Estimation error of candidate methods with a threshold of 0.1.

<p>Estimation error of candidate methods with a threshold of 0.1.</p>

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Bibliographic Details
Main Author:	Lulu Pan (8977979) (author)
Other Authors:	Qian Gao (146991) (author), Kecheng Wei (2747674) (author), Yongfu Yu (477682) (author), Guoyou Qin (681758) (author), Tong Wang (87696) (author)
Published:	2025
Subjects:	Genetics Evolutionary Biology Science Policy Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified penalized maximum likelihood linear regression model extensive simulation experiments dimensional linear regression dimensional linear models avoid including non transferable sources based integrate useful information accommodate complex data ptlr demonstrates robustness outliers exist compared transfer learning problem useful source data expectation maximization algorithm maximization algorithm transfer learning source datasets ptlr ), offering robustness informative sources borrowing information learning performance target data variable selection tissue expression target tissue support integration poses challenges oracle case gene associations effectively applied distributed error better performance application demonstrate
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