Using an evolutionary algorithm and parallel computing for haplotyping in a general complex pedigree with multiple marker loci

Background  

Haplotype reconstruction is important in linkage mapping and association mapping of quantitative trait loci (QTL). One widely used statistical approach for haplotype reconstruction is simulated annealing (SA), implemented in SimWalk2. However, the algorithm needs a very large number of sequential iterations, and it does not clearly show if convergence of the likelihood is obtained.     

Optimization of feeding profile for a fed-batch bioreactor by an evolutionary algorithm

The optimal feeding profile of a fed batch process was designed by means of an evolutionary algorithm. The algorithm chromosomes include the real-valued parameters of a profile function, defined by previous knowledge. Each chromosome is composed of the parameters that define the feeding profile: the feed rates, the singular arc parameters and the switching times between the profile states. The feed profile design was tested on a fed-batch process simulation. The accepted profiles were smooth and similar to those derived analytically in other studies. Two selection functions, roulette wheel and geometric ranking, were compared. In order to overcome the problem of model mismatches, a novel optimization scheme was carried out. During its operation the process was sampled, the model was updated and the optimization procedure was applied. The on-line optimization showed improvement in the objective function for relatively low sample times. Choosing the sampling frequencies depends on the process dynamics and the time required for the measurements and optimization. Further study on experiments of fed-batch process demonstrated the use of complex, non-differentiable model and produced improved process performances using the optimal feeding profile.     

Study of the genetic code adaptability by means of a genetic algorithm

We used simulated evolution to study the adaptability level of the canonical genetic code. An adapted genetic algorithm (GA) searches for optimal hypothetical codes. Adaptability is measured as the average variation of the hydrophobicity that the encoded amino acids undergo when errors or mutations are present in the codons of the hypothetical codes. Different types of mutations and point mutation rates that depend on codon base number are considered in this study. Previous works have used statistical approaches based on randomly generated alternative codes or have used local search techniques to determine an optimum value. In this work, we emphasize what can be concluded from the use of simulated evolution considering the results of previous works. The GA provides more information about the difficulty of the evolution of codes, without contradicting previous studies using statistical or engineering approaches. The GA also shows that, within the coevolution theory, the third base clearly improves the adaptability of the current genetic code.     

Inferring the evolutionary history of vibrios by means of multilocus sequence analysis

We performed the first broad study aiming at the reconstruction of the evolutionary history of vibrios by means of multilocus sequence analysis of nine genes. Overall, 14 distinct clades were recognized using the SplitsTree decomposition method. Some of these clades may correspond to families, e.g., the clades Salinivibrio and Photobacteria, while other clades, e.g., Splendidus and Harveyi, correspond to genera. The common ancestor of all vibrios was estimated to have been present 600 million years ago. We can define species of vibrios as groups of strains that share >95% gene sequence similarity and >99.4% amino acid identity based on the eight protein-coding housekeeping genes. The gene sequence data were used to refine the standard online electronic taxonomic scheme for vibrios (http://www.taxvibrio.lncc.br).     

Inference of Euler angles for single-particle analysis by means of evolutionary algorithms

Single-particle analysis is one of the methods for structural studies of protein and macromolecules; it requires advanced image analysis of electron micrographics. Reconstructing three-dimensional (3D) structure from microscope images is not an easy analysis because of the low image resolution of images and lack of the directional information of images in 3D structure. To improve the resolution, different projections are aligned, classified, and averaged. Inferring the orientations of these images is so difficult that the task of reconstructing 3D structures depends upon the experience of researchers. But recently, a method to reconstruct 3D structures was automatically devised. In this paper, we propose a new method for determining Euler angles of projections by applying genetic algorithms. We empirically show that the proposed approach has improved the previous one in terms of computational time and acquired precision.     

Regulatory motif discovery using a population clustering evolutionary algorithm

This paper describes a novel evolutionary algorithm for regulatory motif discovery in DNA promoter sequences. The algorithm uses data clustering to logically distribute the evolving population across the search space. Mating then takes place within local regions of the population, promoting overall solution diversity and encouraging discovery of multiple solutions. Experiments using synthetic data sets have demonstrated the algorithm's capacity to find position frequency matrix models of known regulatory motifs in relatively long promoter sequences. These experiments have also shown the algorithm's ability to maintain diversity during search and discover multiple motifs within a single population. The utility of the algorithm for discovering motifs in real biological data is demonstrated by its ability to find meaningful motifs within muscle-specific regulatory sequences.     

Discovery of predictive rule sets for chlorophyll-a dynamics in the Nakdong River (Korea) by means of the hybrid evolutionary algorithm HEA

This paper presents a hybrid evolutionary algorithm (HEA) to discover complex rule sets predicting the concentration of chlorophyll-a (Chl.a) based on the measured meteorological, hydrological and limnological variables in the hypertrophic Nakdong River. The HEA is designed: (1) to evolve the structure of rule sets by using genetic programming and (2) to optimise the random parameters in the rule sets by means of a genetic algorithm. Time-series of input–output data from 1995 to 1998 without and with time lags up to 7 days were used for training HEA. Independent input–output data for 1994 were used for testing HEA. HEA successfully discovered rule sets for multiple nonlinear relationships between physical, chemical variables and Chl.a, which proved to be predictive for unseen data as well as explanatory. The comparison of results by HEA and previously applied recurrent artificial neural networks to the same data with input–output time lags of 3 days revealed similar good performances of both methods. The sensitivity analysis for the best performing predictive rule set unraveled relationships between seasons, specific input variables and Chl.a which to some degree correspond with known properties of the Nakdong River. The statistics of numerous random runs of the HEA also allowed determining most relevant input variables without a priori knowledge.     

