Pairwise Distance Calculation Research Articles

Aplikasi Kajian DNA Molekuler dan Fenotipik Pada Program Pelepasliaran Burung Kakatua

ABSTRACT There are six species of cockatoos in Indonesia which are well known as exotic, smart, and they can be trained in a variety of attractions. Thus, many people want to keep those birds as pets. All of pets which have been kept by community should be evaluated from various aspects before being reintroduced to their natural habitat. The examination of sex and species of illegal cocktoos play as a key role for the reintroduction programme. The objective of this study was to evaluate the reliability and effectivity of evaluation technique of morphometric and molecular for reintroduction programme of cockatoos. We used the COI gene sequences from 68 individuals of cockatoos from pet communities in and around Jakarta and four sequences from GenBank. The phylogenetic analysis used the neighbor-joining method, in which the genetic distance matrix calculations with Kimura 2-parameter models that are implemented on a pairwise distance calculation in the MEGA program version 6:05. The result of the genetic variation of the cockatoo species which shows intraspecific divergence was Cacatua alba (n=4)= 0%, C. galerita (Australia n=9)= 0.6%, C. galerita (Indonesia n=53)= 0.3%, C .goffiniana (n=3)= 0%, C. moluccensis (n=7)= 0.1%, and C. sulphurea (n=2)= 0.3%, with a range of 0-0.6%. The results indicate that the average of intraspecific of COI in the cockatoos community was 0.25±0.055%, and interspecific divergences ranged from 3.1 to 11.6%. The phylogenetic tree shows the monophyletic clade of cockatoo species in Indonesia. In addition, DNA barcode analysis and molecular sexing could correct the error and doubts the result of five individual species identification and two individual sexing identification of C. galerita by morphological identification. The results of morphological examanation base on body weight, body length and head-bill length of C. galerita triton were not significantly different (P?0,5). Finally, 19 individuals C. galerita triton and two individuals P. aterrimus were reintroduced to their natural habitat. Keywords: cockatoo, barcodes DNA, reintroduction

Towards Fast Niching Evolutionary Algorithms: A Locality Sensitive Hashing-Based Approach

Niching techniques have recently been incorporated into evolutionary algorithms (EAs) for multisolution optimization in multimodal landscape. However, existing niching techniques inevitably increase the time complexity of basic EAs due to the computation of the distance matrix of individuals. In this paper, we propose a fast niching technique. The technique avoids pairwise distance calculations by introducing the locality sensitive hashing, an efficient algorithm for approximately retrieving nearest neighbors. Individuals are projected to a number of buckets by hash functions. The similar individuals possess a higher probability of being hashed into the same bucket than the dissimilar ones. Then, interactions between individuals are limited to the candidates that fall in the same bucket to achieve local evolution. It is proved that the complexity of the proposed fast niching is linear to the population size. In addition, this mechanism induces stable niching behavior and it inherently keeps a balance between the exploration and exploitation of multiple optima. The theoretical analysis conducted in this paper suggests that the proposed technique is able to provide bounds for the exploration and exploitation probabilities. Experimental results show that the fast niching versions of the multimodal algorithms can exhibit similar or even better performance than their original ones. More importantly, the execution time of the algorithms is significantly reduced.

Local density-based anomaly detection in hyperspectral image

A local density-based anomaly detection (LDAD) method is proposed. LDAD is a nonparameter model-based method, which utilizes the pixel’s local density in hyperspectral images as a criterion to determine the pixel’s anomalousness. In this method, the local density is calculated as a function of the spectral distance between pixels. Distinct from the statistical-based method, there are no assumptions made on the background distributions. Due to the pairwise distance calculation between pixels, LDAD’s computational complexity is quadratic to the total number of pixels. To improve the efficiency, an optimization strategy by pruning is implemented to reduce the unnecessary computational costs. Experiments on real hyperspectral image suggest that the proposed anomaly detector can achieve better detection performance than its counterparts, while keeping the computational cost relatively low by applying the optimization.

