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.     

A simulated annealing algorithm for maximum likelihood pedigree reconstruction

The calculation of maximum likelihood pedigrees for related organisms using genotypic data is considered. The problem is formulated so that the domain of optimization is a permutation space. This is a feature shared by the travelling salesman problem, for which simulated annealing is known to be effective. Using this technique it is found that pedigrees can be reconstructed with minimal error using genotypic data of a quality currently realizable. In complex pedigrees accurate reconstruction can be done with no a priori age or sex information. For smaller numbers of individuals a method of efficiently enumerating all admissible pedigrees of nonzero likelihood is given.     

Applications of simulated annealing to peptides

We report the application of a new conformation searching algorithm called simulated annealing to the location of the global minimum energy conformation of peptides. Simulated annealing is a Metropolis Monte Carlo approach to conformation generation in which both the energy and temperature dependence of the Boltzmann distribution guides the search for the global minimum. Both uphill and downhill moves are possible, which allows the molecule to escape from local minima. Applications to the 20 natural amino acid "dipeptide models" as well as to polyalanines up to Ala80 are very successful in finding the lowest energy conformation. A history file of the simulated annealing process allows reconstruction and examination of the random walk around conformation space. A separate program, Conf-Gen, reads the history file and extracts all low-energy conformations visited during the run.     

ODS: ordering DNA sequences--a physical mapping algorithm based on simulated annealing

In the program ODS we provide a methodology for quickly orderingrandom clones into a physical map. The process of ordering individualclones with respect to their position along a chromosome isbased on the similarity of binary signatures assigned to eachclone. This binary signature is obtained by hybridizing eachclone to a panel of oligonucleotide probes. By using the factthat the amount of overlap between any two clones is reflectedin the similarity of their binary signatures, it is possibleto reconstruct a chromosome by minimizing the sum of linkingdistances between an ordered sequence of clones. Unlike otherprograms for physical mapping, ODS is very general in the typesof data that can be utilized for chromosome reconstruction.Any trait that can be scored in a presence–absence manner,such as hybridized synthetic oligonucleotides, restriction endonucleaserecognition sites or single copy landmarks, can be used foranalysis. Furthermore, the computational requirements for theconstruction of large physical maps can be measured in a matterof hours on workstations such as the VAX2000.     

An approach to improve Wang-Smith chaotic simulated annealing

Previous research shows that Wang-Smith chaotic simulated annealing, which employs a gradually decreasing time-step, has only a scaling effect to computational energy of the Hopfield model without changing its shape. This makes the net has sensitive dependence on the value of damping factor. Considering Chen-Aihara chaotic simulated annealing with decaying self-coupling has a shape effect to computational energy of the Hopfield model, a novel approach to improve Wang-Smith chaotic simulated annealing, which reaps the benefits of Wang-Smith model and Chen-Aihara model, is proposed in this paper. With the aid of this method the improved model can affect on computational energy of the Hopfield model from scaling and shape. By adjusting the time-step, the improved neural network can also pass from a chaotic to a non-chaotic state. From numerical simulation experiments, we know that the improved model can escape from local minima more efficiently than original Wang-Smith model.     

基于模拟退火算法的高分辨率蛋白质质谱数据特征选择

蛋白质质谱技术是蛋白质组学的重要研究工具,它被出色地应用于癌症早期诊断等领域,但是蛋白质质谱数据带来的维灾难问题使得降维成为质谱分析的必需的步骤。本文首先将美国国家癌症研究所提供的高分辨率SELDI—TOF卵巢质谱数据进行预处理;然后将质谱数据的特征选择问题转化成基于模拟退火算法的组合优化模型,用基于线性判别式分析的分类错误率和样本后验概率构造待优化目标函数,用基于均匀分布和控制参数的方法构造新解产生器,在退火过程中添加记忆功能;然后用10-fold交叉验证法选择训练和测试样本,用线性判别式分析分类器评价降维后的质谱数据。实验证明,用模拟退火算法选择6个以上特征时,能够将高分辨率SELDI—TOF卵巢质谱数据全部正确分类,说明模拟退火算法可以很好地应用于蛋白质质谱数据的特征选择。     

A novel algorithm for alignment of multiple PPI networks based on simulated annealing

Background

To infer gene regulatory networks (GRNs) from gene-expression data is still a fundamental and challenging problem in systems biology. Several existing algorithms formulate GRNs inference as a regression problem and obtain the network with an ensemble strategy. Recent studies on data driven dynamic network construction provide us a new perspective to solve the regression problem.

Results

In this study, we propose a data driven dynamic network construction method to infer gene regulatory network (D3GRN), which transforms the regulatory relationship of each target gene into functional decomposition problem and solves each sub problem by using the Algorithm for Revealing Network Interactions (ARNI). To remedy the limitation of ARNI in constructing networks solely from the unit level, a bootstrapping and area based scoring method is taken to infer the final network. On DREAM4 and DREAM5 benchmark datasets, D3GRN performs competitively with the state-of-the-art algorithms in terms of AUPR.

