CCMI - Training

CCMI Software Series: The Human Protein Atlas

November

24

9:00 AM-11:00 AM

Dr. Cecilia Lindskog Bergström, Director of the HPA Tissue Atlas, takes us through navigating the extensive resources of the HPA

The CCMI’s Computational Biology Software Series will cover a range of publicly available databases and analysis tools to help empower your research.

Please click here to register for free.

The Human Protein Atlas – Spatial proteomics in health and disease. The spatial distribution of proteins determines the morphology and function of tissues, cells, and organelles. Knowledge of this spatial distribution is therefore essential to understand the healthy and diseased human body. The Human Protein Atlas (HPA) project is a large-scale initiative aiming at mapping the entire human proteome using antibody-based proteomics and integration of various other omics technologies. The publicly available knowledge resource www.proteinatlas.org has grown into one of the world’s most visited biological databases. The current version is divided into six main sections, each focusing on particular aspects of the human proteome: (a) the Tissue Atlas showing the distribution of proteins across all major tissues and organs in the human body; (b) the Single Cell Type Atlas showing expression of protein-coding genes in single human cell types; (c) the Pathology Atlas showing the impact of protein levels on survival of patients with cancer; (d) the Brain Atlas exploring the distribution of proteins in various regions of the mammalian brain; (e) the Blood Atlas describing proteins detected in the blood cell types and proteins secreted by human tissues; and (f) the Cell Atlas showing the subcellular localization of proteins in single cells. The HPA constitutes an important resource for further understanding of human biology and precision medicine efforts, and the publicly available datasets hold much promise for integration with other emerging efforts focusing on single cell analyses, both at transcriptomic and proteomic level.

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