Application of Artificial Bee Colony Algorithm to Maximum Likelihood DOA Estimation

Maximum Likelihood (ML) method has an excellent performance for Direction-Of-Arrival (DOA) estimation, but a multidimensional nonlinear solution search is required which complicates the computation and prevents the method from practical use. To reduce the high computational burden of ML method and make it more suitable to engineering applications, we apply the Artificial Bee Colony (ABC) algorithm to maximize the likelihood function for DOA estimation. As a recently proposed bio-inspired computing algorithm, ABC algorithm is originally used to optimize multivariable functions by imitating the behavior of bee colony finding excellent nectar sources in the nature environment. It offers an excellent alternative to the conventional methods in ML-DOA estimation. The performance of ABC-based ML and other popular meta-heuristic-based ML methods for DOA estimation are compared for various scenarios of convergence, Signal-to-Noise Ratio (SNR), and number of iterations. The computation loads of ABC-based ML and the conventional ML methods for DOA estimation are also investigated. Simulation results demonstrate that the proposed ABC based method is more efficient in computation and statistical performance than other ML-based DOA estimation methods.     

ploidyfrost: Reference-free estimation of ploidy level from whole genome sequencing data based on de Bruijn graphs

Polyploidy is ubiquitous and its consequences are complex and variable. A change of ploidy level generally influences genetic diversity and results in morphological, physiological and ecological differences between cells or organisms with different ploidy levels. To avoid cumbersome experiments and take advantage of the less biased information provided by the vast amounts of genome sequencing data, computational tools for ploidy estimation are urgently needed. Until now, although a few such tools have been developed, many aspects of this estimation, such as the requirement of a reference genome, the lack of informative results and objective inferences, and the influence of false positives from errors and repeats, need further improvement. We have developed ploidyfrost , a de Bruijn graph-based method, to estimate ploidy levels from whole genome sequencing data sets without a reference genome. ploidyfrost provides a visual representation of allele frequency distribution generated using the ggplot2 package as well as quantitative results using the Gaussian mixture model. In addition, it takes advantage of colouring information encoded in coloured de Bruijn graphs to analyse multiple samples simultaneously and to flexibly filter putative false positives. We evaluated the performance of ploidyfrost by analysing highly heterozygous or repetitive samples of Cyclocarya paliurus and a complex allooctoploid sample of Fragaria × ananassa. Moreover, we demonstrated that the accuracy of analysis results can be improved by constraining a threshold such as Cramér's V coefficient on variant features, which may significantly reduce the side effects of sequencing errors and annoying repeats on the graphical structure constructed.     

Straightforward method for calibration of mechanistic cation exchange chromatography models for industrial applications

Mechanistic modeling of chromatography processes is one of the most promising techniques for the digitalization of biopharmaceutical process development. Possible applications of chromatography models range from in silico process optimization in early phase development to in silico root cause investigation during manufacturing. Nonetheless, the cumbersome and complex model calibration still decelerates the implementation of mechanistic modeling in industry. Therefore, the industry demands model calibration strategies that ensure adequate model certainty in a limited amount of time. This study introduces a directed and straightforward approach for the calibration of pH-dependent, multicomponent steric mass action (SMA) isotherm models for industrial applications. In the case investigated, the method was applied to a monoclonal antibody (mAb) polishing step including four protein species. The developed strategy combined well-established theories of preparative chromatography (e.g. Yamamoto method) and allowed a systematic reduction of unknown model parameters to 7 from initially 32. Model uncertainty was reduced by designing two representative calibration experiments for the inverse estimation of remaining model parameters. Dedicated experiments with aggregate-enriched load material led to a significant reduction of model uncertainty for the estimates of this low-concentrated product-related impurity. The model was validated beyond the operating ranges of the final unit operation, enabling its application to late-stage downstream process development. With the proposed model calibration strategy, a systematic experimental design is provided, calibration effort is strongly reduced, and local minima are avoided.     

Myoblast proliferation and syncytial fusion both depend on connexin43 function in transfected skeletal muscle primary cultures

Muscles are formed by fusion of individual postmitotic myoblasts to form multinucleated syncytial myotubes. The process requires a well-coordinated transition from proliferation, through migratory alignment and cycle exit, to breakdown of apposed membranes. Connexin43 protein and cell-cycle inhibitor levels are correlated, and gap junction blockers can delay muscle regeneration, so a coordinating role for gap junctions has been proposed. Here, wild-type and dominant-negative connexin43 variants (wtCx43, dnCx43) were introduced into rat myoblasts in primary culture through pIRES-eGFP constructs that made transfected cells fluoresce. GFP-positive cells and vitally-stained nuclei were counted on successive days to reveal differences in proliferation, and myotubes were counted to reveal differences in fusion. Individual transfected cells were injected with Cascade Blue, which permeates gap junctions, mixed with FITC-dextran, which requires cytoplasmic continuity to enter neighbouring cells. Myoblasts transfected with wtCx43 showed more gap-junctional coupling than GFP-only controls, began fusion sooner as judged by the incidence of cytoplasmic coupling, and formed more myotubes. Myoblasts transfected with dnCx43 remained proliferative for longer than either GFP-only or wtCx43 myoblasts, showed less coupling, and underwent little fusion into myotubes. These results highlight the critical role of gap-junctional coupling in myotube formation.     

