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A consensus method for prioritising drug-associated target proteins.

Gang Shu1, Xiaodi Huang, Shanfeng Zhu

  • 1The School of Computer Science and Shanghai Key Lab. of Intelligent Information Processing, Fudan University, Shanghai 200433, China. 09210240030@fudan.edu.cn

International Journal of Data Mining and Bioinformatics
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PubMed
Summary

This study compares eight methods for biomedical text mining, finding that pof, coherence, and all-confidence are top performers. A consensus approach integrating coherence into pof achieved the best results for prioritizing drug targets.

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Area of Science:

  • Biomedical text mining
  • Bioinformatics
  • Natural Language Processing

Background:

  • The frequency of entity co-occurrence in literature is often used to infer the strength of their relationship.
  • Several statistical methods exist for quantifying these co-occurrences in biomedical text mining.

Purpose of the Study:

  • To compare the performance of eight established co-occurrence-based methods in biomedical text mining.
  • To identify the optimal method for prioritizing potential drug targets.
  • To develop and evaluate a consensus approach to further enhance performance.

Main Methods:

  • Evaluation of eight distinct co-occurrence measures: support, confidence, chi-square, odds ratio, lift, all-confidence, coherence, and pof.
  • Development of a consensus method by integrating coherence with the pof measure.
  • Experimental validation using a drug target prioritization task.

Main Results:

  • The methods pof, coherence, and all-confidence demonstrated superior performance individually.
  • The developed consensus approach, which integrates coherence into pof, significantly outperformed all other tested methods.
  • The findings highlight the effectiveness of combining different statistical measures for improved biomedical relation extraction.

Conclusions:

  • The pof, coherence, and all-confidence methods are highly effective for biomedical relation extraction and drug target prioritization.
  • A consensus strategy, specifically combining coherence and pof, offers the best performance among the evaluated techniques.
  • This research provides a refined approach for leveraging literature-based co-occurrence data in drug discovery.