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Biological gene extraction path based on knowledge graph and natural language processing.

Canlin Zhang1, Xiaopei Cao2

  • 1Sorenson Communications, Salt Lake City, UT, United States.

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Summary
This summary is machine-generated.

This study introduces a novel method for identifying key genes in breast cancer research, significantly reducing costs and improving efficiency. The approach effectively screens genetic data, achieving a high recognition rate and removing over 99% of redundant genes.

Keywords:
biological genebiological gene extractionknowledge graphnatural language processingpath research

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Area of Science:

  • Bioinformatics and Computational Biology
  • Genomics and Molecular Biology
  • Cancer Research

Background:

  • Advancements in bioinformatics technology revolutionize biological gene research.
  • A persistent challenge in genetic research is efficiently identifying crucial genes from large datasets to minimize costs and unnecessary studies.
  • Effective gene extraction is vital for focusing research efforts on the most valuable genetic information.

Purpose of the Study:

  • To develop and validate an efficient method for extracting characteristic genes from breast cancer samples.
  • To reduce research costs and time by minimizing the analysis of non-essential genes.
  • To improve the accuracy and efficiency of genetic analysis in breast cancer research.

Main Methods:

  • Utilized Bhattacharyya distance index and Gini index for sample gene screening.
  • Applied Principal Component Analysis (PCA) to extract principal components from selected public genes.
  • Evaluated the performance of the characteristic gene extraction method on breast cancer datasets.

Main Results:

  • The optimal selection of 5 characteristic genes achieved the highest gene recognition rate of 90.31%.
  • The developed method demonstrated a high removal rate of 99.75% for redundant genes.
  • The findings indicate a significant reduction in research time and financial expenditure.

Conclusions:

  • The proposed characteristic gene extraction method effectively identifies key genes in breast cancer.
  • This approach offers a substantial improvement in research efficiency and cost-effectiveness.
  • The study provides a valuable tool for accelerating genetic research in oncology.