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Access to experimental X-ray diffraction image data is fundamental for validation and reproduction of macromolecular models and indispensable for development of structural biology processing methods. Here, we established a diffraction data publication and dissemination system, Structural Biology Data Grid (SBDG; data.sbgrid.org), to preserve primary experimental data sets that support scientific publications. Data sets are accessible to researchers through a community driven data grid, which facilitates global data access. Our analysis of a pilot collection of crystallographic data sets demonstrates that the information archived by SBDG is sufficient to reprocess data to statistics that meet or exceed the quality of the original published structures. SBDG has extended its services to the entire community and is used to develop support for other types of biomedical data sets. It is anticipated that access to the experimental data sets will enhance the paradigm shift in the community towards a much more dynamic body of continuously improving data analysis.
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http://dx.doi.org/10.1038/ncomms10882 | 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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