05). The components were subjected to NMDS analysis to understand the differences in components among different types of musk, with the results suggesting that white musk was different from normal and black musks.

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Section: Discussionmentioning

confidence: 99%

Study of compositions of musks in different types secreted by forest musk deer (Moschus berezovskii)

et al. 2021

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“…Hypergraphs and their null models might be used to analyse other data sets. Among them are association-based data (e.g., ingredient-product networks [47,48], authorship networks [49], company-directorate networks [50]) or social networks in which higher-order interactions have been shown to be prominent [51,52]. The tools in this manuscript could be used to investigate such data as hypergraphs and so reveal organisational principles beyond their pairwise interactions.…”

Section: Discussionmentioning

confidence: 99%

Hypergraphs for predicting essential genes using multiprotein complex data

Klimm

Deane

Reinert

2021

Journal of Complex Networks

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Protein–protein interactions are crucial in many biological pathways and facilitate cellular function. Investigating these interactions as a graph of pairwise interactions can help to gain a systemic understanding of cellular processes. It is known, however, that proteins interact with each other not exclusively in pairs but also in polyadic interactions and that they can form multiprotein complexes, which are stable interactions between multiple proteins. In this manuscript, we use hypergraphs to investigate multiprotein complex data. We investigate two random null models to test which hypergraph properties occur as a consequence of constraints, such as the size and the number of multiprotein complexes. We find that assortativity, the number of connected components, and clustering differ from the data to these null models. Our main finding is that projecting a hypergraph of polyadic interactions onto a graph of pairwise interactions leads to the identification of different proteins as hubs than the hypergraph. We find in our data set that the hypergraph degree is a more accurate predictor for gene essentiality than the degree in the pairwise graph. In our data set analysing a hypergraph as pairwise graph drastically changes the distribution of the local clustering coefficient. Furthermore, using a pairwise interaction representing multiprotein complex data may lead to a spurious hierarchical structure, which is not observed in the hypergraph. Hence, we illustrate that hypergraphs can be more suitable than pairwise graphs for the analysis of multiprotein complex data.

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Section: Discussionmentioning

confidence: 99%

Hypergraphs for predicting essential genes using multiprotein complex data

Klimm

Deane

Reinert

2020

Preprint

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Protein-protein interactions are crucial in many biological pathways and facilitate cellular function. Investigating these interactions as a graph of pairwise interactions can help to gain a systemic understanding of cellular processes. It is known, however, that proteins interact with each other not exclusively in pairs but also in polyadic interactions and they can form multiprotein complexes, which are stable interactions between multiple proteins. In this manuscript, we use hypergraphs to investigate multiprotein complex data. We investigate two random null models to test which hypergraph properties occur as a consequence of constraints, such as the size and the number of multiprotein complexes. We find that assortativity, the number of connected components, and clustering differ from the data to these null models. Our main finding is that projecting a hypergraph of polyadic interactions onto a graph of pairwise interactions leads to the identification of different proteins as hubs than the hypergraph. We find in our data set that the hypergraph degree is a more accurate predictor for gene-essentiality than the degree in the pairwise graph. We find that analysing a hypergraph as pairwise graph drastically changes the distribution of the local clustering coefficient. Furthermore, using a pairwise interaction representing multiprotein complex data may lead to a spurious hierarchical structure, which is not observed in the hypergraph. Hence, we illustrate that hypergraphs can be more suitable than pairwise graphs for the analysis of multiprotein complex data.

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Social success of perfumes

Cited by 7 publications

References 29 publications

Study of compositions of musks in different types secreted by forest musk deer (Moschus berezovskii)

Study of compositions of musks in different types secreted by forest musk deer (Moschus berezovskii)

Hypergraphs for predicting essential genes using multiprotein complex data

Hypergraphs for predicting essential genes using multiprotein complex data

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