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Related Concept Videos

Thermosensation01:43

Thermosensation

Peripheral thermosensation is the perception of external temperature. A change in temperature (on the surface of the skin and other tissues) is detected by a family of temperature-sensitive ion channels called Transient Receptor Potential, or TRP, receptors. These receptors are located on free nerve endings. Those detecting cold temperatures are closer to the surface of the skin than the nerve endings detecting warmth. These thermoTRP channels, while temperature selective, have relatively...

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Analysis Based on TCGA Data and Single-cell Data, taking TRPM4 as an Example.

Yiqiang Da1, Xuerui Chen1, Lanxin Yu2

  • 1The First Clinical Medical College, Nanjing Medical University.

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|December 22, 2025
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This study introduces a novel bioinformatics method using single-cell data to analyze single gene roles in tumors, aiding in understanding the tumor immune microenvironment and predicting patient prognosis.

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Area of Science:

  • Oncology
  • Bioinformatics
  • Genomics

Background:

  • Tumorigenesis involves complex gene interactions influencing the tumor microenvironment and patient outcomes.
  • Analyzing single genes offers insights into tumor heterogeneity and molecular subtypes, but traditional methods face limitations.

Purpose of the Study:

  • To present an integrated method for comprehensive single-gene analysis in tumors.
  • To explore the role of single genes in shaping the tumor immune microenvironment, molecular subtypes, and prognosis.
  • To provide accessible tools for researchers, including the TISCH2 web platform.

Main Methods:

  • Utilizing public transcriptomic and single-cell datasets for gene expression analysis.
  • Employing 101 machine learning models to build accurate prognostic prediction models.
  • Leveraging the TISCH2 web platform (http://tisch.compbio.cn/) for simplified single-cell data analysis.

Main Results:

  • The method allows for detailed characterization of single-gene functions within tumors.
  • It enhances understanding of gene expression patterns in specific cell clusters.
  • The integrated approach improves the accuracy of prognostic models.

Conclusions:

  • This integrated single-gene analysis method combines bioinformatics, machine learning, and single-cell analysis for robust tumor research.
  • It offers a powerful approach to investigate gene functions in tumor progression and pathways.
  • The TISCH2 platform democratizes single-cell analysis for a wider research community.