Estimating graph distance and centrality on shared nothing architectures

SummaryWe present a parallel toolkit for pairwise distance computation in massive networks. Computing the exact shortest paths between a large number of vertices is a costly operation, and serial algorithms are not practical for billion‐scale graphs. We first describe an efficient parallel method to solve the single source shortest path problem on commodity hardware with no shared memory. Using it as a building block, we introduce a new parallel algorithm to estimate the shortest paths between arbitrary pairs of vertices. Our method exploits data locality, produces highly accurate results, and allows batch computation of shortest paths with 7% average error in graphs that contain billions of edges. The proposed algorithm is up to two orders of magnitude faster than previously suggested algorithms and does not require large amounts of memory or expensive high‐end servers. We further leverage this method to estimate the closeness and betweenness centrality metrics, which involve systems challenges dealing with indexing, joining, and comparing large datasets efficiently. In one experiment, we mined a real‐world Web graph with 700 million nodes and 12 billion edges to identify the most central vertices and calculated more than 63 billion shortest paths in 6 h on a 20‐node commodity cluster. Copyright © 2014 John Wiley & Sons, Ltd.

Exploitation of Pairwise Class Distances for Ordinal Classification

Ordinal classification refers to classification problems in which the classes have a natural order imposed on them because of the nature of the concept studied. Some ordinal classification approaches perform a projection from the input space to one-dimensional (latent) space that is partitioned into a sequence of intervals (one for each class). Class identity of a novel input pattern is then decided based on the interval its projection falls into. This projection is trained only indirectly as part of the overall model fitting. As with any other latent model fitting, direct construction hints one may have about the desired form of the latent model can prove very useful for obtaining high-quality models. The key idea of this letter is to construct such a projection model directly, using insights about the class distribution obtained from pairwise distance calculations. The proposed approach is extensively evaluated with 8 nominal and ordinal classifiers methods, 10 real-world ordinal classification data sets, and 4 different performance measures. The new methodology obtained the best results in average ranking when considering three of the performance metrics, although significant differences are found for only some of the methods. Also, after observing other methods of internal behavior in the latent space, we conclude that the internal projections do not fully reflect the intraclass behavior of the patterns. Our method is intrinsically simple, intuitive, and easily understandable, yet highly competitive with state-of-the-art approaches to ordinal classification.

Spherical Stochastic Neighbor Embedding of Hyperspectral Data

In hyperspectral imagery, low-dimensional representations are sought in order to explain well the nonlinear characteristics that are hidden in high-dimensional spectral channels. While many algorithms have been proposed for dimension reduction and manifold learning in Euclidean spaces, very few attempts have focused on non-Euclidean spaces. Here, we propose a novel approach that embeds hyperspectral data, transformed into bilateral probability similarities, onto a nonlinear unit norm coordinate system. By seeking a unit <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> -norm nonlinear manifold, we encode similarity representations onto a space in which important regularities in data are easily captured. In its general application, the technique addresses problems related to dimension reduction and visualization of hyperspectral images. Unlike methods such as multidimensional scaling and spherical embeddings, which are based on the notion of pairwise distance computations, our approach is based on a stochastic objective function of spherical coordinates. This allows the use of an Exit probability distribution to discover the nonlinear characteristics that are inherent in hyperspectral data. In addition, the method directly learns the probability distribution over neighboring pixel maps while computing for the optimal embedding coordinates. As part of evaluation, classification experiments were conducted on the manifold spaces for hyperspectral data acquired by multiple sensors at various spatial resolutions over different types of land cover. Various visualization and classification comparisons to five existing techniques demonstrated the strength of the proposed approach while its algorithmic nature is guaranteed to converge to meaningful factors underlying the data.