基于新杂合进化算法的蛋白质折叠计算

蛋白质能量最小化是蛋白质折叠的重要内容。用于蛋白质折叠的新的杂合进化算法结合了交叉和柯西变异。基于toy模型的蛋白质能量最小化算例表明,这个新的杂合进化算法是有效的。     

Alternating evolutionary pressure in a genetic algorithm facilitates protein model selection

Background  

Automatic protein modelling pipelines are becoming ever more accurate; this has come hand in hand with an increasingly complicated interplay between all components involved. Nevertheless, there are still potential improvements to be made in template selection, refinement and protein model selection.     

Fast sequence clustering using a suffix array algorithm

MOTIVATION: Efficient clustering is important for handling the large amount of available EST sequences. Most contemporary methods are based on some kind of all-against-all comparison, resulting in a quadratic time complexity. A different approach is needed to keep up with the rapid growth of EST data. RESULTS: A new, fast EST clustering algorithm is presented. Sub-quadratic time complexity is achieved by using an algorithm based on suffix arrays. A prototype implementation has been developed and run on a benchmark data set. The produced clusterings are validated by comparing them to clusterings produced by other methods, and the results are quite promising. AVAILABILITY: The source code for the prototype implementation is available under a GPL license from http://www.ii.uib.no/~ketil/bio/.     

The merits of a parallel genetic algorithm in solving hard optimization problems

A parallel genetic algorithm for optimization is outlined, and its performance on both mathematical and biomechanical optimization problems is compared to a sequential quadratic programming algorithm, a downhill simplex algorithm and a simulated annealing algorithm. When high-dimensional non-smooth or discontinuous problems with numerous local optima are considered, only the simulated annealing and the genetic algorithm, which are both characterized by a weak search heuristic, are successful in finding the optimal region in parameter space. The key advantage of the genetic algorithm is that it can easily be parallelized at negligible overhead.     

Few-view CT reconstruction via a novel non-local means algorithm

PurposeNon-local means (NLM) based reconstruction method is a promising algorithm for few-view computed tomography (CT) reconstruction, but often suffers from over-smoothed image edges. To address this problem, an adaptive NLM reconstruction method based on rotational invariance (ART-RIANLM) is proposed.MethodsThe method consists of four steps: 1) Initializing parameters; 2) ART reconstruction using raw data; 3) Positivity constraint of the reconstructed image; 4) Image updating by RIANLM filtering. In RIANLM, two kinds of rotational invariance measures which are average gradient (AG) and region homogeneity (RH) are proposed to calculate the distance between two patches and a novel NLM filter is developed to avoid over-smoothed image. Moreover, the parameter h in RIANLM which controls the decay of the weights is adaptive to avoid over-smoothness, while it is constant in NLM during the whole reconstruction process. The proposed method is validated on two digital phantoms and real projection data.ResultsIn our experiments, the searching neighborhood size is set as 15 × 15 and the similarity window is set as 3 × 3. For the simulated case of Shepp-Logan phantom, ART-RIANLM produces higher SNR (36.23 dB > 24.00 dB) and lower MAE (0.0006 < 0.0024) reconstructed images than ART-NLM. The visual inspection demonstrated that the proposed method could suppress artifacts or noises more effectively and recover image edges better. The result of real data case is also consistent with the simulation result.ConclusionsA RIANLM based reconstruction method for few-view CT is presented. Compared to the traditional ART-NLM method, SNR and MAE from ART-RIANLM increases 51% and decreases 75%, respectively.     

Robustness analysis of EGFR signaling network with a multi-objective evolutionary algorithm

Robustness, the ability to maintain performance in the face of perturbations and uncertainty, is believed to be a necessary property of biological systems. In this paper, we address the issue of robustness in an important signal transduction network--epidermal growth factor receptor (EGFR) network. First, we analyze the robustness in the EGFR signaling network using all rate constants against the Gauss variation which was described as "the reference parameter set" in the previous study [Kholodenko, B.N., Demin, O.V., Moehren, G., Hoek, J.B., 1999. Quantification of short term signaling by the epidermal growth factor receptor. J. Biol. Chem. 274, 30169-30181]. The simulation results show that signal time, signal duration and signal amplitude of the EGRR signaling network are relatively not robust against the simultaneous variation of the reference parameter set. Second, robustness is quantified using some statistical quantities. Finally, a multi-objective evolutionary algorithm (MOEA) is presented to search reaction rate constants which optimize the robustness of network and compared with the NSGA-II, which is a representation of a class of modern multi-objective evolutionary algorithms. Our simulation results demonstrate that signal time, signal duration and signal amplitude of the four key components--the most downstream variable in each of the pathways: R-Sh-G-S, R-PLP, R-G-S and the phosphorylated receptor RP in EGRR signaling network for the optimized parameter sets have better robustness than those for the reference parameter set and the NSGA-II. These results can provide valuable insight into experimental designs and the dynamics of the signal-response relationship between the dimerized and activated EGFR and the activation of downstream proteins.     

