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Related Concept Videos

Proteomics01:33

Proteomics

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A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
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Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation01:26

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Inductively coupled plasma (ICP) is the common plasma source used in atomic emission spectroscopy (AES), a technique that detects and analyzes various elements in a sample. This method is often called inductively coupled plasma atomic emission spectroscopy (ICP-AES).
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Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine
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Aquila: a spatial omics database and analysis platform.

Yimin Zheng1,2,3,4, Yitian Chen1,2,3,4, Xianting Ding5

  • 1Cancer Centre, University of Macau, Taipa 999078, Macau SAR.

Nucleic Acids Research
|October 16, 2022
PubMed
Summary
This summary is machine-generated.

Aquila is a new database for spatial omics data, offering analysis and visualization tools for transcript and protein expression within tissue microenvironments. It provides insights into cellular networks and disease studies.

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Area of Science:

  • Biotechnology
  • Bioinformatics
  • Genomics

Background:

  • Spatial omics integrates spatial information with molecular data to study tissue microenvironments.
  • Existing databases lack comprehensive resources for accessing and analyzing diverse spatial omics datasets.

Purpose of the Study:

  • To develop Aquila, a centralized platform for managing and analyzing spatial omics data.
  • To provide tools for visualizing and analyzing transcript and protein expression in tissues.

Main Methods:

  • Compiled 107 spatial omics datasets covering 30 diseases, including spatial transcriptomics and proteomics.
  • Integrated data from 2D and 3D experiments using various technologies.
  • Developed visualization tools for cell distribution, marker expression, and co-localization.

Main Results:

  • Aquila hosts 15.7 million cells across 6500+ regions of interest.
  • The platform supports basic and advanced spatial analyses.
  • Users can securely upload their own data for analysis.

Conclusions:

  • Aquila offers a comprehensive resource for spatial omics data management and analysis.
  • The platform enhances understanding of tissue architecture and molecular interactions.
  • Aquila is accessible via a web interface and a desktop application with API support.