Fast algorithm for population‐based protein structural model analysis

De novo protein structure prediction often generates a large population of candidates (models), and then selects near-native models through clustering. Existing structural model clustering methods are time consuming due to pairwise distance calculation between models. In this paper, we present a novel method for fast model clustering without losing the clustering accuracy. Instead of the commonly used pairwise root mean square deviation and TM-score values, we propose two new distance measures, Dscore1 and Dscore2, based on the comparison of the protein distance matrices for describing the difference and the similarity among models, respectively. The analysis indicates that both the correlation between Dscore1 and root mean square deviation and the correlation between Dscore2 and TM-score are high. Compared to the existing methods with calculation time quadratic to the number of models, our Dscore1-based clustering achieves a linearly time complexity while obtaining almost the same accuracy for near-native model selection. By using Dscore2 to select representatives of clusters, we can further improve the quality of the representatives with little increase in computing time. In addition, for large size (~500 k) models, we can give a fast data visualization based on the Dscore distribution in seconds to minutes. Our method has been implemented in a package named MUFOLD-CL, available at http://mufold.org/clustering.php.

Godzillius fuchsi, a new species of Remipedia (Godzilliidae) from Abaco Island, Bahamas

We describe a new species of Godzillius, a remipede belonging to Godzilliidae, discovered from Dan’s Cave and Ralph’s Sink, two inland anchialine blue holes on Abaco Island, Bahamas. Godzillius fuchsi n. sp. is the second species assigned to this genus. Collected adult specimens have a relatively robust body, with lengths measuring 34 mm and up to 28 trunk segments. The new species is distinguished from G. robustus in particular by the varying construction of the terminal claw complex on the cephalic limbs; having seven large teeth on the maxillae; and six large teeth separated by seven smaller teeth on the maxillipeds. The status of G. fuchsi as a distinct species was validated using pairwise distance calculations of COI sequences and that of previously published Bayesian analyses from selected remipede taxa, including G. robustus. Dan’s Cave and Ralph’s Sink are in very close proximity and likely are hydrologically connected. Godzillius fuchsi is the fifth remipede to be recorded from Dan’s Cave.

Clustering 100,000 Protein Structure Decoys in Minutes

Ab initio protein structure prediction methods first generate large sets of structural conformations as candidates (called decoys), and then select the most representative decoys through clustering techniques. Classical clustering methods are inefficient due to the pairwise distance calculation, and thus become infeasible when the number of decoys is large. In addition, the existing clustering approaches suffer from the arbitrariness in determining a distance threshold for proteins within a cluster: a small distance threshold leads to many small clusters, while a large distance threshold results in the merging of several independent clusters into one cluster. In this paper, we propose an efficient clustering method through fast estimating cluster centroids and efficient pruning rotation spaces. The number of clusters is automatically detected by information distance criteria. A package named ONION, which can be downloaded freely, is implemented accordingly. Experimental results on benchmark data sets suggest that ONION is 14 times faster than existing tools, and ONION obtains better selections for 31 targets, and worse selection for 19 targets compared to SPICKER’s selections. On an average PC, ONION can cluster 100,000 decoys in around 12 minutes.

A New Genomic Evolutionary Model for Rearrangements, Duplications, and Losses that Applies across Eukaryotes and Prokaryotes

Genomic rearrangements have been studied since the beginnings of modern genetics and models for such rearrangements have been the subject of many papers over the last 10 years. However, none of the extant models can predict the evolution of genomic organization into circular unichromosomal genomes (as in most prokaryotes) and linear multichromosomal genomes (as in most eukaryotes). Very few of these models support gene duplications and losses--yet these events may be more common in evolutionary history than rearrangements and themselves cause apparent rearrangements. We propose a new evolutionary model that integrates gene duplications and losses with genome rearrangements and that leads to genomes with either one (or a very few) circular chromosome or a collection of linear chromosomes. Our model is based on existing rearrangement models and inherits their linear-time algorithms for pairwise distance computation (for rearrangement only). Moreover, our model predictions fit observations about the evolution of gene family sizes and agree with the existing predictions about the growth in the number of chromosomes in eukaryotic genomes.

