Development and application of computational methodologies in qualitative modeling

La présente thèse s'intitule "Développent et Application des Méthodologies Computationnelles pour la Modélisation Qualitative". Elle comprend tous les différents projets que j'ai entrepris en tant que doctorante. Plutôt qu'une mise en oeuvre systématique d'un cadre défini a priori, cette thèse devrait être considérée comme une exploration des méthodes qui peuvent nous aider à déduire le plan de processus regulatoires et de signalisation. Cette exploration a été mue par des questions biologiques concrètes, plutôt que par des investigations théoriques. Bien que tous les projets aient inclus des systèmes divergents (réseaux régulateurs de gènes du cycle cellulaire, réseaux de signalisation de cellules pulmonaires) ainsi que des organismes (levure à fission, levure bourgeonnante, rat, humain), nos objectifs étaient complémentaires et cohérents. Le projet principal de la thèse est la modélisation du réseau de l'initiation de septation (SIN) du S.pombe. La cytokinèse dans la levure à fission est contrôlée par le SIN, un réseau signalant de protéines kinases qui utilise le corps à pôle-fuseau comme échafaudage. Afin de décrire le comportement qualitatif du système et prédire des comportements mutants inconnus, nous avons décidé d'adopter l'approche de la modélisation booléenne. Dans cette thèse, nous présentons la construction d'un modèle booléen étendu du SIN, comprenant la plupart des composantes et des régulateurs du SIN en tant que noeuds individuels et testable expérimentalement. Ce modèle utilise des niveaux d'activité du CDK comme noeuds de contrôle pour la simulation d'évènements du SIN à différents stades du cycle cellulaire. Ce modèle a été optimisé en utilisant des expériences d'un seul "knock-out" avec des effets phénotypiques connus comme set d'entraînement. Il a permis de prédire correctement un set d'évaluation de "knock-out" doubles. De plus, le modèle a fait des prédictions in silico qui ont été validées in vivo, permettant d'obtenir de nouvelles idées de la régulation et l'organisation hiérarchique du SIN. Un autre projet concernant le cycle cellulaire qui fait partie de cette thèse a été la construction d'un modèle qualitatif et minimal de la réciprocité des cyclines dans la S.cerevisiae. Les protéines Clb dans la levure bourgeonnante présentent une activation et une dégradation caractéristique et séquentielle durant le cycle cellulaire, qu'on appelle communément les vagues des Clbs. Cet évènement est coordonné avec la courbe d'activation inverse du Sic1, qui a un rôle inhibitoire dans le système. Pour l'identification des modèles qualitatifs minimaux qui peuvent expliquer ce phénomène, nous avons sélectionné des expériences bien définies et construit tous les modèles minimaux possibles qui, une fois simulés, reproduisent les résultats attendus. Les modèles ont été filtrés en utilisant des simulations ODE qualitatives et standardisées; seules celles qui reproduisaient le phénotype des vagues ont été gardées. L'ensemble des modèles minimaux peut être utilisé pour suggérer des relations regulatoires entre les molécules participant qui peuvent ensuite être testées expérimentalement. Enfin, durant mon doctorat, j'ai participé au SBV Improver Challenge. Le but était de déduire des réseaux spécifiques à des espèces (humain et rat) en utilisant des données de phosphoprotéines, d'expressions des gènes et des cytokines, ainsi qu'un réseau de référence, qui était mis à disposition comme donnée préalable. Notre solution pour ce concours a pris la troisième place. L'approche utilisée est expliquée en détail dans le dernier chapitre de la thèse. -- The present dissertation is entitled "Development and Application of Computational Methodologies in Qualitative Modeling". It encompasses the diverse projects that were undertaken during my time as a PhD student. Instead of a systematic implementation of a framework defined a priori, this thesis should be considered as an exploration of the methods that can help us infer the blueprint of regulatory and signaling processes. This exploration was driven by concrete biological questions, rather than theoretical investigation. Even though the projects involved divergent systems (gene regulatory networks of cell cycle, signaling networks in lung cells), as well as organisms (fission yeast, budding yeast, rat, human), our goals were complementary and coherent. The main project of the thesis is the modeling of the Septation Initiation Network (SIN) in S.pombe. Cytokinesis in fission yeast is controlled by the SIN, a protein kinase signaling network that uses the spindle pole body as scaffold. In order to describe the qualitative behavior of the system and predict unknown mutant behaviors we decided to adopt a Boolean modeling approach. In this thesis, we report the construction of an extended, Boolean model of the SIN, comprising most SIN components and regulators as individual, experimentally testable nodes. The model uses CDK activity levels as control nodes for the simulation of SIN related events in different stages of the cell cycle. The model was optimized using single knock-out experiments of known phenotypic effect as a training set, and was able to correctly predict a double knock-out test set. Moreover, the model has made in silico predictions that have been validated in vivo, providing new insights into the regulation and hierarchical organization of the SIN. Another cell cycle related project that is part of this thesis was to create a qualitative, minimal model of cyclin interplay in S.cerevisiae. CLB proteins in budding yeast present a characteristic, sequential activation and decay during the cell cycle, commonly referred to as Clb waves. This event is coordinated with the inverse activation curve of Sic1, which has an inhibitory role in the system. To generate minimal qualitative models that can explain this phenomenon, we selected well-defined experiments and constructed all possible minimal models that, when simulated, reproduce the expected results. The models were filtered using standardized qualitative ODE simulations; only the ones reproducing the wave-like phenotype were kept. The set of minimal models can be used to suggest regulatory relations among the participating molecules, which will subsequently be tested experimentally. Finally, during my PhD I participated in the SBV Improver Challenge. The goal was to infer species-specific (human and rat) networks, using phosphoprotein, gene expression and cytokine data and a reference network provided as prior knowledge. Our solution to the challenge was selected as in the final chapter of the thesis.

