Computational approaches for the analyses of spatial profiling technologies

Division Of Basic Sciences - Nci

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Abstract

In a tumor ecosystem, the location and spatial interactions among diverse cell populations are determining the tumor progression and therapy outcome. However, conventional genomics approaches, such as bulk sequencing and single-cell profiling, cannot capture critical spatial information. Recent years have seen the rapid progress of spatial technologies for both proteomics and transcriptomics profiling. These technologies generate new data types, which may have a lower resolution than current data, but contains spatial dynamics patterns. Therefore, I plan to develop bioinformatics methods to enable knowledge mining for spatial proteomics and transcriptomics data. Since joining the CCR on July 8th, 2019, I have been establishing my laboratory to begin these endeavors.