Vicković Lab
As the field of digital pathology continually evolves, at the Vicković Lab, we continuously strive to develop new tools to advance our understanding of human diseases. Our ultimate goal? To better understand and track how diseases progress in the human body and to identify potential drug and therapeutic targets that can lead to improved treatments.
Overview
In Vicković Lab we utilize collaborative approach to cover a diversified portfolio of projects:
To achieve this, cutting-edge techniques such as single-cell sequencing, machine learning and spatial transcriptomics are employed. Spatial genomics in particular stands out as a game-changer in this rapidly advancing field. By focusing specifically on the spatial distribution of chromatin, RNA and proteins within a tissue sample, spatial genomics allows for a more nuanced understanding of cell and tissue function. This innovative approach is revolutionizing the way we analyze and interpret genomic data, placing us at the forefront of this exciting frontier in science.
Sanja Vicković, PhD
Core Faculty Member, NYGC, Director, Technology Innovation Lab, NYGC
Assistant Professor, Department of Engineering and Institute for Cancer Dynamics, Columbia University; Wallenberg Academy Fellow of the Royal Swedish Academy of Sciences and the Royal Swedish Academy of Engineering Sciences at Uppsala University
Highlights From Dr. Vicković’s Previous Work
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Nature Communications. · 2022 Feb. 11.
Three-dimensional spatial transcriptomics uncovers cell type dynamics in the human rheumatoid arthritis synovium.
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Nature Communications. · 2022 Feb. 10.
SM-Omics is an automated platform for high-throughput spatial multi-omics.
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Nature Methods. · 2019 Sept. 09.
High-definition spatial transcriptomics for in situ tissue profiling.
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Science. · 2019 April 05.
Spatiotemporal dynamics of molecular pathology in amyotrophic lateral sclerosis.
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Nature Communications. · 2016 Oct. 14.
Massive and parallel expression profiling using microarrayed single-cell sequencing.
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Science. · 2016 July 01.
Visualization and analysis of gene expression in tissue sections by spatial transcriptomics.