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Comparison of human cell signaling pathway databases--evolution, drawbacks and challenges.

Saikat Chowdhury1, Ram Rup Sarkar2

  • 1Chemical Engineering and Process Development Division, CSIR-National Chemical Laboratory, Dr. Homi Bhaba Road, Pune, Maharashtra 411008, India and Academy of Scientific & Innovative Research (AcSIR), New Delhi 110 001, India Chemical Engineering and Process Development Division, CSIR-National Chemical Laboratory, Dr. Homi Bhaba Road, Pune, Maharashtra 411008, India and Academy of Scientific & Innovative Research (AcSIR), New Delhi 110 001, India.

Database : the Journal of Biological Databases and Curation
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PubMed
Summary

This review analyzes 24 cell signaling databases, identifying limitations in data heterogeneity and annotation. It proposes solutions for future development to aid biological research and understanding of cell signaling pathways.

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Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Systems Biology

Background:

  • Cell signaling pathways are crucial for understanding gene regulation, cell fate, and diseases.
  • The Human Genome Project facilitated pathway analysis.
  • Numerous pathway databases exist, offering computational tools.

Purpose of the Study:

  • To review and evaluate 24 popular cell signaling databases.
  • To identify limitations and propose improvements for future database development.
  • To aid the scientific community in utilizing pathway data.

Main Methods:

  • Systematic review of 24 actively functioning cell signaling databases.
  • Analysis based on pathway information and technical details.
  • Examination of freely accessible commercial and academic databases.

Main Results:

  • Identified challenges include pathway data heterogeneity, annotation, and updates.
  • Highlighted novel features not yet integrated into existing databases.
  • Assessed the evolution and enrichment of pathway data over time.

Conclusions:

  • Current databases have limitations requiring solutions for better data integration and usability.
  • Future database development should focus on addressing identified drawbacks.
  • Enhanced databases will significantly benefit biological research and disease study.