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  In recent years, a variety of sequencing techniques have been widely used in basic biology and clinical medical research, allowing us to understand the internal mechanisms of cell development, differentiation, transformation and cytopathy from the genomic level. However, in-depth analysis of massive sequencing data is still a problem, especially single-cell sequencing data contains a lot of experimental noise, and its data scale has now increased exponentially to the order of millions, efficient and accurate bioinformatics algorithms and tools are urgently needed.

  The Bioinformatics Center of NIBS is committed to developing new machine learning and deep learning algorithms, through the analysis of multiple types of large-scale sequencing data, including single-cell genome, spatial transcriptome, epigenetic group, whole genome, proteome and other omics data, in-depth mining of the pathogenesis of various major diseases and potential drug targets, to provide personalized and accurate diagnosis and treatment of patients to provide support.In addition, the Bioinformatics Center works closely with various laboratories in the NIBS to explore the internal mechanisms of the emergence and transformation of various diseases and the development and differentiation of cells using a variety of bioinformatics analysis methods.

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