[This corrects the article DOI: 10.1371/journal.pone.0212294.].
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6844475 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0225294 | PLOS |
Brief Bioinform
November 2024
Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, No. 15 Shangxiadian Road, Cangshan District, Fuzhou 350002, China.
Spatial transcriptomics (ST) technologies enable dissecting the tissue architecture in spatial context. To perceive the global contextual information of gene expression patterns in tissue, the spatial dependence of cells must be fully considered by integrating both local and non-local features by means of spatial-context-aware. However, the current ST integration algorithm ignores for ST dropouts, which impedes the spatial-aware of ST features, resulting in challenges in the accuracy and robustness of microenvironmental heterogeneity detecting, spatial domain clustering, and batch-effects correction.
View Article and Find Full Text PDFConnections between the mechanical properties of DNA and biological functions have been speculative due to the lack of methods to measure or predict DNA mechanics at scale. Recently, a proxy for DNA mechanics, cyclizability, was measured by loop-seq and enabled genome-scale investigation of DNA mechanics. Here, we use this dataset to build a computational model predicting bias-corrected intrinsic cyclizability, with near-perfect accuracy, solely based on DNA sequence.
View Article and Find Full Text PDFAnnotation with widely used, well-structured ontologies, combined with the use of ontology-aware software tools, ensures data and analyses are Findable, Accessible, Interoperable and Reusable (FAIR). Standardized terms with synonyms support lexical search. Ontology structure supports biologically meaningful grouping of annotations (typically by location and type).
View Article and Find Full Text PDFFront Immunol
December 2024
Department of Computer Science, University of Victoria, Victoria, BC, Canada.
Introduction: Accurate genotyping of Killer cell Immunoglobulin-like Receptor (KIR) genes plays a pivotal role in enhancing our understanding of innate immune responses, disease correlations, and the advancement of personalized medicine. However, due to the high variability of the KIR region and high level of sequence similarity among different KIR genes, the generic genotyping workflows are unable to accurately infer copy numbers and complete genotypes of individual KIR genes from next-generation sequencing data. Thus, specialized genotyping tools are needed to genotype this complex region.
View Article and Find Full Text PDFStudy Question: Do recent changes in European Society of Human Reproduction and Embryology (ESHRE) clinical guidelines result in more comprehensive diagnosis of women with endometriosis?
Summary Answer: The latest shift in clinical guidelines results in diagnosis of more women with endometriosis but current ESHRE diagnostic criteria do not capture a sizable percentage of women with the disease.
What Is Known Already: Historically, laparoscopy was the gold standard for diagnosing endometriosis, a complex gynecological condition marked by a heterogeneous set of symptoms that vary widely among women. More recently, changes in clinical guidelines have shifted to incorporate imaging-based approaches such as transvaginal sonography and magnetic resonance imaging.
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