An unbiased sensitivity analysis reveals important parameters controlling periodicity of circadian clock

To assess the importance of model parameters in kinetic models, sensitivity analysis is generally employed to provide key measures. However, it is quite often that no information is available for a significant number of parameters in biochemical models. Therefore, the results of sensitivity analysis that heavily rely on the accuracy of parameters are largely ambiguous. In this study, we propose a computational approach to determine the relative importance of parameters controlling the performance of the circadian clock in Drosophila. While previous attempts to sensitivity analysis largely depend on the knowledge of model parameters which are generally unknown, our study depicts a consistent picture of sensitivity assessment for a large number of parameters, even when the values of these parameters are not available in vivo. The resulting parametric sensitivity analysis suggests that PER/TIM negative loop is critical to maintain the stable periodicity of the circadian clock, which is consistent to the previously experimental and computational findings. Furthermore, our analysis generates a rich hypothesis of important parameters in the circadian clock that can be further tested experimentally. This approach can also be extended to assess the sensitivity of parameters in any biochemical system where a large number of parameters have unknown values. Biotechnol. Bioeng. 2010; 105: 250–259. © 2009 Wiley Periodicals, Inc.     

Correlation between interaction strengths drives stability in large ecological networks

Food webs have markedly non‐random network structure. Ecologists maintain that this non‐random structure is key for stability, since large random ecological networks would invariably be unstable and thus should not be observed empirically. Here we show that a simple yet overlooked feature of natural food webs, the correlation between the effects of consumers on resources and those of resources on consumers, substantially accounts for their stability. Remarkably, random food webs built by preserving just the distribution and correlation of interaction strengths have stability properties similar to those of the corresponding empirical systems. Surprisingly, we find that the effect of topological network structure on stability, which has been the focus of countless studies, is small compared to that of correlation. Hence, any study of the effects of network structure on stability must first take into account the distribution and correlation of interaction strengths.     

THE COMPLEX EVOLUTIONARY HISTORY OF SEEING RED: MOLECULAR PHYLOGENY AND THE EVOLUTION OF AN ADAPTIVE VISUAL SYSTEM IN DEEP‐SEA DRAGONFISHES (STOMIIFORMES: STOMIIDAE)

The vast majority of deep‐sea fishes have retinas composed of only rod cells sensitive to only shortwave blue light, approximately 480–490 nm. A group of deep‐sea dragonfishes, the loosejaws (family Stomiidae), possesses far‐red emitting photophores and rhodopsins sensitive to long‐wave emissions greater than 650 nm. In this study, the rhodopsin diversity within the Stomiidae is surveyed based on an analysis of rod opsin‐coding sequences from representatives of 23 of the 28 genera. Using phylogenetic inference, fossil‐calibrated estimates of divergence times, and a comparative approach scanning the stomiid phylogeny for shared genotypes and substitution histories, we explore the evolution and timing of spectral tuning in the family. Our results challenge both the monophyly of the family Stomiidae and the loosejaws. Despite paraphyly of the loosejaws, we infer for the first time that far‐red visual systems have a single evolutionary origin within the family and that this shift in phenotype occurred at approximately 15.4 Ma. In addition, we found strong evidence that at approximately 11.2 Ma the most recent common ancestor of two dragonfish genera reverted to a primitive shortwave visual system during its evolution from a far‐red sensitive dragonfish. According to branch‐site tests for adaptive evolution, we hypothesize that positive selection may be driving spectral tuning in the Stomiidae. These results indicate that the evolutionary history of visual systems in deep‐sea species is complex and a more thorough understanding of this system requires an integrative comparative approach.     

The empirical Bayes estimators of fine‐scale population structure in high gene flow species

An empirical Bayes (EB) pairwise F_ST estimator was previously introduced and evaluated for its performance by numerical simulation. In this study, we conducted coalescent simulations and generated genetic population structure mechanistically, and compared the performance of the EBF_ST with Nei's G_ST, Nei and Chesser's bias‐corrected G_ST (G_{ST_NC}), Weir and Cockerham's θ (θ_WC) and θ with finite sample correction (θ_{WC_F}). We also introduced EB estimators for Hedrick’ G’_ST and Jost’ D. We applied these estimators to publicly available SNP genotypes of Atlantic herring. We also examined the power to detect the environmental factors causing the population structure. Our coalescent simulations revealed that the finite sample correction of θ_WC is necessary to assess population structure using pairwise F_ST values. For microsatellite markers, EBF_ST performed the best among the present estimators regarding both bias and precision under high gene flow scenarios (). For 300 SNPs, EBF_ST had the highest precision in all cases, but the bias was negative and greater than those for G_{ST_NC} and θ_{WC_F} in all cases. G_{ST_NC} and θ_{WC_F} performed very similarly at all levels of F_ST. As the number of loci increased up to 10 000, the precision of G_{ST_NC} and θ_{WC_F} became slightly better than for EBF_ST for cases with , even though the size of the bias remained constant. The EB estimators described the fine‐scale population structure of the herring and revealed that ~56% of the genetic differentiation was caused by sea surface temperature and salinity. The R package finepop for implementing all estimators used here is available on CRAN.