Sophie Gagnon,Emmanuelle Ametepe,Floriane Point et al. Sophie Gagnon et al.

This study aims to validate TBpore, a novel bioinformatic pipeline for clustering TB transmission isolates using Oxford Nanopore Technology (ONT) data and comparing it against conventional Mycobacterial Interspersed Repetitive-Unit Variable Number (MIRU-VNTR) typing and Illumina sequencing....SNP distances were used to compare clustering results across methods, with clusters defined by SNP distance thresholds of ≤5 and ≤12. Both sequencing methods showed a high degree of concordance in clustering results....This study suggests potential increased clustering sensitivity with Nanopore technology, warranting further validation on larger datasets with robust epidemiological metadata. Copyright: © 2025 Gagnon et al.

Hailang Fan,Xiaojie Li,Yaqian Zhao et al. Hailang Fan et al.

Methods: We performed integrated multi-omics clustering of DNAme and bulk RNA-seq data from 302 paired meningioma samples. This identified molecular types characterized by distinct survival, copy number variation (CNV), immune infiltration, and pathway enrichment profiles.

Benedicto Byamukama,Asfor Amin,Frank Nobert Mwiine et al. Benedicto Byamukama et al.

FMD clustering was observed near international borders with Kenya and Tanzania and around Queen Elizabeth National Park. Identified risk factors included dry season, animal movements, proximity to borders, and pastoralism.

Zixuan Zhang,Xiaogang Lu,Meng Jin et al. Zixuan Zhang et al.

We devised a hierarchical analytical approach: (1) unsupervised pattern recognition (HCA/PCA) revealed the inherent clustering of two primary synthetic pathways, (2) oPLS-DA modeling achieved 100% classification accuracy (R2 = 0.990) with 15 VIP-discriminating features, and (3) rigorous validation through

Daniel Camillo Spona,Ketil Jørgen Haugan,Claus Graff et al. Daniel Camillo Spona et al.

K-means clustering revealed two distinct groups of patients with mostly midnight-morning [median 6 a.m. (3 a.m.-11 a.m.)] and daytime [median 12 p.m. (9 a.m.-5 p.m.)], onset respectively.

Yue-Bei Luo,Maho Nakazawa,Nham Pham Thi Minh et al. Yue-Bei Luo et al.

Keywords: Vietnamese; autoantibody; clustering analysis; cytokine; idiopathic inflammatory myopathy. © 2025 The Author(s). Muscle & Nerve published by Wiley Periodicals LLC.

Diver E Marin,Stanley B Grant,Shantanu V Bhide et al. Diver E Marin et al.

In this study, we applied principal component analysis and hierarchical clustering to identify ion covariance patterns, or "ion clusters," in Broad Run, an urban stream in the Mid-Atlantic United States.

Xuening Li,Zhuang Zhang,Siying Li et al. Xuening Li et al.

Hyaluronic acid (HA) is the main ligand for binding CD44 to modulate the targeted delivery of nanodrugs; however, the corresponding receptor clustering mechanism remains unclear. The differential effects of HA on CD44 clustering are closely associated with the number of disaccharide units....Then, the clustering effect induced by HA containing various disaccharide units was evaluated and the optimal clustering effect was verified....Furthermore, the clustering effect on cell entry dynamic parameters of HA targeting nanodrugs was assessed based on different cell lines at the single particle level....These results demonstrate that the clustering effect will enhance the entry cell efficiency of HA targeting nanodrugs, and the effect is more obvious on the cell line with low expression level of CD44....This study offers a new way to evaluate the cell membrane receptor clustering and the corresponding effect on cellular uptake, which will provide potential strategy for designing appropriate targeting nanodrugs with high delivery efficiency tailored to different cancers.

Haicheng Liu,Shikai Tong,Weiyao Zhu et al. Haicheng Liu et al.

Fuzzy logic is then employed to derive a quantitative characterization formula, while K-means clustering categorizes flow field types....Membership functions align with observed data distributions, and K-means clustering achieves a silhouette coefficient of 0.724, delineating three distinct flow field types: dominant (10.99%), weak flow field type I (52.71%), and weak flow field type II (36.29%).

Thiago Franca,Miller Lacerda,Camila Calvani et al. Thiago Franca et al.

Principal component analysis was then applied to observe clustering tendencies, and the further selection of principal components improved clustering. Using support vector machine algorithms, the predictive models achieved overall accuracies of 95.8% for dried samples and 91.7% for liquid samples.