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MOPITAS Seminar

 

Unveiling the Spatial Multi-OMICS Frontier from algorithm to application 

 

Dates: November 5-6 

Location: Copenhagen Denmark 

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Planned Sessions

Session I – Latest Technologies: Talks covering the forefront of spatial omics technologies and recent developments in spatial multi-OMICS technologies. Additionally, we seek to provide insights into the evolving landscape of spatial proteomics, with a spotlight on spatial mass spectrometry.

Session II – Multi-modal data integration: This session focuses on the synergistic integration of multi-modal data in spatial omics research. We cover a broad spectrum of approaches for the integration of spatial transcriptomics with genomics and epigenomics, fostering a deeper appreciation for the interplay between different molecular layers.

Session III – Translation: This session explores the possibilities and limitations of bringing spatial transcriptomics technologies from the laboratory to clinical practice. We will discuss the role of spatial transcriptomics in disease progression, diagnosis, and prognosis, and its utility in developing personalized treatment strategies. 

Session IV – Benchmarking: This session delves into the complex algorithmic solutions for processing spatial transcriptomics data and the correct evaluation. The lack of a gold standard dataset is a bottleneck for objectively comparing and evaluating competing methods. Artificial data generation could speed up development and evaluation in different scenarios.

Session V - Interpretation & Regulatory Mechanisms: In this session, we explore the nuanced interpretation of spatial transcriptomics data with a specific focus on regulatory mechanisms. The spatial resolution allows for precise investigation of cell-cell interactions but requires appropriate analysis methods and statistical tests. Discussions will include the integration of spatial transcriptomics with other molecular layers to uncover spatially resolved transcription factor interactions.

 

The symposium is funded by the Danish Data Science Academy and the Novo Nordisk Fonden  

 

 

Last Updated 24.07.2024