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Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
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Omics-driven insights and microarray applications in drug discovery and development.

Pooja Mathur1, Kanika Goyal2, Ajay Pal Singh3

  • 1Department of Pharmacy, School of Healthcare and Allied Sciences, GD Goenka University, Sohna, Gurugram, Haryana 121003, India.

Computational Biology and Chemistry
|November 19, 2025
PubMed
Summary

Omics techniques like genomics, transcriptomics, and metabolomics are revolutionizing drug discovery. These methods provide deeper insights into complex diseases, enabling the development of more targeted and personalized medicines.

Keywords:
Drug discoveryGenomicsMetabolomicsProteomicsTranscriptomics

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Area of Science:

  • Biotechnology
  • Genomics
  • Molecular Biology

Background:

  • Complex biological systems pose challenges in drug discovery.
  • Omics techniques offer novel approaches to understand these systems.

Purpose of the Study:

  • To explore the role of genomics, transcriptomics, and metabolomics in drug discovery and development.
  • To highlight how these techniques enhance understanding of diseases and therapeutic interventions.

Main Methods:

  • Genomics: Analyzing complete genetic information for target identification.
  • Transcriptomics: Profiling gene expression for disease insights and biomarker discovery.
  • Metabolomics: Studying small molecules to understand metabolic pathways and identify drug candidates.

Main Results:

  • Omics data aids in identifying drug targets and disease susceptibility factors.
  • Gene expression patterns reveal molecular intricacies and therapeutic targets.
  • Metabolomic analysis accelerates drug candidate identification and personalized medicine.

Conclusions:

  • Omics techniques are transforming drug discovery by providing molecular insights.
  • These approaches facilitate the development of more effective, targeted therapies.
  • A new era of personalized medicine is emerging through advanced omics analysis.