ESPRIT-Tree: hierarchical clustering analysis of millions of 16S rRNA pyrosequences in quasilinear computational time

Taxonomy-independent analysis plays an essential role in microbial community analysis. Hierarchical clustering is one of the most widely employed approaches to finding operational taxonomic units, the basis for many downstream analyses. Most existing algorithms have quadratic space and computational complexities, and thus can be used only for small or medium-scale problems. We propose a new online learning-based algorithm that simultaneously addresses the space and computational issues of prior work. The basic idea is to partition a sequence space into a set of subspaces using a partition tree constructed using a pseudometric, then recursively refine a clustering structure in these subspaces. The technique relies on new methods for fast closest-pair searching and efficient dynamic insertion and deletion of tree nodes. To avoid exhaustive computation of pairwise distances between clusters, we represent each cluster of sequences as a probabilistic sequence, and define a set of operations to align these probabilistic sequences and compute genetic distances between them. We present analyses of space and computational complexity, and demonstrate the effectiveness of our new algorithm using a human gut microbiota data set with over one million sequences. The new algorithm exhibits a quasilinear time and space complexity comparable to greedy heuristic clustering algorithms, while achieving a similar accuracy to the standard hierarchical clustering algorithm.

Non-maternal transmission is the major mode of ovine lentivirus transmission in a ewe flock: A molecular epidemiology study

Transmission of ovine progressive pneumonia virus (OPPV), a lentivirus of sheep, occurs through both maternal and non-maternal means. Currently, the contribution of each route to the overall flock OPPV prevalence is poorly understood since previous serological epidemiologic studies lacked the ability to accurately track routes of transmission within an infected flock. In this study, the amount of maternal OPP transmission was assessed in a naturally infected ewe flock by applying molecular analyses to proviral sequences derived from peripheral blood leukocytes of OPP positive dam–daughter pairs ( N = 40). Both proviral envelope ( env) and long terminal repeat (LTR) sequences, separately and combined, were utilized in the following 2 sequence analysis methods: phylogenetic analysis and pairwise distance calculations. True maternal transmission events were defined as agreement in 2 out of the 2 sequence analysis methods. Using this criterion, proviral env sequences resulted in a 14.3% maternal transmission frequency, and proviral LTR sequences resulted in a 10% maternal transmission frequency. Both proportions of maternal transmission varied significantly from equality ( P < 0.0001). This indicates that the remaining 85.7–90% of daughters are infected via non-maternal transmission. This is also the first study to calculate the OPP proviral rate of change for the env gene and LTR promoter. Accurately defining the routes of OPPV transmission provides critical epidemiological data supporting management intended to reduce flock transmission and viral dose.

Phylogenetic analysis of the pathogenic bacteria Spiroplasma penaei based on multilocus sequence analysis

A pathogenic Spiroplasma penaei strain was isolated from the hemolymph of moribund Pacific white shrimp, Penaeus vannamei. The shrimp sample originated from a shrimp farm near Cartagena, Colombia, that was suffering from high mortalities in ponds with very low salinity and high temperatures. This new emerging disease in a marine crustacean in the Americas is described as a systemic infection. The multilocus phylogenetic analysis suggests that S. penaei strain has a terrestrial origin. Evolutionary relationship trees, based on five partial DNA sequences of 16S rDNA, 23S rDNA, 5S rDNA, gyrB, rpoB genes and two complete DNA sequences of 16S–23S rDNA and 23S–5S rDNA intergenic spacer region, were reconstructed using the distance-based Neighboring-Joining (NJ) method with Kimura-2-parameter substitution model. The NJ trees based on all DNA sequences investigated in this study positioned S. penaei in the Citri–Poulsonii clade and corroborate the observations by other investigators using the 16S rDNA gene. Pairwise genetic distance calculation between sequences of spiroplasmas showed S. penaei to be closely related to Spiroplasma insolitum and distantly related to Spiroplasma sp. SHRIMP from China.

