Titre : Caulobacteraceae

Caulobacteraceae : Questions médicales fréquentes

Nom anglais: Caulobacteraceae

Descriptor UI: D042063

Tree Number: B03.660.050.090

Termes MeSH sélectionnés :

Cluster Analysis

Questions fréquentes et termes MeSH associés

Général 1

#1

Erreur lors de la génération.

Veuillez réessayer ultérieurement.
Caulobacteraceae
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Dr Olivier Menir

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Expert en Médecine, Optimisation des Parcours de Soins et Révision Médicale

Validation scientifique effectuée le 13/02/2025

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Sous-catégories

2 au total
└─

Caulobacter

Caulobacter D016934 - B03.660.050.090.100
└─└─

Caulobacter crescentus

Caulobacter crescentus D016935 - B03.660.050.090.100.100

Auteurs principaux

Xiaojun Yang

1 publication dans cette catégorie

Affiliations :
  • College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Publications dans "Caulobacteraceae" :

Yuanping Li

1 publication dans cette catégorie

Affiliations :
  • Institute of Environmental Microbiology, College of Resources and Environment, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Publications dans "Caulobacteraceae" :

Renwei Feng

1 publication dans cette catégorie

Affiliations :
  • Institute of Environmental Microbiology, College of Resources and Environment, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Publications dans "Caulobacteraceae" :

Jian Chen

1 publication dans cette catégorie

Affiliations :
  • Department of Cellular Biology and Pharmacology, Herbert Wertheim College of Medicine, Florida International University, Miami, FL 33199, USA.
Publications dans "Caulobacteraceae" :

Hend A Alwathnani

1 publication dans cette catégorie

Affiliations :
  • Department of Botany and Microbiology, College of Science, King Saud University, Riyadh 11451, Saudi Arabia.
Publications dans "Caulobacteraceae" :

Weifeng Xu

1 publication dans cette catégorie

Affiliations :
  • Joint International Research Laboratory of Water and Nutrient in Crop, College of Resources and Environment, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Publications dans "Caulobacteraceae" :

Christopher Rensing

1 publication dans cette catégorie

Affiliations :
  • Institute of Environmental Microbiology, College of Resources and Environment, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Publications dans "Caulobacteraceae" :

Sources (10000 au total)

Cluster analysis for symptomatic management of

2022
DOI: 10.3389/fpubh.2022.1005481 PMID: 36466460

This study aimed to perform a cluster analysis of symptoms linked with... From 15 April to 16 May 2018, a cross-sectional study was conducted, and patients attending sexually transmitted infections (STI) related clinics were recruited from 22 medical institutions in six dis... A structured questionnaire was used to collect social-demographic information as well as STI symptoms, and urine samples were collected for nucleic acid detection. Cluster analysis and logistic regres... Among 8,207 participants, the prevalence of CT and NG infection was 9.04% (742/8,207) and 2.36% (194/8,207), respectively. Among male outpatients, four clusters with distinct symptomatic patterns were... The cluster of symptoms integrated into risk assessment for CT and NG infections suggests a new strategy of symptomatic management. Healthcare providers in STI clinics and resource-limited places may ...

Humans Female Male Chlamydia trachomatis Neisseria gonorrhoeae +5 autres

Statistical power for cluster analysis.

31 May 2022
DOI: 10.1186/s12859-022-04675-1 PMID: 35641905

Cluster algorithms are gaining in popularity in biomedical research due to their compelling ability to identify discrete subgroups in data, and their increasing accessibility in mainstream software. W... We found that clustering outcomes were driven by large effect sizes or the accumulation of many smaller effects across features, and were mostly unaffected by differences in covariance structure. Suff... Traditional intuitions about statistical power only partially apply to cluster analysis: increasing the number of participants above a sufficient sample size did not improve power, but effect size was...

Algorithms Cluster Analysis Humans Normal Distribution Sample Size +1 autres

Cluster randomised trials with a binary outcome and a small number of clusters: comparison of individual and cluster level analysis method.

12 08 2022
DOI: 10.1186/s12874-022-01699-2 PMID: 35962318

Cluster randomised trials (CRTs) are often designed with a small number of clusters, but it is not clear which analysis methods are optimal when the outcome is binary. This simulation study aimed to d... Unweighted CL, GLMM pseudolikelihood, and Fay-and-Graubard GEE with independent or exchangeable working correlation matrix controlled type-one error in > 97% scenarios with clusters minus parameters D... We recommend that CRTs with ≤ 30 clusters and a binary outcome use an unweighted CL or restricted pseudolikelihood GLMM both with DoF clusters minus cluster-level parameters....

Cluster Analysis Computer Simulation Humans Linear Models Randomized Controlled Trials as Topic +1 autres