pIPHULA--parallel inference of population parameters using a likelihood approach

pIPHULA is the parallel program to estimate the parameters of a realistic model of population growth.     

Kinetic parameters of enzymatic reactions in states of maximal activity; an evolutionary approach

A theoretical investigation is presented which allows the calculation of states of maximal reaction rates for single enzymes and for unbranched enzymatic chains. As an extension to previous papers (Heinrich & Holzhütter, 1985, Biomed. biochim. Acta 44, 959-969; Heinrich et al., 1987, Bull. math. Biol. 49, 539-595) a detailed enzymatic mechanism was taken into consideration. Conclusions are drawn for the optimal values of the microscopic rate constants as well as of the maximal activities and Michaelis constants. Ten solutions are found which depend on the equilibrium constant as well as on the concentrations of substrates and products. It is shown that for high equilibrium constants one of the solutions applies to a very large range of the concentrations of the outer reactants. This solution is characterized by maximal values of the rate constants of all forward reactions and by non-maximal values of the rate constants of all backward reactions. In contrast to previous assumptions (Albery & Knowles, 1976b, Biochemistry 15, 5631-5640; Burbaum et al., 1989, Biochemistry 28, 9293-9305) states of maximal reaction rate are not always characterized by the highest possible values of the second-order rate constants which are related to the diffusion of the substrate and the product to the active site of the enzyme. Predictions are made concerning the ratios of maximal activities in optimal states as well as for the adaptation of the Michaelis constants to the concentrations of the outer reactants. Using metabolic control analysis it is shown that the solutions obtained for single enzymes may also be applied in multi-enzyme systems.     

Spread of Q fever within dairy cattle herds: key parameters inferred using a Bayesian approach

Q fever is a worldwide zoonosis caused by Coxiella burnetii. Although ruminants are recognized as the most important source of human infection, no previous studies have focused on assessing the characteristics of the bacterial spread within a cattle herd and no epidemic model has been proposed in this context. We assess the key epidemiological parameters from field data in a Bayesian framework that takes into account the available knowledge, missing data and the uncertainty of the observation process owing to the imperfection of diagnostic tests. We propose an original individual-based Markovian model in discrete time describing the evolution of the infection for each animal. Markov chain Monte Carlo methodology is used to estimate parameters of interest from data consisting of individual health states of 217 cows of five chronically infected dairy herds sampled every week for a four-week period. Outputs are the posterior distributions of the probabilities of transition between health states and of the environmental bacterial load. Our findings show that some herds are characterized by a very low infection risk while others have a mild infection risk and a non-negligible intermittent shedding probability. Moreover, the antibody status seems to be a key point in the bacterial spread (shedders with antibodies shed for a longer period of time than shedders without antibodies). In addition to the biological insights, these estimates also provide information for calibrating simulation models to assess control strategies for C. burnetii infection.     

Quantitative approach using multiple single parameters versus visual assessment in dobutamine stress echocardiography

ABSTRACT: BACKGROUND: A number of myocardial Doppler-derived velocity, strain myocardial imaging parameters (DMI) and speckle tracking imaging (STI) have been proposed for the quantification of myocardial ischemia during stress echocardiography. The purpose of the study was to identify the best single ultrasound quantitative parameter for prediction of significant coronary stenosis and compare it with visual assessment during dobutamine stress echocardiography (DSE). METHODS: Prospective analysis included data of 151 patients (age 61.8 +/- 9.2) who underwent dobutamine stress echocardiography for known (n=35) or suspected CAD (n=36) or symptomatic chest pain (n=80), excluding patients with previous myocardial infarction. Systolic, post-systolic and diastolic velocities, strain and strain rate parameters were obtained at rest and at peak dobutamine challenge. Derivative markers as E'/A' ratio, post-systolic index and changes from rest to stress were calculated (98 parameters overall, predominantly longitudinal). Coronary angiography was chosen as reference method considering at least one stenosis greater than or equal to 70% per patient as significant CAD. The predictive value of quantitative parameters and wall motion score index (WMSI) was obtained using logistic regression and ROC analysis. RESULTS: The value of single parameters discriminated as independent predictors of CAD appeared to be modest (area under the curve [AUC] ranged from 0.63 to 0.72 for 16 PW-DMI, 12 CC-DMI and 12 STI markers), comparing to AUC of WMSI 0.88. Sensitivity, specificity and accuracy of visual DSE evaluation was 82.4% (95%CI 77.4%; 85.2%), 92.6% (95%CI 83.4%; 97.5%) and 86.0% (95%CI 79.5%; 89.6%), respectively, Youden index 0.75. Sensitivity, specificity and accuracy of single predictors ranged from 40.0% to 93.3% (95% CI 22.7%; 99.2%), from 34.2% to 88.7% (95% CI 25.6%; 94.1%) and from 45.8% to 80.0% (95% CI 37.5%; 87.2%) respectively, Youden index ranged from 0.20 to 0.52. CONCLUSIONS: Multiple single quantitative parameters showed limited predictive ability to identify significant coronary artery stenosis. Visual assessment of DSE appears to be more accurate than single velocity and strain/strain rate markers in the diagnosis of CAD.     