Interaction characteristics as evolutionary features for the spatial Prisoner’s Dilemma in a population modeled by continuous probabilistic cellular automata and evolutionary algorithm

Evolutionary games usually take into consideration individuals’ strategies as the transformative characteristic which leads to the evolution of the population. Here, besides the strategies, interaction aspects are also considered as evolutionary attributes which can change over time as the replacement dynamic renovates the population choosing locally better individuals to reproduce. The population is modeled by cellular automata, interactions by the Prisoner’s Dilemma game and the replacement process is ruled by two versions of death-birth dynamic. Although the average payoff per game is considered as the fitness for choosing better individuals, the number of games per time step and a maximum radius of interaction with neighbours are also present in the individual’s chromosome which is passed to the next generation. Numerical simulations show that individual interaction properties and cooperation level are linked to the version of death-birth dynamic used and the game payoff. For instance, when the fitness bias is on the death event, individuals have more interactions in a larger radius, and the cooperation level is usually lower than the case where the fitness bias is on the birth event. Also, the individuals’ interaction profiles are heterogeneous, and cooperative individuals form clusters in the lattice to protect themselves.     

Fast imaging in flow: a means of combining flow-cytometry and image analysis.

The morphological identification of cells by flow cytometry is difficult. Usually cell sorting and microscopical analysis have to be used in addition. Morphological analysis is simplified by taking cell pictures from a range of particular interest immediately during flow cytometric analysis. Instruments using the video scanning technique for fluorescence imaging are slow and expensive (8, 10). Morphological information can also be obtained by transmission imaging of cells in flow, which requires shorter exposure times. Therefore a cell volume activated flow imaging device has been developed which operates at flow speeds up to 5 m/sec and which depicts transmission images of selected cells on a 16-mm film by a nsec flashlamp illumination. An electronic unit detects the particles in the optically accessible orifice, performs the pulse height analysis, triggers the flashlamp if particles are in the preselcted range of interest and feeds the film. The instrument is capable of delivering up to 150 pictures per second and works either as a flow microscope in which the cells in the preselected volume range are directly observed, or as a picture system in which the cell pictures are stored on the 16-mm film for documentation or for image analysis.     

Simplifying amino acid alphabets by means of a branch and bound algorithm and substitution matrices

MOTIVATION: Protein and DNA are generally represented by sequences of letters. In a number of circumstances simplified alphabets (where one or more letters would be represented by the same symbol) have proved their potential utility in several fields of bioinformatics including searching for patterns occurring at an unexpected rate, studying protein folding and finding consensus sequences in multiple alignments. The main issue addressed in this paper is the possibility of finding a general approach that would allow an exhaustive analysis of all the possible simplified alphabets, using substitution matrices like PAM and BLOSUM as a measure for scoring. RESULTS: The computational approach presented in this paper has led to a computer program called AlphaSimp (Alphabet Simplifier) that can perform an exhaustive analysis of the possible simplified amino acid alphabets, using a branch and bound algorithm together with standard or user-defined substitution matrices. The program returns a ranked list of the highest-scoring simplified alphabets. When the extent of the simplification is limited and the simplified alphabets are maintained above ten symbols the program is able to complete the analysis in minutes or even seconds on a personal computer. However, the performance becomes worse, taking up to several hours, for highly simplified alphabets. AVAILABILITY: AlphaSimp and other accessory programs are available at http://bioinformatics.cribi.unipd.it/alphasimp     

The evolutionary and developmental basis of parallel reduction in mammalian zeugopod elements

Understanding the mechanisms by which parallel evolution occurs has the potential to clarify the complex relationship between evolution and development. In this study, we examine the role of development in the repeated reduction of zeugopod elements during mammalian evolution, a functionally important phenomenon enabling locomotor specialization. By completing a morphometric study (incorporating both analyses of variation and phylogenetics) of mammalian limbs, we are able to demonstrate an evolutionary trend toward width reduction in posterior zeugopod elements of the forelimbs and hindlimbs, the ulna and fibula, respectively. We also examine the developmental basis of limb reduction in three test cases, the bat Carollia perspicillata ulna and fibula and the mouse Mus musculus fibula. The most common pattern of reduction, that of reduced element width, was achieved via the same developmental process in both bat and mouse limbs (i.e., by a slower growth rate relative to other skeletal elements), suggesting that the parallel reduction of the posterior zeugopod element within mammals could have occurred primarily by the repeated evolution of the same developmental mechanism. However, our findings also suggest that the developmental mechanisms behind the parallel evolution of other, more taxon-specific characteristics of limb reduction (i.e., element fusion) are not conserved.