Artificial intelligence (AI) has become a common tool for bioinformatics, with hundreds of methods published in recent years. Due to the training data demands of deep-learning algorithms, ...

Characterizing spatial variations in gene expression with cell type specificity is crucial for understanding complex traits and diseases, yet it remains challenging. Here, we introduce the Mixture of ...

This study makes a valuable contribution to spatial transcriptomics by rigorously benchmarking cell-type deconvolution methods, assessing their performance across diverse datasets with a focus on ...

How do astroimagers get such sharp images of the Sun, Moon, and planets? The answer is a technique called lucky imaging. As every astronomer has witnessed, the atmosphere roils with waves as hot and ...

This tutorial presents and explains examples of the deconvolution of hydrophone measurement data. The motivation for performing deconvolution is that, in many cases, measurements of ultrasonic signals ...

Abstract: Estimating the time delay difference between two microphones is important in many systems, including sonar, radar, wireless, and acoustics imaging systems. The generalized cross correlation ...

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Spatial transcriptomics technologies generate gene expression profiles with spatial context, requiring spatially informed analysis tools for three key tasks, spatial clustering, multisample ...