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Revolutionary 'scLENS' unveiled to decode complex single-cell genomic data - EurekAlert

Revolutionizing single-cell RNA sequencing analysis, IBS and KAIST researchers unveiled 'scLENS', a tool leveraging Random Matrix Theory for automatic signal detection. This eliminates subjective bias, vastly improving data accuracy and efficiency. Published in 'Nature Communications', scLENS marks a significant advance, simplifying the extraction of biological signals from complex data, promising major strides in life sciences research. Now, researchers can rapidly identify key genes, enhancing our understanding of cellular processes.

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