Correlations of conformational parameters and equilibrium conformational states in a variety of beta-D-arabinonucleosides and their analogues.

H nuclear magnetic resonance spectroscopy has been applied to a study of the conformations of a variety of purine and pyrimidine beta-D-arabinofuranosyl nucleosides. The experimental results, together with data collected from the literature, demonstrated the existence of reasonably good correlations between the coupling constants made it possible to define more accurately, than hitherto possible, the conformational states between which equilibria exist in solution. The equilibrium for the arabinonucleosides differs from that previously established for ribonucleosides; in particular, structural modifications and solvent effects may appreciably modify the conformational states between which equilibria exist. Preliminary measurements on some arabinosides in the syn conformation about the glycosidic bond indicated that these do not conform to the foregoing correlations, and will require separate study. A correlation has also been established between the conformation of the arabinose ring and that of the exocyclic 5'-CH2OH group. For both purine and pyrimidine arabinonucleosides, the conformational state 3E of the arabinose ring coexists to some extent with a gauche-gauche conformation of the exocyclic 5'-CH2OH, as in the case of pyrimidine (but not purine) ribonucleosides. Application of the foregoing to some biological problems is described.     

Molecular parameters involved in bee-plant relationships: a biological and chemical approach

Honeybee-plant relationships are based on a conditioning process in which olfactory (plant aroma) and gustatory cues (mainly nectars) are closely linked, leading to a selective foraging behaviour. Among crops dependent upon entomophilous cross-pollination, the sunflower has recently undergone extensive expansion due to hybrid variety selection. Sunflower hybrid seed production is strictly dependent upon pollinating insects, mainly the honeybees, but foragers may have preferences among the parental lines, leading to a lack of pollen carriage and consequently to a decrease of hybrid seed yield. In order to define the role of plant chemicals (aromas, nectars) involved in the pollination process, we set up a study combining behavioural and chemical assays. It appears that even though volatile chemical blends are much more complex compared to glucidic blends, for both kinds of cues only a 'limited chemical pattern' is responsible for foragers' choices. Therefore, it is henceforth possible to take these molecular criteria into account for plant improvement.     

Jaatha: a fast composite-likelihood approach to estimate demographic parameters

While information about a species’ demography is interesting in its own right, it is an absolute necessity for certain types of population genetic analyses. The most widely used methods to infer a species’ demographic history do not take intralocus recombination or recent divergence into account, and some methods take several weeks to converge. Here, we present Jaatha, a new composite‐likelihood method that does incorporate recent divergence and is also applicable when intralocus recombination rates are high. This new method estimates four demographic parameters. The accuracy of Jaatha is comparable to that of other currently available methods, although it is superior under certain conditions, especially when divergence is very recent. As a proof of concept, we apply this new method to estimate demographic parameters for two closely related wild tomato species, Solanum chilense and S. peruvianum. Our results indicate that these species likely diverged 1.44·N generations ago, where N is the effective population size of S. chilense, and that some introgression between these species continued after the divergence process initiated. Furthermore, S. peruvianum likely experienced a population expansion following speciation.     

Building a baseline for habitat-forming corals by a multi-source approach,including Web Ecological Knowledge

In the Mediterranean, habitat-forming corals often characterize essential fish habitats. While their distribution is sufficiently known for the western basin, few data are available from the Central-Eastern Mediterranean Sea (CEM). This study fills this gap supplying the largest dataset ever built on the geographical and bathymetric distribution of the most relevant habitat-forming corals (Eunicella cavolini, Eunicella verrucosa, Eunicella singularis, Leptogorgia sarmentosa, Paramuricea clavata, Corallium rubrum and Savalia savaglia) of the CEM. Information collected from different sources such as literature, citizen science, and from the World Wide Web (WWW) was combined. Videos published on the WWW provided additional information on the presence of fishing lines and signs of damage, as well as on the distribution of purple and yellow-purple colonies of Paramuricea clavata. The study highlighted the impressive amount of information that the WWW can offer to scientists, termed here as Web Ecological Knowledge (WEK). The WEK is constantly fuelled by internauts, representing a free, refreshable, long-term exploitable reservoir of information. A quick and easy method to retrieve data from the WWW was illustrated. In addition, the distribution of corals was overlapped to marine protected areas and to the distribution of environmental conditions suitable for coralligenous habitats, fragile biogenic Mediterranean structures hosting complex assemblages in need of strict protection. The collected data allowed identifying priority areas with high species diversity and sites that are impacted by fishing activities. Supplied data can correctly address conservation and restoration policies in the CEM, adding an important contribution to ecosystem-based marine spatial planning.     

