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Disease Sequences High-Accuracy Alignment Based on the Precision Medicine.

ManZhi Li1, HaiXia Long2, HongTao Wang1

  • 1School of Mathematics and Statistics, Hainan Normal University, Haikou, Hainan 571158, China.

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Summary
This summary is machine-generated.

Accurate sequence alignment is crucial for disease treatment. This study introduces new formulas for sequence alignment parameters, improving accuracy for precision medicine applications.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Accurate multiple sequence alignment (MSA) is vital for understanding disease mechanisms and developing treatments.
  • MSA results are sensitive to objective function parameters: gap open penalties (GOP), gap extension penalties (GEP), and substitution matrices (SM).

Purpose of the Study:

  • To infer theoretical formulas for GOP, GEP, and SM based on sequence characteristics.
  • To validate these formulas experimentally and derive optimized parameters for MSA tools.
  • To enhance the accuracy of sequence alignment for applications in precision medicine.

Main Methods:

  • Derived theoretical parameter formulas for GOP, GEP, and SM using sequence length, number, and identity.
  • Experimentally tested the derived formulas using ClustalW and MAFFT alignment programs.
  • Generated optimized MAFFT parameters based on the proposed theoretical formulas.

Main Results:

  • The sum-of-pair scores (SPS) achieved using theoretically derived parameters were superior to those from default parameters in both ClustalW and MAFFT.
  • Experimental validation confirmed the feasibility and efficiency of the proposed parameter determination method.
  • The new parameters yielded higher accuracy in sequence alignment.

Conclusions:

  • The developed theoretical framework and derived parameters offer a feasible and efficient method for optimizing MSA.
  • This approach significantly improves alignment accuracy, providing valuable data for precision medicine.
  • The findings contribute to more effective disease treatment and prevention strategies through enhanced bioinformatics tools.