SPAR profiles and genetic diversity amongst pomegranate (Punica granatum L.) genotypes

We are interested in studying the distribution and range of diversity amongst the pomegranates in India. Single Primer Amplification Reaction (SPAR) profiling using Random Amplified Polymorphic DNA (RAPD) and Directed Amplification of Minisatellite DNA (DAMD) methods enabled the determination of the genetic diversity amongst a total of 64 Indian pomegranate genotypes including 15 wild, 34 semi-wild and 14 cultivated types. SPAR profile data were scored for the computation of pairwise distances as well as a Neighbour Joining (NJ) tree of all the genotypes. Eight RAPD and four DAMD primers showed discrete polymorphic patterns amongst these genotypes. From the profiles obtained with all the 12 primers considered together, 259 bands were scored. The NJ tree generated after a 1000 bootstrap test using Jaccard coefficient showed separation of Lagerstroemia speciosa used as the out-group taxon, while the pomegranate genotypes were resolved into distinct genetic lineages such that all the cultivated (except CBd70), and wild genotypes (except W101) clearly separated from other genotypes in distinct sub clusters while the semi-wild genotypes were resolved into three sub-clusters. The greatest and least distances detected between genotypes were 0.94 and 0.12, 0.97 and 0.24 and 0.95 and 0.38, amongst the cultivated, semi-wild and the wild genotypes respectively. The results indicate the high levels of genetic diversity present amongst the genotypes. Significantly, the wild genotypes also have a reasonably good range of diversity. A good germplasm collection, especially including the wild genotypes will enable a better pomegranate improvement program. Both SPAR methods, RAPD and DAMD, are found to be useful for studying the genetic diversity of pomegranate.

Genetic Analysis of the Flagella Gene of Lyme Disease Spirochetes ( Borrelia burgdorferi) Isolated from the Offshore Kinmen Island of Taiwan

The flagella gene of Lyme disease spirochetes (Borrelia burgdorferi) was analyzed for the first time in Taiwan. The genetic identities of these Taiwan isolates (TWKM17) were clarified by comparing their sequence similarities and nucleotide distance values of the PCR-amplified flagella genes with three major genospecies of Lyme disease spirochetes for human infection and other zoonotic species of Borrelia spirochetes. Results from 26 isolates indicate that the sequence similarity of these Taiwan isolates revealed a highly homogeneous genotype, ranging from 99.3% to 100%, within the genospecies of B. burgdorferi sensu stricto and was distinguished from other genospecies of Borrelia isolates. Moreover, the nucleotide distance values performed by a pairwise distance calculation (Kimura 2-parameter distance) revealed a highly homogeneity ( 0.05) among other genospecies of spirochetes. The phylogenetic analysis also demonstrated that all these Taiwan isolates were closely related to the genospecies of B. burgdorferi sensu stricto within the same phylogenic group of B. burgdorferi sensu lato and can be clearly distinguished from other zoonotic species of Borrelia isolates. Thus, we conclude that all these Taiwan isolates should be classified into the genospecies of B. burgdorferi sensu stricto based on the genetic identity of the flagella gene.

COMPUTING THE ALL-PAIRS QUARTET DISTANCE ON A SET OF EVOLUTIONARY TREES

We present two algorithms for calculating the quartet distance between all pairs of trees in a set of binary evolutionary trees on a common set of species. The algorithms exploit common substructure among the trees to speed up the pairwise distance calculations, thus performing significantly better on large sets of trees compared to performing distinct pairwise distance calculations, as we illustrate experimentally, where we see a speedup factor of around 130 in the best case.

Fast Switching Filter for Impulsive Noise Removal from Color Images

In this paper, we present a fast switching filter for impulsive noise removal from color images. The filter exploits the HSL color space, and is based on the peer group concept, which allows for the fast detection of noise in a neighborhood without resorting to pairwise distance computations between each pixel. Experiments on large set of diverse images demonstrate that the proposed approach is not only extremely fast, but also gives excellent results in comparison to various state-of-the-art filters.

