Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
We present O-SNAP (Objective Single-Molecule Nuclear Architecture Profiler), a comprehensive pipeline for the automated extraction, comparison, and classification of nuclear features from single-molecule localization microscopy (SMLM) data. O-SNAP quantifies 144 interpretable, biologically grounded spatial features describing chromatin organization or histone mark distributions at nanoscale resolution. The pipeline includes modules for pairwise comparison of features using volcano plots, feature set enrichment analysis, robust feature selection and classification of cell states, and pseudotime trajectory inference. We validate O-SNAP across diverse biological contexts, including fibroblast-to-stem cell reprogramming, tendon disease, histone variant sensitivity to oxidative stress, and chondrocyte de-differentiation, demonstrating its ability to detect subtle changes in nanoscale chromatin organization across diverse biological transitions.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12330546 | PMC |
| http://dx.doi.org/10.1101/2025.07.18.665612 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Comparison of Diagnostic Accuracies of Radiomics and Non-radiomics Model for Preoperative Prediction of Macrotrabecular-Massive Hepatocellular Carcinoma: A Systematic Review and Meta-analysis.
Acad Radiol
September 2025
Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China. Electronic address:
Rationale And Objectives: The diagnostic value of traditional imaging methods and radiomics in predicting macrotrabecular-massive hepatocellular carcinoma (MTM HCC) is yet to be ascertained. Therefore, this meta-analysis aims to compare the diagnostic performance of radiomics and conventional imaging techniques for MTM HCC.
Materials And Methods: Comprehensive publications were searched in PubMed, Embase, Web of Science, and Cochrane Library up to 28 February 2025.
Reduced model aided fluid-structure interaction design framework for shunt systems.
Med Eng Phys
October 2025
Department of Engineering Science, University of Oxford, United Kingdom. Electronic address:
Traditionally, clinical devices are designed, tested and improved through lengthy and expensive laboratory experiments and clinical trials [1]. More recently, computational methods have allowed for rapid testing, speeding up the design process and enabling far more complete searches of design space. While computational models cannot fully capture the complexities of biological systems, they provide valuable insights into crucial underlying mechanisms, such as the effects of fluid-structure interactions (FSIs).
View Article and Find Full Text PDFANASFV: a workflow for African swine fever virus whole-genome analysis.
Microb Genom
September 2025
Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, PR China.
African swine fever virus (ASFV) is highly transmissible and can cause up to 100% mortality in pigs. The virus has spread across most regions of Asia and Europe, resulting in the deaths of millions of pigs. A deep understanding of the genetic diversity and evolutionary dynamics of ASFV is necessary to effectively manage outbreaks.
View Article and Find Full Text PDFMITE Annotation and Landscape in 207 Plant Genomes Reveal Their Evolutionary Dynamics and Functional Roles.
Mol Ecol Resour
September 2025
College of Life Sciences, Henan Normal University, Xinxiang, China.
Miniature inverted-repeat transposable elements (MITEs) are short, non-autonomous class II transposable elements prevalent in eukaryotic genomes, contributing to various genomic and genic functions in plants. However, research on MITEs mainly targets a few species, limiting a comprehensive understanding and systematic comparison of MITEs in plants. Here, we developed a highly sensitive MITE annotation pipeline with a low false positive rate and applied it to 207 high-quality plant genomes.
View Article and Find Full Text PDFDeveloping a Spatiotemporal Repository of Extreme Heat and Cold Exposure in the United States for Precision Public Health Research.
Environ Sci Technol
September 2025
Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck St, Boston, Massachusetts 02115, United States.
Accurate attribution of the areas and populations impacted by climate-related events often relies on linear distance-based methods, where the study unit is assigned temperature data to the closest weather station. We developed a novel method and data pipeline that provides a grid-based measure of exposure to extreme heat and cold events called Grid EXposure (, enabling linkage to individual-level human health data at different spatial scales. GridEX automates the gathering of station-based climatological data and provides estimates of apparent temperature, offering a more comprehensive representation of human thermal comfort and perceived temperature.
View Article and Find Full Text PDF