Determination of Lennard-Jones interaction parameters using a new procedure

For theoretical and chemical engineering applications, accurate and, if possible, simple models of molecular interactions are needed. We have recently proposed a new procedure for determining Lennard-Jones interaction parameters for fluids, forcing agreement between the values of the pressure obtained from empirical equations of state and those obtained from computer simulations. In this work we obtain new intermolecular Lennard-Jones parameters for non-polar molecules, taking into account their deviation from the spherical shape by means of an acentric factor. Our procedure could help to connect the microscopic and macroscopic worlds and it will be progressively implemented in order to obtain a better representation of other substances and mixtures of chemical interest.     

Estimating ancestral distributions of lineages with uncertain sister groups： a statistical approach to Dispersal-Vicariance Analysis and a case using Aesculus L. （Sapindaceae） including fossils

We propose a simple statistical approach for using Dispersal-Vicariance Analysis （DIVA） software to infer biogeographic histories without fully bifurcating trees. In this approach, ancestral ranges are first optimized for a sample of Bayesian trees. The probability P of an ancestral range r at a node is then calculated as P（rY） = ∑t^n=1 F（rY）t Pt where Y is a node, and F（rY） is the frequency of range r among all the optimal solutions resulting from DIVA optimization at node Y, t is one of n topologies optimized, and Pt is the probability of topology t. Node Y is a hypothesized ancestor shared by a specific crown lineage and the sister of that lineage ＂x＂, where x may vary due to phylogenetic uncertainty （polytomies and nodes with posterior probability 〈 100%）. Using this method, the ancestral distribution at Y can be estimated to provide inference of the geographic origins of the specific crown group of interest. This approach takes into account phylogenetic uncertainty as well as uncertainty from DIVA optimization. It is an extension of the previously described method called Bayes-DIVA, which pairs Bayesian phylogenetic analysis with biogeographic analysis using DIVA. Further, we show that the probability P of an ancestral range at Y calculated using this method does not equate to pp＊F（rY） on the Bayesian consensus tree when both variables are 〈 100%, where pp is the posterior probability and F（rY） is the frequency of range r for the node containing the specific crown group. We tested our DIVA-Bayes approach using Aesculus L., which has major lineages unresolved as a polytomy. We inferred the most probable geographic origins of the five traditional sections of Aesculus and ofAesculus californica Nutt. and examined range subdivisions at parental nodes of these lineages. Additionally, we used the DIVA-Bayes data from Aesculus to quantify the effects on biogeographic inference of including two wildcard fossil taxa in phylogenetic analysis. Our analysis resolved the geographic     

Predicting domain-domain interactions using a parsimony approach

We propose a novel approach to predict domain-domain interactions from a protein-protein interaction network. In our method we apply a parsimony-driven explanation of the network, where the domain interactions are inferred using linear programming optimization, and false positives in the protein network are handled by a probabilistic construction. This method outperforms previous approaches by a considerable margin. The results indicate that the parsimony principle provides a correct approach for detecting domain-domain contacts.     

Protein domain decomposition using a graph-theoretic approach

MOTIVATION: Automatic decomposition of a multi-domain protein into individual domains represents a highly interesting and unsolved problem. As the number of protein structures in PDB is growing at an exponential rate, there is clearly a need for more reliable and efficient methods for protein domain decomposition simply to keep the domain databases up-to-date. RESULTS: We present a new algorithm for solving the domain decomposition problem, using a graph-theoretic approach. We have formulated the problem as a network flow problem, in which each residue of a protein is represented as a node of the network and each residue--residue contact is represented as an edge with a particular capacity, depending on the type of the contact. A two-domain decomposition problem is solved by finding a bottleneck (or a minimum cut) of the network, which minimizes the total cross-edge capacity, using the classical Ford--Fulkerson algorithm. A multi-domain decomposition problem is solved through repeatedly solving a series of two-domain problems. The algorithm has been implemented as a computer program, called DomainParser. We have tested the program on a commonly used test set consisting of 55 proteins. The decomposition results are 78.2% in agreement with the literature on both the number of decomposed domains and the assignments of residues to each domain, which compares favorably to existing programs. On the subset of two-domain proteins (20 in number), the program assigned 96.7% of the residues correctly when we require that the number of decomposed domains is two.     

