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About 10,000 papers for “Dendrogram”

Dendrogram

Rogério Galante Negri · Encyclopedia of earth sciences series/Encyclopedia of earth sciences · 2023

Cited by 0

Dendrogram

Herry Riswandi · Figshare · 2018

Dendrogram of a hydrochemical cluster generated by hierarchical cluster analysis.

Cited by 0Open access

Dendrogram

University Research Chair · Encyclopedia of Database Systems · 2009

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Dendrogram.

Matthias Weger (2550757), Hermann Wagner (57832) · Figshare · 2016

Dendrograms were separately created for the different measurement positions based on the unweighted average distance and using the Euclidean distance metric at the corresponding position. The values next to the branches represent the distance between data points. (A): 0.2 of vane. (B): 0.4 of vane. (C) 0.6 of vane. Note that in (B) and (C) the diurnal species are clustered separately from the diurnal species, while in (A) the biggest species, B. bubo is clustered separately, while the remaining 6 species are clustered according to their activity pattern.

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dendrogram

2024

Citation: 'dendrogram' in the IUPAC Compendium of Chemical Terminology, 5th ed.; International Union of Pure and Applied Chemistry; 2025. Online version 5.0.0, 2025. 10.1351/goldbook.10122 • License: The IUPAC Gold Book is licensed under Creative Commons Attribution-ShareAlike CC BY-SA 4.0 International for individual terms. Requests for commercial usage of the compendium should be directed to IUPAC.

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Dendrogram

Rogério Galante Negri · Encyclopedia of earth sciences series/Encyclopedia of earth sciences · 2022

Cited by 5

Dendrogram.

Remziye Akarsu (19964507), Gonca Bumin (6692084), Yusuf Celik (19964510) · Figshare · 2024

<div>Early literacy skills, the foundational abilities necessary for the development of literacy, must be examined holistically in preschool children. This study aimed to investigate early literacy skills in preschool children and determine how variables related to literacy development can be clustered by using a dendrogram. The study was conducted on 166 preschool children (75 female, 91 male; mean age: 65.9±4.4 months). Hierarchical cluster analysis (CA) was used to find the variable clustering trends. The 44 variables related to literacy (sociodemographic factors related to the child and family, child–parent relationship, child’s behavior, and social, sensory integration, motor, and auditory linguistic skills) that were closest to each other in the dendrogram were clustered, and the situation was summarized by reducing them to two main clusters and six sub-clusters. This study elaborates on the implications of reducing multivariate complexity using CA. It is recommended that the relationships among the variables in this dendrogram structure are considered when new hypotheses and studies related to early literacy are designed.</div>

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dendrogram

The SAGE Dictionary of Statistics · 2004

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Dendrogram.

Wendi D. Roe (6325805), Baukje Lenting (6325808), Anna Kokosinska (6325811) et al. · Figshare · 2019

Nine variable number tandem repeat and two direct repeat loci were used to compare Mycobacterium pinnipedii strains isolated from cattle and pinnipeds in New Zealand with selected M. pinnipedii isolates from Australian pinnipeds and selected M. bovis isolates from New Zealand cattle.

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Dendrogram.

Maroua Jerbi (9606727), Sonia Labidi (9606730), Anissa Lounès-Hadj Sahraoui (9606733) et al. · Figshare · 2020

Cited by 0Open access

Dendrogram

Herry Riswandi · Figshare · 2018

Dendrogram of a hydrochemical cluster generated by hierarchical cluster analysis.

Cited by 0Open access

Dendrogram.

Dustin H. Ranglack (837945), Lauren K. Dobson (837946), Johan T. du Toit (837947) et al. · Figshare · 2015

Unrooted tree diagram with maximum likelihood scores comparing Henry Mountain bison samples to 8 US federal herds using 40 polymorphic loci. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0144239#pone.0144239.g002" target="_blank">Fig 2</a> for herd name abbreviations.

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Cluster dendrogram.

Dorota Formanowicz (3808495), Marcin Radom (3808504), Piotr Zawierucha (3808498) et al. · Figshare · 2017

Cited by 0Open access

Cluster dendrogram.

Julien Noble (22170708), Antoine Jardin (22170711) · Figshare · 2025

<div> Hundreds of studies have been published on fear of crime, but few models offer a unified framework for this social phenomenon. This is the ambition of the model of experiential and expressive fear of crime (EEF) developed in the mid-2000s by a team of British researchers. However, despite its numerous contributions, this original model faces two limitations. First, the different versions of the model present certain discrepancies. Second, the statistical methods used consistently rely on hypothetico-deductive reasoning, which may overlook the existence of certain combinations of variables. The objective of this article, based on a French piece of research, is to revisit this model by combining two different families of statistical methods: multivariate configuration analysis and logistic regression analysis. The first analysis attempts to overcome these two limitations by adopting an inductive approach, which involves studying the multidimensional structure of the data without imposing predefined structures on them. It identifies four classes of respondents, each associated with a specific relationship to experiential fear and expressive fear. If the ‘unworried’ and the ‘worried-dysfunctional’ associate these two dimensions of fear of crime, the ‘anxious’ and the ‘worried-functional’ clearly separate them. By adopting an inferential approach, the second analysis aims to determine the sociodemographic factors of these different groups. It shows that the predictors vary significantly from one group to another and that no variable (not even gender) is a predictor for all groups. These results encourage moving beyond the dichotomous conceptualization (‘worried’/ ‘unworried’), which is still widely used in the study of fear of crime. Systematically identifying these different groups could also help combat fear of crime more effectively by implementing targeted and adapted public policies. </div>

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Cluster dendrogram.

Eugenia Radulescu (319733), Qiang Chen (114038), Giulio Pergola (349304) et al. · Figshare · 2023

Correspondence between co-expression networks calculated after adjusting the expression data to protect/ preserve, or remove variance explained by effects of genomic scores. Legend: N = number of modules from each network, grey = genes not assigned to modules; prot = protected or preserved; rm = removed. (TIF)

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Cluster Dendrogram.

Zahra Zinati (12068304), Leyla Nazari (21772273) · Figshare · 2025

The dendrogram branches represent different gene clusters, color-coded to indicate distinct gene modules. The y-axis denotes height, reflecting the level of dissimilarity between clusters. The Dynamic Tree Cut method and Merged dynamic were used to identify and merge modules.

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Dendrogram Topology

J. B. Phipps · Systematic Zoology · 1971

<it>Phipps, J. B. (Dept. Plant Sciences, Univ. Western Ontario, London, Ont.) Dendrogram Topology. Syst. Zool., 20:306–308</it>.—The term ‘dendrogram topology’ is defined as the branching pattern relationship among individuals in a dendrogram. An example developed in the text indicates that it is a useful concept in comparing classifications.

Cited by 40

Dendrogram analysis.

Yan Jin (143500), Chunhong Shao (709659), Jian Li (41607) et al. · Figshare · 2015

Dendrogram generated with the Fingerprinting II Informatix software package (Bio-Rad Laboratories, Hercules, CA) showing the relatedness of fingerprints (XbaI-PFGE) for 21 K. pneumoniae. The phylogenetic tree was constructed using the Dice coefficient and UPGMA clustering. A genetic similarity index scale is shown in the left of the dendrogram. PFGE types, strain number, collection data and wards distribution information are included along each PFGE lane. No., number

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