A simulated annealing algorithm for finding consensus sequences

Motivation: A consensus sequence for a family of related sequences is, as the name suggests, a sequence that captures the features common to most members of the family. Consensus sequences are important in various DNA sequencing applications and are a convenient way to characterize a family of molecules. Results: This paper describes a new algorithm for finding a consensus sequence, using the popular optimization method known as simulated annealing. Unlike the conventional approach of finding a consensus sequence by first forming a multiple sequence alignment, this algorithm searches for a sequence that minimises the sum of pairwise distances to each of the input sequences. The resulting consensus sequence can then be used to induce a multiple sequence alignment. The time required by the algorithm scales linearly with the number of input sequences and quadratically with the length of the consensus sequence. We present results demonstrating the high quality of the consensus sequences and alignments produced by the new algorithm. For comparison, we also present similar results obtained using ClustalW. The new algorithm outperforms ClustalW in many cases.

Evolutionary experiments on mate recognition in the Drosophila serrata species complex

It is becoming increasingly apparent that at least some aspects of the evolution of mate recognition may be amenable to manipulation in evolutionary experiments. Quantitative genetic analyses that focus on the genetic consequences of evolutionary processes that result in mate recognition evolution may eventually provide an understanding of the genetic basis of the process of speciation. We review a series of experiments that have attempted to determine the genetic basis of the response to natural and sexual selection on mate recognition in the Drosophila serrata species complex. The genetic basis of mate recognition has been investigated at three levels: (1) between the species of D. serrata and D. birchii using interspecific hybrids, (2) between populations of D. serrata that are sympatric and allopatric with respect to D. birchii, and (3) within populations of D. serrata. These experiments suggest that it may be possible to use evolutionary experiments to observe important events such as the reinforcement of mate recognition, or the generation of the genetic associations that are central to many sexual selection models.

A monolithic smoothing-gap algorithm for contact-impact based on the signed distance function

A new algorithm has been developed for smoothing the surfaces in finite element formulations of contact-impact. A key feature of this method is that the smoothing is done implicitly by constructing smooth signed distance functions for the bodies. These functions are then employed for the computation of the gap and other variables needed for implementation of contact-impact. The smoothed signed distance functions are constructed by a moving least-squares approximation with a polynomial basis. Results show that when nodes are placed on a surface, the surface can be reproduced with an error of about one per cent or less with either a quadratic or a linear basis. With a quadratic basis, the method exactly reproduces a circle or a sphere even for coarse meshes. Results are presented for contact problems involving the contact of circular bodies. Copyright (C) 2002 John Wiley Sons, Ltd.

Neuro-angiostrongylosis in wild Black and Grey-headed flying foxes (Pteropus spp)

Objective To identify nematodes seen in histological sections of brains of flying foxes (fruit bats) and describe the associated clinical disease and pathology. Proceedures Gross and histological examination of brains from 86 free-living flying foxes with neurological disease was done as part of an ongoing surveillance program for Australian bat lyssavirus. Worms were recovered, or if seen in histological sections, extracted by maceration of half the brain and identified by microscopic examination. Histological archives were also reviewed. Results There was histological evidence of angiostrongylosis in 16 of 86 recently submitted flying foxes with neurological disease and in one archival case from 1992. In 10 flying foxes, worms were definitively identified as Angiostrongylus cantonensis fifth-stage larvae. A worm fragment and third stage larvae were identified as Angiostrongylus sp, presumably A cantonensis, in a further three cases. The clinical picture was dominated by paresis, particularly of the hind-limbs, and depression, with flying foxes surviving up to 22 days in the care of wildlife volunteers. Brains containing fifth-stage larvae showed a moderate to severe eosinophilic and granulomatous meningoencephalitis (n = 14), whereas there was virtually no inflammation of the brains of bats which died when infected with only smaller, third-stage larvae (n = 3). There was no histological evidence of pulmonary involvement. Conclusion This is the first report of the recovery and identification of A cantonensis from free-living Australian wildlife. While anglostrongylosis is a common cause of paresis in flying foxes, the initial clinical course cannot be differentiated from Australian bat lyssavirus infection, and wildlife carers should be urged not to attempt to rehabilitate flying foxes with neurological disease.

