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Division of Hematology, Children's National Hospital, Washington, District of Columbia, USA.
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College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China.
The role of cell-cell communications (CCCs) is increasingly recognized as being important to differentiation, invasion, metastasis, and drug resistance in tumoral tissues. Developing CCC inference methods using traditional experimental methods are time-consuming, labor-intensive, cannot handle large amounts of data. To facilitate inference of CCCs, we proposed a computational framework, called CellMsg, which involves two primary steps: identifying ligand-receptor interactions (LRIs) and measuring the strength of LRIs-mediated CCCs.
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View Article and Find Full Text PDFAn examination of daily CO emissions prediction through a comparative analysis of machine learning, deep learning, and statistical models.
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Department of Geology and Mineral Science, Kwara State University, Malete, P.M.B. 1530, Ilorin, Kwara State, Nigeria.
Human-induced global warming, primarily attributed to the rise in atmospheric CO, poses a substantial risk to the survival of humanity. While most research focuses on predicting annual CO emissions, which are crucial for setting long-term emission mitigation targets, the precise prediction of daily CO emissions is equally vital for setting short-term targets. This study examines the performance of 14 models in predicting daily CO emissions data from 1/1/2022 to 30/9/2023 across the top four polluting regions (China, India, the USA, and the EU27&UK).
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