Plasmodium (Haemamoeba) cathemerium gene sequences for phylogenetic analysis of malaria parasites

The DNA sequence information on avian malaria parasites of the genus Plasmodium is quite limited. At present, sequences of only 6 out of 34 valid species are available. However, sequence data of avian malaria parasites are particularly important with regard to the resolution of the phylogenetic relationships of the most virulent human malaria agent, Plasmodium falciparum. The question as to whether P. falciparum originates from avian or from mammalian parasites would contribute to our understanding of its biology and would probably facilitate the interpretation of experimental results. To add to the body of molecular data, we sequenced three genes (cytochrome b, 18 SSU rRNA, caseinolytic protease C) of different organellar origin of one of the most widespread avian malaria parasites, Plasmodium (Haemamoeba) cathemerium, which once used to be an important laboratory in vivo model in human malaria research. The analysis of the new P. cathemerium sequences in direct comparison with the rodent parasite P. berghei and the four human malaria parasites by pairwise distance calculation do not suggest a closer relationship of P. cathemerium to P. falciparum than to the other species involved.

Genetic diversity estimates in Cicer using AFLP analysis

AbstractAmplified fragment length polymorphism (AFLP) analysis was used to evaluate the genetic variation among cultivated chickpea and wild Cicer relatives. In total, 214 marker loci were assessed, of which 211 were polymorphic (98.6%) across the 95 accessions that represented 17 species of Cicer. The genetic variation within a species was highest in C. pinnatifidum followed by C. reticulatum and lowest in C. macracanthum. Three main species groups were identified by UPGMA clustering using Nei's pair‐wise distance calculations. Group I included the cultivated species C. arietinum, C. reticulatum and C. echinospermum. Within this group, C. reticulatum accessions were clustered closest to the C. arietinum cultivars ‘Lasseter’, ‘Kaniva’ and ‘Bumper’, supporting the hypothesis that C. reticulatum is the most probable progenitor of the cultivated species. Cicer bijugum, C. judaicum and C. pinnatifidum were clustered together creating group II. Group III contained all nine perennial species assessed and two annual species C. yamashitae and C. cuneatum. The genetic distance detected between group I and group III (0.13) was equivalent to the genetic distance detected between group I and group II (the primary and annual tertiary species, respectively; 0.14). This indicated that the perennial tertiary species may be as valuable for increasing variation to incorporate novel germplasm in the cultigen as the annual tertiary species.

FAST CLUSTERING AND MINIMUM WEIGHT MATCHING ALGORITHMS FOR VERY LARGE MOBILE BACKBONE WIRELESS NETWORKS

Mobile Backbone Wireless Networks (MBWN) [10] are wireless networks in which the base stations are mobile. Our strategy is the following: mobile nodes are dynamically grouped into clusters of bounded radius. In the very large wireless networks we deal with we deal with, several hundreds of clusters may be generated. Clustering makes use of a two dimensional Euclidean version of the Antipole Tree data structure [5]. This very effective structure was originally designed for finite sets of points in an arbitrary metric space to support efficient range searching. It requires only a linear number of pair-wise distance calculations among nodes. Mobile Base Stations occupy an approximate centroid of the clusters and are moved according to a fast practical bipartite matching algorithm which tries to minimize both total and maximum distance. We show that the best known computational geometry algorithms [1] become infeasible for our application when a high number of mobile base stations is required. On the other hand our proposed 8% average error solution requires O (k log k) running time instead of the approximatively O (k2) exact algorithm [1]. Communication among nodes is realized by a Clusterhead Gateway Switching Routing (CGSR) protocol [15] where the mobile base stations are organized in a suitable network. Other efficient clustering algorithms [11, 17] may be used instead of the Antipole Tree. However the nice hierarchical structure of the Antipole Tree makes it applicable to other types of mobile wireless (Ad-Hoc) and wired networks but this will be subject of future work.