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Standard workflows for analyzing microbiomes often include the creation and curation of phylogenetic trees. Here we present EMPress, an interactive web tool for visualizing trees in the context of microbiome, metabolome, and other community data scalable to trees with well over 500,000 nodes. EMPress provides novel functionality-including ordination integration and animations-alongside many standard tree visualization features and thus simplifies exploratory analyses of many forms of 'omic data. Phylogenetic trees are integral data structures for the analysis of microbial communities. Recent work has also shown the utility of trees constructed from certain metabolomic data sets, further highlighting their importance in microbiome research. The ever-growing scale of modern microbiome surveys has led to numerous challenges in visualizing these data. In this paper we used five diverse data sets to showcase the versatility and scalability of EMPress, an interactive web visualization tool. EMPress addresses the growing need for exploratory analysis tools that can accommodate large, complex multi-omic data sets.
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http://dx.doi.org/10.1128/mSystems.01216-20 | DOI Listing |
Psychopharmacology (Berl)
September 2025
Institute of Cardiovascular Research, Sleep Medical Center, Department of Psychiatry, Fundamental and Clinical Research on Mental Disorders Key Laboratory of Luzhou, Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan Province, 646000, China.
Rationale: Genome-wide association studies (GWASs) are used to identify genetic variants for association with schizophrenia (SCZ) risk; however, each GWAS can only reveal a small fraction of this association.
Objectives: This study systematically analyzed multiple GWAS data sets to identify gene subnetwork and pathways associated with SCZ.
Methods: We identified gene subnetwork using dmGWAS program by combining SCZ GWASs and a human interaction network, performed gene-set analysis to test the association of gene subnetwork with clinical symptom scores and disease state, meanwhile, conducted spatiotemporal and tissue-specific expression patterns and cell-type-specific analysis of genes in the subnetwork.
mBio
September 2025
APC Microbiome Ireland, Biosciences Institute, Biosciences Research Institute, University College, Cork, Ireland.
Bacteriocins are antimicrobial peptides/proteins that can have narrow or broad inhibitory spectra and remarkable potency against clinically relevant pathogens. One such bacteriocin that is extensively used in the food industry and with potential for biotherapeutic application is the post-translationally modified peptide, nisin. Recent studies have shown the impact of nisin on the gastrointestinal microbiome, but relatively little is known of how abundant nisin production is in nature, the breadth of existing variants, and their antimicrobial potency.
View Article and Find Full Text PDFJ Chem Theory Comput
September 2025
Department of Materials Science and Engineering, City University of Hong Kong, Kowloon 999077, Hong Kong China.
Coarse-grained (CG) lipid models enable efficient simulations of large-scale membrane events. However, achieving both speed and atomic-level accuracy remains challenging. Graph neural networks (GNNs) trained on all-atom (AA) simulations can serve as CG force fields, which have demonstrated success in CG simulations of proteins.
View Article and Find Full Text PDFActa Crystallogr D Struct Biol
October 2025
Turkish Accelerator and Radiation Laboratory, 06830 Ankara, Türkiye.
Membrane-protein quality control in Escherichia coli involves coordinated actions of the AAA+ protease FtsH, the insertase YidC and the regulatory complex HflKC. These systems maintain proteostasis by facilitating membrane-protein insertion, folding and degradation. To gain structural insights into a putative complex formed by FtsH and YidC, we performed single-particle cryogenic electron microscopy on detergent-solubilized membrane samples, from which FtsH and YidC were purified using Ni-NTA affinity and size-exclusion chromatography.
View Article and Find Full Text PDFJ Appl Stat
February 2025
Department of Mathematics & Statistics, International Islamic University, Islamabad, Pakistan.
Adaptive cluster sampling is particularly helpful whenever the target population is unique, dispersed unevenly, concealed or difficult to find. In the current investigation, under an adaptive cluster sampling approach, we propose a ratio-product-logarithmic type estimator employing a single auxiliary variable for the estimation of finite population variance. The bias and mean square error of the proposed estimator are developed by using simulation as well as real data sets.
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