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Related Concept Videos

Overview of Cell Death01:30

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Cell death is an essential process where the body gets rid of old or damaged cells. Cell proliferation and death need to be balanced, as an imbalance between the two may lead to cancer or autoimmune diseases.
Cell death was observed in the early 19th century, but there was no experimental evidence to prove it. In 1842, Carl Vogt first discovered cell death in a metamorphic toad; however, it was not termed ‘cell death.’ Scientists discovered different cell death pathways only in the...
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Informatics and data science in cell death research.

Hue Vu-Thi1, Huy Than Quang2, Vu-Hung Nguyen2

  • 1The Interdisciplinary Research Group on Biomedicine and Health, International School, Vietnam National University, Hanoi, Vietnam; Faculty of Applied Sciences, International School, Vietnam National University, Hanoi, Vietnam.

Progress in Molecular Biology and Translational Science
|September 22, 2025
PubMed
Summary
This summary is machine-generated.

Informatics and data science enhance cell death research by improving data analysis and diagnostics. These advanced methods address challenges in quantifying and defining cell death, crucial for understanding diseases like cancer.

Keywords:
ApoptosisCell deathData scienceInformatics

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Area of Science:

  • Cell biology
  • Bioinformatics
  • Computational biology

Background:

  • Cell death is vital for tissue homeostasis and removing damaged cells.
  • Dysregulation of cell death pathways is implicated in diseases such as cancer and autoimmune disorders.
  • Traditional cell death research faces challenges in quantification, classification, and detection.

Purpose of the Study:

  • To provide an overview of informatics and data science applications in cell death research.
  • To discuss the advantages and limitations of traditional cell death research methods.
  • To explore how informatics, data science, and artificial intelligence (AI) can overcome existing challenges.

Main Methods:

  • Review of existing literature on informatics and data science in cell death research.
  • Analysis of traditional cell death research methodologies.
  • Discussion of AI-driven approaches for cell death analysis.

Main Results:

  • Informatics and data science offer significant advantages over traditional methods in cell death research.
  • These computational approaches improve the efficiency of complex data processing and biological system modeling.
  • Implementation of these methods enhances the performance of diagnostic procedures.

Conclusions:

  • Informatics and data science are revolutionizing cell death research.
  • AI and data-driven strategies provide powerful tools to overcome limitations in traditional methods.
  • This integration facilitates the development of more effective research plans and improved diagnostic capabilities for cell death-related diseases.