Ant-Based Phylogenetic Reconstruction (ABPR): A new distance algorithm for phylogenetic estimation based on ant colony optimization

Abstract

We propose a new distance algorithm for phylogenetic estimation based on Ant Colony Optimization (ACO), named Ant-Based Phylogenetic Reconstruction (ABPR). ABPR joins two taxa iteratively based on evolutionary distance among sequences, while also accounting for the quality of the phylogenetic tree built according to the total length of the tree. Similar to optimization algorithms for phylogenetic estimation, the algorithm allows exploration of a larger set of nearly optimal solutions. We applied the algorithm to four empirical data sets of mitochondrial DNA ranging from 12 to 186 sequences, and from 898 to 16,608 base pairs, and covering taxonomic levels from populations to orders. We show that ABPR performs better than the commonly used Neighbor-Joining algorithm, except when sequences are too closely related (e.g., population-level sequences). The phylogenetic relationships recovered at and above species level by ABPR agree with conventional views. However, like other algorithms of phylogenetic estimation, the proposed algorithm failed to recover expected relationships when distances are too similar or when rates of evolution are very variable, leading to the problem of long-branch attraction. ABPR, as well as other ACO-based algorithms, is emerging as a fast and accurate alternative method of phylogenetic estimation for large data sets.

New Approach of Bellman Ford Algorithm on GPU using Compute Unified Design Architecture (CUDA)

“…Create edge_strt_node(Sa), edge_end_node (Ea), edge_weight (Wa) and node_weight (Na) from G (V, E, W) [1] for each vertex V in parallel do [2] Invoke INITNODEWEIGHT (Na, S) [3] end for [4] for i = 0 toV-1 do [5] for each edge E in parallel do [6] Invoke RELAX (Na, Sa, Ea, Wa) [7] end for [8] end for Basic Bellman Ford algorithm consists of two kernels as a part of its implementation.…”

“…Create Flag (F1) and Flag (F2) [1] for each vertex v in parallel do [2] Invoke INITNODEWEIGHT (Na, S, F1, F2)…”

“…Graphs are the commonly used data structures that describe a set of objects as nodes and the connections between them as edges. A large number of graph operations are present, such as minimum spanning tree, breadth-first search, shortest path etc., having applications in different problem domains like VLSI chip layout [1], phylogeny reconstruction [2] , data mining, and network analysis [3].…”