Abstract: Cluster analysis is a fundamental method for studying big data problems, as it groups samples based on shared features. In cluster analysis, a particular class of big data problems is ...
Family has always been important to those working in population genetics. When Sohini Ramachandran was a postdoc, the issue of relatives in a dataset causing inaccurate results was considered a major ...
ABSTRACT: Spatial transcriptomics is undergoing rapid advancements and iterations. It is a beneficial tool to significantly enhance our understanding of tissue organization and relationships between ...
In structural health monitoring (SHM), uncertainties from environmental noise and modeling errors affect damage detection accuracy. This paper introduces a new concept: the Fast Fourier Transform ...
Abstract: Most clustering algorithms require setting one or more parameters, which rely on prior knowledge or are constantly adjusted based on external indicators. To address the issues of requiring ...
This project constructed a nonnegative matrix factorization model integrating two scRNA-seq. This model is called the Integrated Nonnegative Low Rank Matrix Factorization (INLRMF), which can ...
PSMA-based PET imaging in newly diagnosed, high-risk localized prostate cancer, a National Cancer Institute (NCI) Cancer Moonshot trial. This is an ASCO Meeting Abstract from the 2025 ASCO ...
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