Dynamic and Parallel Approaches to Optimal Evolutionary Tree Construction

Phylogenetic trees are commonly reconstructed based on hard optimization problems such as Maximum parsimony (MP) and Maximum likelihood (ML). Conventional MP heuristics for producing phylogenetic trees produce good solutions within reasonable time on small databases (up to a few thousand sequences) while ML heuristics are limited to smaller datasets (up to a few hundred sequences). However, since MP and ML are NP-hard, application of such approaches do not scale large datasets. In this paper, we present a promising divideand-conquer technique, the ZAZ method, to construct an evolutionary tree. The algorithm has been implemented and tested against five large biological datasets ranging from 5000-7000 sequences and dramatic speedup with significant improvement in accuracy (better than 94%), in comparison to existing approaches, has been obtained. Thus, high quality reconstruction can be obtained for large datasets by using this approach. Moreover, we present here another approach to con...

• Type: Conference
• Year: 2006
• Where: CCECE
• Authors: Anupam Bhattacharjee, Kazi Zakia Sultana, Zalia Shams
• Keywords: CCECE 2006, Conventional MP Heuristics, Electrical And Computer Engineering, Large Datasets, Phylogenetic Trees