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http://dx.doi.org/10.1073/pnas.2312950120 | DOI Listing |
Sci Rep
January 2025
MRC WIMM Centre for Computational Biology, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 9DS, UK.
Bulk ATAC-seq assays have been used to map and profile the chromatin accessibility of regulatory elements such as enhancers, promoters, and insulators. This has provided great insight into the regulation of gene expression in many cell types in a variety of organisms. To date, ATAC-seq has most often been used to provide an average evaluation of chromatin accessibility in populations of cells.
View Article and Find Full Text PDFSci Rep
January 2025
D. Y. Patil Agriculture and Technical University, Talsande, Maharashtra, India.
Indian agriculture is vital sector in the country's economy, providing employment and sustenance to millions of farmers. However, Plant diseases are a serious risk to crop yields and farmers' livelihoods. Traditional plant disease diagnosis methods rely heavily on human expertise, which can lead to inaccuracies due to the invisible nature of early disease symptoms and the labor-intensive process, making them inefficient for large-scale agricultural management.
View Article and Find Full Text PDFNano Lett
January 2025
Electron Microscopy Center, Empa - Swiss Federal Laboratories for Materials Science and Technology, Überlandstrasse 129, 8600 Dübendorf, Switzerland.
The computational cost of simulating scanning transmission electron microscopy (STEM) images limits the curation of large enough data sets to train accurate and robust machine learning networks for deep feature extraction from atomically resolved STEM images. For nanoparticle size estimation in particular, a diverse data set is essential due to the large variations in size, shape, crystallinity, orientation, and dynamical diffraction effects in experimental data. To address this, we train a 3D convolutional neural network to predict STEM images from voxelized atomic models, achieving a 100x speed-up compared to traditional multislice simulations while maintaining high image quality.
View Article and Find Full Text PDFComput Biol Med
January 2025
State Key Laboratory of Oral Diseases and National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, China. Electronic address:
Medical image segmentation is pivotal in disease diagnosis and treatment. This paper presents a novel network architecture for medical image segmentation, termed TransDLNet, which is engineered to enhance the efficiency of multi-scale information utilization. TransDLNet integrates convolutional neural networks and Transformers, facilitating cross-level multi-scale information fusion for complex medical images.
View Article and Find Full Text PDFJMIR Med Inform
January 2025
INSERM U1064, CR2TI - Center for Research in Transplantation and Translational Immunology, Nantes University, 30 Bd Jean Monnet, Nantes, 44093, France, 33 2 40 08 74 10.
Precision medicine involves a paradigm shift toward personalized data-driven clinical decisions. The concept of a medical "digital twin" has recently become popular to designate digital representations of patients as a support for a wide range of data science applications. However, the concept is ambiguous when it comes to practical implementations.
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