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Achieving large and distant ancestral genome inference by using an improved discrete quantum-behaved particle swarm optimization algorithm.

Zhaojuan ZhangWan Liang WangRuofan XiaGaofeng PanJiandong WangJijun Tang
Published in: BMC bioinformatics (2020)
Our experimental results demonstrate the advantages of IDQPSO-Median approach over the other methods when the genomes are large and distant. When our experimental results are evaluated in a comprehensive manner, it is clear that the IDQPSO-Median approach we propose achieves better scalability compared to existing algorithms. Moreover, our experimental results by using simulated and real datasets confirm that the IDQPSO-Median, when integrated with the GRAPPA framework, outperforms other heuristics in terms of accuracy, while also continuing to infer phylogenies that were equivalent or close to the true trees within 5 days of computation, which is far beyond the difficulty level that can be handled by GRAPPA.
Keyphrases
  • machine learning
  • lymph node
  • deep learning
  • single cell
  • rna seq
  • genome wide
  • dna methylation