DeepChopper model improves RNA sequencing research by mitigating chimera artifacts

Scientists in the laboratory of Rendong Yang, Ph.D., associate professor of Urology, have developed a new large language model that can interpret transcriptomic data in cancer cell lines more accurately than conventional approaches, as detailed in a recent study published in Nature Communications.

Originally published at Phys.org