A subset-oriented algorithm for minimizing the number of steps required for synthesis of cyclic-peptide libraries

Libraries of cyclic peptides are being synthesized using combinatorial chemistry for high throughput screening in the drug discovery process. This paper describes the min_syn_steps.cpp program (available at http://www.imb.uq.edu.au/groups/smythe/tran), which after inputting a list of cyclic peptides to be synthesized, removes cyclic redundant sequences and calculates synthetic strategies which minimize the synthetic steps as well as the reagent requirements. The synthetic steps and reagent requirements could be minimized by finding common subsets within the sequences for block synthesis. Since a brute-force approach to search for optimum synthetic strategies is impractically large, a subset-orientated approach is utilized here to limit the size of the search. (C) 2002 Elsevier Science Ltd. All rights reserved.

An augmented Lanczos algorithm for the efficient computation of a dot-product of a function of a large sparse symmetric matrix

The Lanczos algorithm is appreciated in many situations due to its speed. and economy of storage. However, the advantage that the Lanczos basis vectors need not be kept is lost when the algorithm is used to compute the action of a matrix function on a vector. Either the basis vectors need to be kept, or the Lanczos process needs to be applied twice. In this study we describe an augmented Lanczos algorithm to compute a dot product relative to a function of a large sparse symmetric matrix, without keeping the basis vectors.

The tree cut and merge algorithm for estimation of network reliability

This article presents Monte Carlo techniques for estimating network reliability. For highly reliable networks, techniques based on graph evolution models provide very good performance. However, they are known to have significant simulation cost. An existing hybrid scheme (based on partitioning the time space) is available to speed up the simulations; however, there are difficulties with optimizing the important parameter associated with this scheme. To overcome these difficulties, a new hybrid scheme (based on partitioning the edge set) is proposed in this article. The proposed scheme shows orders of magnitude improvement of performance over the existing techniques in certain classes of network. It also provides reliability bounds with little overhead.

A genetic algorithm/method of moments approach to the optimization of an RF coil for MRI applications - Theoretical considerations - Abstract

A Combined Genetic Algorithm and Method of Moments design methods is presented for the design of unusual near-field antennas for use in Magnetic Resonance Imaging systems. The method is successfully applied to the design of an asymmetric coil structure for use at 190MHz and demonstrates excellent radiofrequency field homogeneity.

Mapping the royal road and other hierarchical functions

In this paper we present a technique for visualising hierarchical and symmetric, multimodal fitness functions that have been investigated in the evolutionary computation literature. The focus of this technique is on landscapes in moderate-dimensional, binary spaces (i.e., fitness functions defined over {0, 1}(n), for n less than or equal to 16). The visualisation approach involves an unfolding of the hyperspace into a two-dimensional graph, whose layout represents the topology of the space using a recursive relationship, and whose shading defines the shape of the cost surface defined on the space. Using this technique we present case-study explorations of three fitness functions: royal road, hierarchical-if-and-only-if (H-IFF), and hierarchically decomposable functions (HDF). The visualisation approach provides an insight into the properties of these functions, particularly with respect to the size and shape of the basins of attraction around each of the local optima.

Automated traffic route identification through the shared nearest neighbour algorithm

Many organisations need to extract useful information from huge amounts of movement data. One example is found in maritime transportation, where the automated identification of a diverse range of traffic routes is a key management issue for improving the maintenance of ports and ocean routes, and accelerating ship traffic. This paper addresses, in a first stage, the research challenge of developing an approach for the automated identification of traffic routes based on clustering motion vectors rather than reconstructed trajectories. The immediate benefit of the proposed approach is to avoid the reconstruction of trajectories in terms of their geometric shape of the path, their position in space, their life span, and changes of speed, direction and other attributes over time. For clustering the moving objects, an adapted version of the Shared Nearest Neighbour algorithm is used. The motion vectors, with a position and a direction, are analysed in order to identify clusters of vectors that are moving towards the same direction. These clusters represent traffic routes and the preliminary results have shown to be promising for the automated identification of traffic routes with different shapes and densities, as well as for handling noise data.