Who is Who in Phylogenetic Networks

Publications of Changiz Eslahchi     Order by:   Type | Year

Associated keywords

abstract-network circular-split-system explicit-network from-distances from-quartets from-triplets from-unrooted-trees heuristic level-k-phylogenetic-network phylogenetic-network phylogeny Program-MC-Net Program-SAQ-Net Program-SNSA Program-SplitsTree Program-TripNet reconstruction simulated-annealing software split split-network

2017

1 Ruzbeh Tusserkani, Hadi Poormohammadi, Azin Azadi and Changiz Eslahchi. Inferring phylogenies from minimal information. In AEEICB17, Pages 202-206, IEEE, 2017. Keywords: from triplets, phylogenetic network, phylogeny, Program TripNet, reconstruction.

2014

2 Hadi Poormohammadi, Changiz Eslahchi and Ruzbeh Tusserkani. TripNet: A Method for Constructing Rooted Phylogenetic Networks from Rooted Triplets. In PLoS ONE, Vol. 9(9):e106531, 2014. Keywords: explicit network, from triplets, heuristic, level k phylogenetic network, phylogenetic network, phylogeny, Program TripNet, reconstruction, software. Note: http://arxiv.org/abs/1201.3722.         Toggle abstract "The problem of constructing an optimal rooted phylogenetic network from an arbitrary set of rooted triplets is an NP-hard problem. In this paper, we present a heuristic algorithm called TripNet, which tries to construct a rooted phylogenetic network with the minimum number of reticulation nodes from an arbitrary set of rooted triplets. Despite of current methods that work for dense set of rooted triplets, a key innovation is the applicability of TripNet to non-dense set of rooted triplets. We prove some theorems to clarify the performance of the algorithm. To demonstrate the efficiency of TripNet, we compared TripNet with SIMPLISTIC. It is the only available software which has the ability to return some rooted phylogenetic network consistent with a given dense set of rooted triplets. But the results show that for complex networks with high levels, the SIMPLISTIC running time increased abruptly. However in all cases TripNet outputs an appropriate rooted phylogenetic network in an acceptable time. Also we tetsed TripNet on the Yeast data. The results show that Both TripNet and optimal networks have the same clustering and TripNet produced a level-3 network which contains only one more reticulation node than the optimal network."

2012

3 Hadi Poormohammadi and Changiz Eslahchi. Constructing Rooted Phylogenetic Networks from Triplets based on Height Function. In International Journal of Emerging Technology and Advanced Engineering, Vol. 2(7):389-393, 2012. Keywords: from triplets, heuristic, phylogenetic network, phylogeny, reconstruction. Note: http://www.ijetae.com/files/Volume2Issue7/IJETAE_0712_67.pdf.         4 Changiz Eslahchi, Reza Hassanzadeh, Ehsan Mottaghi, Mahnaz Habibi, Hamid Pezeshk and Mehdi Sadeghi. Constructing circular phylogenetic networks from weighted quartets using simulated annealing. In MBIO, Vol. 235(2):123-127, 2012. Keywords: abstract network, from quartets, heuristic, phylogenetic network, phylogeny, Program SAQ-Net, Program SplitsTree, reconstruction, simulated annealing, software, split network. Note: http://dx.doi.org/10.1016/j.mbs.2011.11.003.         Toggle abstract "In this paper, we present a heuristic algorithm based on the simulated annealing, SAQ-Net, as a method for constructing phylogenetic networks from weighted quartets. Similar to QNet algorithm, SAQ-Net constructs a collection of circular weighted splits of the taxa set. This collection is represented by a split network. In order to show that SAQ-Net performs better than QNet, we apply these algorithm to both the simulated and actual data sets containing salmonella, Bees, Primates and Rubber data sets. Then we draw phylogenetic networks corresponding to outputs of these algorithms using SplitsTree4 and compare the results. We find that SAQ-Net produces a better circular ordering and phylogenetic networks than QNet in most cases. SAQ-Net has been implemented in Matlab and is available for download at http://bioinf.cs.ipm.ac.ir/softwares/saq.net. © 2011 Elsevier Inc." 5 Reza Hassanzadeh, Changiz Eslahchi and Wing-Kin Sung. Constructing phylogenetic supernetworks based on simulated annealing. In MPE, Vol. 63(3):738-744, 2012. Keywords: abstract network, from unrooted trees, heuristic, phylogenetic network, phylogeny, Program SNSA, reconstruction, simulated annealing, software, split network. Note: http://dx.doi.org/10.1016/j.ympev.2012.02.009.         Toggle abstract Different partial phylogenetic trees can be derived from different sources of evidence and different methods. One important problem is to summarize these partial phylogenetic trees using a supernetwork. We propose a novel simulated annealing based method called SNSA which uses an optimization function to produce a simple network that still retains a great deal of phylogenetic information. We report the performance of this new method on real and simulated datasets. © 2012 Elsevier Inc.

2011

6 Ruzbeh Tusserkani, Changiz Eslahchi, Hadi Poormohammadi and Azin Azadi. TripNet: A Method for Constructing Phylogenetic Networks from Triplets. 2011. Keywords: explicit network, heuristic, level k phylogenetic network, phylogenetic network, phylogeny, Program TripNet, reconstruction, software. Note: http://arxiv.org/abs/1104.4720.         7 Changiz Eslahchi and Reza Hassanzadeh. New Algorithm for Constructing Supernetworks from Partial Trees. In MCCMB11, Pages 106-107, 2011. Keywords: abstract network, from unrooted trees, heuristic, phylogenetic network, phylogeny, Program SNSA, reconstruction, simulated annealing, split network. Note: http://mccmb.belozersky.msu.ru/2011/mccmb11.pdf#page=106.

2010

8 Changiz Eslahchi, Mahnaz Habibi, Reza Hassanzadeh and Ehsan Mottaghi. MC-Net: a method for the construction of phylogenetic networks based on the Monte-Carlo method. In BMCEB, Vol. 10:254, 2010. Keywords: abstract network, circular split system, from distances, heuristic, phylogenetic network, Program MC-Net, Program SplitsTree, software, split, split network. Note: http://dx.doi.org/10.1186/1471-2148-10-254.         Toggle abstract "Background. A phylogenetic network is a generalization of phylogenetic trees that allows the representation of conflicting signals or alternative evolutionary histories in a single diagram. There are several methods for constructing these networks. Some of these methods are based on distances among taxa. In practice, the methods which are based on distance perform faster in comparison with other methods. The Neighbor-Net (N-Net) is a distance-based method. The N-Net produces a circular ordering from a distance matrix, then constructs a collection of weighted splits using circular ordering. The SplitsTree which is a program using these weighted splits makes a phylogenetic network. In general, finding an optimal circular ordering is an NP-hard problem. The N-Net is a heuristic algorithm to find the optimal circular ordering which is based on neighbor-joining algorithm. Results. In this paper, we present a heuristic algorithm to find an optimal circular ordering based on the Monte-Carlo method, called MC-Net algorithm. In order to show that MC-Net performs better than N-Net, we apply both algorithms on different data sets. Then we draw phylogenetic networks corresponding to outputs of these algorithms using SplitsTree and compare the results. Conclusions. We find that the circular ordering produced by the MC-Net is closer to optimal circular ordering than the N-Net. Furthermore, the networks corresponding to outputs of MC-Net made by SplitsTree are simpler than N-Net. © 2010 Eslahchi et al; licensee BioMed Central Ltd."