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Related Concept Videos

Genomics02:02

Genomics

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Updated: Dec 13, 2025

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
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A User-Friendly Visualization Tool for Multi-Omics Data.

Sunghyun Huh1, Min-Sik Kim1

  • 1Department of New Biology, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, 42988, Republic of Korea.

Proteomics
|August 4, 2020
PubMed
Summary
This summary is machine-generated.

A new web-based tool, ProTrack, simplifies exploring complex cancer multi-omic data from the Clinical Proteomic Tumor Analysis Consortium (CPTAC). This visualization platform makes analyzing genomics, proteomics, and other data types accessible for cancer research without coding.

Keywords:
Clinical Proteomic Tumor Analysis Consortiumdata visualizationmulti-omics

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Area of Science:

  • Oncology
  • Bioinformatics
  • Genomics

Background:

  • The Clinical Proteomic Tumor Analysis Consortium (CPTAC) provides extensive multi-omic cancer datasets.
  • Analyzing these complex datasets is challenging for researchers without bioinformatics expertise due to data heterogeneity and lack of user-friendly tools.

Purpose of the Study:

  • To introduce ProTrack, a web-based visualization platform designed for exploring CPTAC clear cell renal cell carcinoma (ccRCC) data.
  • To provide an accessible tool for investigating associations between different molecular data types within cancer.

Main Methods:

  • Development of ProTrack, a user-friendly, web-based visualization platform.
  • Focus on the CPTAC clear cell renal cell carcinoma (ccRCC) dataset.
  • Enabling exploration of gene-specific data, including mutations and phosphosites, and cross-gene associations.

Main Results:

  • ProTrack offers a customizable interface for exploring CPTAC ccRCC multi-omic data.
  • The platform allows users to inspect associations between genomics, transcriptomics, and proteomics data without coding.
  • Facilitates easy lookup of specific mutation types and phosphosites for any gene of interest.

Conclusions:

  • ProTrack enhances accessibility to complex CPTAC ccRCC data for researchers and clinicians.
  • The tool simplifies the investigation of multi-omic data, aiding cancer biology research.
  • Future work aims to extend ProTrack to other CPTAC datasets, broadening its impact.