Conclusions

We have proposed a novel data driven dynamic network construction method by combining ARNI with bootstrapping and area based scoring strategy. The proposed method performs well on the benchmark datasets, contributing as a competitive method to infer gene regulatory networks in a new perspective.

     

Automated docking of substrates to proteins by simulated annealing

The Metropolis technique of conformation searching is combined with rapid energy evaluation using molecular affinity potentials to give an efficient procedure for docking substrates to macromolecules of known structure. The procedure works well on a number of crystallographic test systems, functionally reproducing the observed binding modes of several substrates.     

Applications of simulated annealing to the multiple-minima problem in small peptides

A Simulated Annealing method has been implemented to overcome the multiple minima problem inherent in finding the global minimum of small peptides with 2, 3, 5, 10 and 24 dihedral angles. The algorithm works much better if one introduces the anticorrelations observed in Molecular Dynamics.     

Comparison of methods to identify individuals at increased risk of coronary disease from the general population

Objectives To evaluate the guidelines on measurement of cholesterol in the national service framework for coronary heart disease and to compare alternative strategies for identifying people at high risk of coronary disease in the general population.Design Comparison of methods (national service framework criteria, Sheffield tables, age threshold of 50 years, estimated risk assessment using fixed cholesterol values) for identifying people with a 10 year coronary event risk of 15% or greater.Setting Health survey for England 1998.Subjects 6307 people aged between 30 and 74 years with no history of myocardial infarction, stroke, or angina.Main outcome measures Proportion of the total population selected for measurement of cholesterol and proportion of people at 15% or greater risk identified.Results The national service framework guidelines selected 43.4% (95% confidence interval 42.2% to 44.6%) of the study population for cholesterol measurement and identified 81.2% (80.2% to 82.2%) of those at 15% or greater risk. The Sheffield tables selected 73.1% (72.0% to 74.2%) for cholesterol measurement and identified 99.91% (99.83% to 99.99%) of those at 15% or greater risk. An age threshold of 50 years selected 46.3% (45.1% to 47.5%) for cholesterol measurement and identified 92.8% (92.1% to 93.4%) of those at 15% or greater risk. Estimated risk assessments using fixed cholesterol values selected 17.8% (16.8% to 18.7%) for cholesterol measurement and identified 75.9% (74.8% to 76.9%) of those at 15% or greater risk.Conclusion Measuring the cholesterol concentration of everyone aged 50 years and over is a simple and efficient method of identifying people at high risk of coronary disease in the general population.     

A general Monte Carlo/simulated annealing algorithm for resonance assignment in NMR of uniformly labeled biopolymers

We describe a general computational approach to site-specific resonance assignments in multidimensional NMR studies of uniformly ¹⁵N,¹³C-labeled biopolymers, based on a simple Monte Carlo/simulated annealing (MCSA) algorithm contained in the program MCASSIGN2. Input to MCASSIGN2 includes lists of multidimensional signals in the NMR spectra with their possible residue-type assignments (which need not be unique), the biopolymer sequence, and a table that describes the connections that relate one signal list to another. As output, MCASSIGN2 produces a high-scoring sequential assignment of the multidimensional signals, using a score function that rewards good connections (i.e., agreement between relevant sets of chemical shifts in different signal lists) and penalizes bad connections, unassigned signals, and assignment gaps. Examination of a set of high-scoring assignments from a large number of independent runs allows one to determine whether a unique assignment exists for the entire sequence or parts thereof. We demonstrate the MCSA algorithm using two-dimensional (2D) and three-dimensional (3D) solid state NMR spectra of several model protein samples (α-spectrin SH3 domain and protein G/B1 microcrystals, HET-s_218–289 fibrils), obtained with magic-angle spinning and standard polarization transfer techniques. The MCSA algorithm and MCASSIGN2 program can accommodate arbitrary combinations of NMR spectra with arbitrary dimensionality, and can therefore be applied in many areas of solid state and solution NMR.     

Constructing linkage maps in autotetraploid species using simulated annealing

In this paper we demonstrate how molecular markers segregating in a full-sib autotetraploid mapping population can be ordered to form a linkage map using simulated annealing. This approach facilitates the examination of orders close to the optimum to see which marker placings are fixed and identify the markers whose position is less certain. A simulation study investigates the effects of population size, marker spacing, ratio of dominant to codominant markers, typing errors and missing values. The method is applied to map 30 amplified fragment length polymorphism and microsatellite markers on linkage group IV of potato.     

An exploratory algorithm to identify intra-host recombinant viral sequences

Since recombination leads to the generation of mosaic genomes that violate the assumption of traditional phylogenetic methods that sequence evolution can be accurately described by a single tree, results and conclusions based on phylogenetic analysis of data sets including recombinant sequences can be severely misleading. Many methods are able to adequately detect recombination between diverse sequences, for example between different HIV-1 subtypes. More problematic is the identification of recombinants among closely related sequences such as a viral population within a host. We describe a simple algorithmic procedure that enables detection of intra-host recombinants based on split-decomposition networks and a robust statistical test for recombination. By applying this algorithm to several published HIV-1 data sets we conclude that intra-host recombination was significantly underestimated in previous studies and that up to one-third of the env sequences longitudinally sampled from a given subject can be of recombinant origin. The results show that our procedure can be a valuable exploratory tool for detection of recombinant sequences before phylogenetic analysis, and also suggest that HIV-1 recombination in vivo is far more frequent and significant than previously thought.     

