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 TangPublished 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.