Sweat loss prediction using a multi-model approach

A new multi-model approach (MMA) for sweat loss prediction is proposed to improve prediction accuracy. MMA was computed as the average of sweat loss predicted by two existing thermoregulation models: i.e., the rational model SCENARIO and the empirical model Heat Strain Decision Aid (HSDA). Three independent physiological datasets, a total of 44 trials, were used to compare predictions by MMA, SCENARIO, and HSDA. The observed sweat losses were collected under different combinations of uniform ensembles, environmental conditions (15–40°C, RH 25–75%), and exercise intensities (250–600 W). Root mean square deviation (RMSD), residual plots, and paired t tests were used to compare predictions with observations. Overall, MMA reduced RMSD by 30–39% in comparison with either SCENARIO or HSDA, and increased the prediction accuracy to 66% from 34% or 55%. Of the MMA predictions, 70% fell within the range of mean observed value ± SD, while only 43% of SCENARIO and 50% of HSDA predictions fell within the same range. Paired t tests showed that differences between observations and MMA predictions were not significant, but differences between observations and SCENARIO or HSDA predictions were significantly different for two datasets. Thus, MMA predicted sweat loss more accurately than either of the two single models for the three datasets used. Future work will be to evaluate MMA using additional physiological data to expand the scope of populations and conditions.     

Modeling of movement-related potentials using a fractal approach

In bio-signal applications, classification performance depends greatly on feature extraction, which is also the case for electroencephalogram (EEG) based applications. Feature extraction, and consequently classification of EEG signals is not an easy task due to their inherent low signal-to-noise ratios and artifacts. EEG signals can be treated as the output of a non-linear dynamical (chaotic) system in the human brain and therefore they can be modeled by their dimension values. In this study, the variance fractal dimension technique is suggested for the modeling of movement-related potentials (MRPs). Experimental data sets consist of EEG signals recorded during the movements of right foot up, lip pursing and a simultaneous execution of these two tasks. The experimental results and performance tests show that the proposed modeling method can efficiently be applied to MRPs especially in the binary approached brain computer interface applications aiming to assist severely disabled people such as amyotrophic lateral sclerosis patients in communication and/or controlling devices.     

Estimating developmental states of tumors and normal tissues using a linear time-ordered model

Background  

Tumor cells are considered to have an aberrant cell state, and some evidence indicates different development states appearing in the tumorigenesis. Embryonic development and stem cell differentiation are ordered processes in which the sequence of events over time is highly conserved. The "cancer attractor" concept integrates normal developmental processes and tumorigenesis into a high-dimensional "cell state space", and provides a reasonable explanation of the relationship between these two biological processes from theoretical viewpoint. However, it is hard to describe such relationship by using existed experimental data; moreover, the measurement of different development states is also difficult.     

Validation of molecular force field parameters for peptides including isomerized amino acids

Recently, stereoinversions and isomerizations of amino acid residues in the proteins of living beings have been observed. Because isomerized amino acids cause structural changes and denaturation of proteins, isomerizations of amino acid residues are suspected to cause age‐related diseases. In this study, AMBER molecular force field parameters were tested by using computationally generated nonapeptides and tripeptides including stereoinverted and/or isomerized amino acid residues. Energy calculations by using density functional theory were also performed for comparison. Although the force field parameters were developed by parameter fitting for l ‐α‐amino acids, the accuracy of the computational results for d ‐amino acids and β‐amino acids was comparable to those for l ‐α‐amino acids. The conformational energies for tripeptides calculated by using density functional theory were reproduced more accurately than those for nonapeptides calculated by using the molecular mechanical force field. The evaluations were performed for the ff99SB, ff03, ff12SB, and the latest ff14SB force field parameters.     

A novel approach to estimate trabecular bone anisotropy using a database approach

Continuum finite element (FE) models of bones have become a standard pre-clinical tool to estimate bone strength. These models are usually based on clinical CT scans and material properties assigned are chosen as isotropic based only on the density distribution. It has been shown, however, that trabecular bone elastic behavior is best described as orthotropic. Unfortunately, the use of orthotropic models in FE analysis derived from CT scans is hampered by the fact that the measurement of a trabecular orientation (fabric) is not possible from clinical CT images due to the low resolution of such images. In this study, we explore the concept of using a database (DB) of high-resolution bone models to derive the fabric information that is missing in clinical images. The goal of this study was to investigate if models with fabric derived from a relatively small database can already produce more accurate results than isotropic models.