SOURCE-LINKED INTELLIGENCE

Spatial Transcriptomics through the lenses of statistical modeling and AI

CORDIS · observation · Publication date unknown

of the data and a mechanistic modeling of the in situ transcriptional measurements. - Combine imaging and tabular data to better define cell types and states through the use of statistical models and artificial intelligence. - Develop an inferential framework to model the localization of transcripts within and across cells and of cells within and across samples. Overall, this proposal will combine machine learning and artificial intelligence approaches with rigorous statistical modeling of transcriptomics data in a spatial, sub-cellular context. This will ultimately serve the biomedical community and provide a suite of tools that will help pave the way towards personalized medicine and computer-assisted pathology. Spatial transcriptomics, single cell, RNA sequencing, transcriptomics, RNA, spatial statistics, machine learning

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recordType

award

status

SIGNED

region

EU

value

1979375

unit

EUR