ENHANCED BIO-INSPIRED ALGORITHM FOR CONSTRUCTING PHYLOGENETIC TREE
This paper illustrates an enhanced algorithm based on one of the swarm intelligence techniques for constructing the Phylogenetic tree (PT), which is used to study the relationship between species. The main scheme is to formulate a PT, an NP- complete problem through an evolutionary algorithm called...
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| Format: | Article |
| Language: | English |
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ICT Academy of Tamil Nadu
2015-10-01
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| Series: | ICTACT Journal on Soft Computing |
| Subjects: | |
| Online Access: | http://ictactjournals.in/paper/IJSC_V6_I1_paper_1_pp_1061_1069.pdf |
| _version_ | 1818573662003920896 |
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| author | J. Jayapriya Michael Arock |
| author_facet | J. Jayapriya Michael Arock |
| author_sort | J. Jayapriya |
| collection | DOAJ |
| description | This paper illustrates an enhanced algorithm based on one of the swarm intelligence techniques for constructing the Phylogenetic tree (PT), which is used to study the relationship between species. The main scheme is to formulate a PT, an NP- complete problem through an evolutionary algorithm called Artificial Bee Colony (ABC). The tradeoff between the accuracy and the computational time taken for constructing the tree makes way for new variants of algorithms. A new variant of ABC algorithm is proposed to promote the convergence rate of general ABC algorithm through recommending a new formula for searching solution. In addition, a searching step has been included so that it constructs the tree faster with a nearly optimal solution. Experimental results are compared with the ABC algorithm, Genetic Algorithm and the state-of-the-art techniques like unweighted pair group method using arithmetic mean, Neighbour-joining and Relaxed Neighbor Joining. For results discussion, we used one of the standard dataset Treesilla. The results show that the Enhanced ABC (EABC) algorithm converges faster than others. The claim is supported by a distance metric called the Robinson-Foulds distance that finds the dissimilarity of the PT, constructed by different algorithms. |
| first_indexed | 2024-12-15T00:14:30Z |
| format | Article |
| id | doaj.art-7de55ddb08424343a102cb31f70bf1fb |
| institution | Directory Open Access Journal |
| issn | 0976-6561 2229-6956 |
| language | English |
| last_indexed | 2024-12-15T00:14:30Z |
| publishDate | 2015-10-01 |
| publisher | ICT Academy of Tamil Nadu |
| record_format | Article |
| series | ICTACT Journal on Soft Computing |
| spelling | doaj.art-7de55ddb08424343a102cb31f70bf1fb2022-12-21T22:42:29ZengICT Academy of Tamil NaduICTACT Journal on Soft Computing0976-65612229-69562015-10-016110611069ENHANCED BIO-INSPIRED ALGORITHM FOR CONSTRUCTING PHYLOGENETIC TREEJ. Jayapriya0Michael Arock1National Institute of Technology, Tiruchirappalli, IndiaNational Institute of Technology, Tiruchirappalli, IndiaThis paper illustrates an enhanced algorithm based on one of the swarm intelligence techniques for constructing the Phylogenetic tree (PT), which is used to study the relationship between species. The main scheme is to formulate a PT, an NP- complete problem through an evolutionary algorithm called Artificial Bee Colony (ABC). The tradeoff between the accuracy and the computational time taken for constructing the tree makes way for new variants of algorithms. A new variant of ABC algorithm is proposed to promote the convergence rate of general ABC algorithm through recommending a new formula for searching solution. In addition, a searching step has been included so that it constructs the tree faster with a nearly optimal solution. Experimental results are compared with the ABC algorithm, Genetic Algorithm and the state-of-the-art techniques like unweighted pair group method using arithmetic mean, Neighbour-joining and Relaxed Neighbor Joining. For results discussion, we used one of the standard dataset Treesilla. The results show that the Enhanced ABC (EABC) algorithm converges faster than others. The claim is supported by a distance metric called the Robinson-Foulds distance that finds the dissimilarity of the PT, constructed by different algorithms.http://ictactjournals.in/paper/IJSC_V6_I1_paper_1_pp_1061_1069.pdfPhylogenetic TreesArtificial Bee Colony AlgorithmEdit DistanceConverges FasterGenetic Algorithm |
| spellingShingle | J. Jayapriya Michael Arock ENHANCED BIO-INSPIRED ALGORITHM FOR CONSTRUCTING PHYLOGENETIC TREE ICTACT Journal on Soft Computing Phylogenetic Trees Artificial Bee Colony Algorithm Edit Distance Converges Faster Genetic Algorithm |
| title | ENHANCED BIO-INSPIRED ALGORITHM FOR CONSTRUCTING PHYLOGENETIC TREE |
| title_full | ENHANCED BIO-INSPIRED ALGORITHM FOR CONSTRUCTING PHYLOGENETIC TREE |
| title_fullStr | ENHANCED BIO-INSPIRED ALGORITHM FOR CONSTRUCTING PHYLOGENETIC TREE |
| title_full_unstemmed | ENHANCED BIO-INSPIRED ALGORITHM FOR CONSTRUCTING PHYLOGENETIC TREE |
| title_short | ENHANCED BIO-INSPIRED ALGORITHM FOR CONSTRUCTING PHYLOGENETIC TREE |
| title_sort | enhanced bio inspired algorithm for constructing phylogenetic tree |
| topic | Phylogenetic Trees Artificial Bee Colony Algorithm Edit Distance Converges Faster Genetic Algorithm |
| url | http://ictactjournals.in/paper/IJSC_V6_I1_paper_1_pp_1061_1069.pdf |
| work_keys_str_mv | AT jjayapriya enhancedbioinspiredalgorithmforconstructingphylogenetictree AT michaelarock enhancedbioinspiredalgorithmforconstructingphylogenetictree |