Relative efficiency of haplotype frequency estimation in sibships and nuclear families compared to unrelated individuals

The problem of estimating haplotype frequencies from unphased single nucleotide polymorphism (SNP) genotype data in sibships with and without parents is considered. We focus on the Fisher information of the haplotype frequencies of the parents in order to correctly deal with the dependence of haplotypes within sibships. We compare these Fisher information matrices with those obtained for unrelated individuals and study the relative efficiency of sibships with and without parents compared to unrelated individuals in estimating haplotype frequencies. Crudely summarizing, the second sib contributes half the information of the first, except for rare haplotypes, when the second sib counts almost as one. We argue that the relative efficiencies can also be used to correct for dependence in the calculation of standard errors after initially ignoring the dependence in the estimation phase.     

Genome-wide eQTLs and heritability for gene expression traits in unrelated individuals

Background

While the possible sources underlying the so-called ‘missing heritability’ evident in current genome-wide association studies (GWAS) of complex traits have been actively pursued in recent years, resolving this mystery remains a challenging task. Studying heritability of genome-wide gene expression traits can shed light on the goal of understanding the relationship between phenotype and genotype. Here we used microarray gene expression measurements of lymphoblastoid cell lines and genome-wide SNP genotype data from 210 HapMap individuals to examine the heritability of gene expression traits.

Results

Heritability levels for expression of 10,720 genes were estimated by applying variance component model analyses and 1,043 expression quantitative loci (eQTLs) were detected. Our results indicate that gene expression traits display a bimodal distribution of heritability, one peak close to 0% and the other summit approaching 100%. Such a pattern of the within-population variability of gene expression heritability is common among different HapMap populations of unrelated individuals but different from that obtained in the CEU and YRI trio samples. Higher heritability levels are shown by housekeeping genes and genes associated with cis eQTLs. Both cis and trans eQTLs make comparable cumulative contributions to the heritability. Finally, we modelled gene-gene interactions (epistasis) for genes with multiple eQTLs and revealed that epistasis was not prevailing in all genes but made a substantial contribution in explaining total heritability for some genes analysed.

Conclusions

We utilised a mixed effect model analysis for estimating genetic components from population based samples. On basis of analyses of genome-wide gene expression from four HapMap populations, we demonstrated detailed exploitation of the distribution of genetic heritabilities for expression traits from different populations, and highlighted the importance of studying interaction at the gene expression level as an important source of variation underlying missing heritability.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-13) contains supplementary material, which is available to authorized users.     

Variability in susceptibility to simulated sunlight of conidia among isolates of entomopathogenic Hyphomycetes

The influence of simulated sunlight on survival of conidia of 4 species of entomopathogenic Hyphomycetes was investigated. Conidia from 65 isolates ofBeauveria bassiana, 23 ofMetarhizium anisopliae, 14 ofMetarhizium flavoviride and 33 isolates ofPaecilomyces fumosoroseus were irradiated by artificial sunlight (295 to 1,100 nm at an ultraviolet-B irradiance of 0.3 W m^–2) for 0, 1, 2, 4 and 8 h. Survival was estimated by comparing the number of colony forming units (CFU) produced by conidia exposed to irradiation to the number of CFUs produced by an unexposed control. Survival decreased with increased exposure to simulated sunlight; exposure for 2 h or more was detrimental to all isolates tested. Overall, isolates ofM. flavoviride were the most resistant to irradiation followed byB. bassiana andM. anisopliae. Conidia ofP. fumosoroseus were most susceptible. In addition to the large interspecies differences in susceptibility to irradiation, there was also an intraspecies variation indicating that strain selection to irradiation tolerance may be important in the development of microbial control agents where increased persistence in an insolated environment is desirable.Abbreviations CFU Colony forming units - UV-B ultraviolet radiation-B     

Analyses to help identify individuals from a historical mass grave in Kassel, Germany

In 2008, the skeletal remains of more than 60 human individuals were found in a mass grave on the grounds of the University of Kassel, Germany. There was no evidence helping to identify them or throwing light on the cause of their death. Mainly due to 14C age determination and initial hints on age and sex distribution, historians hypothesized that they had been soldiers of Napoleon's army who died in an epidemic in the winter of 1813/14. To test this assumption, morphological and molecular analyses were carried out on a sample. The morphological analyses comprised an age and sex determination as well as a macro- and micro-morphological inspection for pathological deviations after the commingled bones had been assembled as individuals. The molecular investigations aimed to identify the geographic origin of the remains. For this, mitochondrial and Y-chromosomal haplotypings were carried out. The results point to a group of mainly young men, some of them suffering from systemic inflammation of the periosteum. Others revealed severe aberrations in bone microstructure. The greatest similarities revealed by Y-haplogroup and -haplotype distribution were to populations that live in what are now the Benelux countries. All aspects support the thesis that these were soldiers of the Napoleonic army.