A semi-grand canonical Monte Carlo simulation model for ion binding to ionizable surfaces: Proton binding of carboxylated latex particles as a case study

In this paper, we present a computer simulation study of the ion binding process at an ionizable surface using a semi-grand canonical Monte Carlo method that models the surface as a discrete distribution of charged and neutral functional groups in equilibrium with explicit ions modelled in the context of the primitive model. The parameters of the simulation model were tuned and checked by comparison with experimental titrations of carboxylated latex particles in the presence of different ionic strengths of monovalent ions. The titration of these particles was analysed by calculating the degree of dissociation of the latex functional groups vs. pH curves at different background salt concentrations. As the charge of the titrated surface changes during the simulation, a procedure to keep the electroneutrality of the system is required. Here, two approaches are used with the choice depending on the ion selected to maintain electroneutrality: counterion or coion procedures. We compare and discuss the difference between the procedures. The simulations also provided a microscopic description of the electrostatic double layer (EDL) structure as a function of pH and ionic strength. The results allow us to quantify the effect of the size of the background salt ions and of the surface functional groups on the degree of dissociation. The non-homogeneous structure of the EDL was revealed by plotting the counterion density profiles around charged and neutral surface functional groups. © 2011 American Institute of Physics.

Base temperature and simulation model for nodes appearance in cape gooseberry (Physalis peruviana L.)

Data was analyzed on development of the solanaceen fruit crop Cape gooseberry to evaluate how well a classical thermal time model could describe node appearance in different environments. The data used in the analysis were obtained from experiments conducted in Colombia in open fields and greenhouse condition at two locations with different climate. An empirical, non linear segmented model was used to estimate the base temperature and to parameterize the model for simulation of node appearance vs. time. The base temperature (Tb) used to calculate the thermal time (TT, ºCd) for node appearance was estimated to be 6.29 ºC. The slope of the first linear segment was 0.023 nodes per TT and 0.008 for the second linear segment. The time at which the slope of node apperance changed was 1039.5 ºCd after transplanting, determined from a statistical analysis of model for the first segment. When these coefficients were used to predict node appearance at all locations, the model successfully fit the observed data (RSME=2.1), especially for the first segment where node appearance was more homogeneous than the second segment. More nodes were produced by plants grown under greenhouse conditions and minimum and maximum rates of node appearance rates were also higher.

Comblike poly(a-alkyl g glutamate)s: computer simulation studies of an intermediate thermal phase.

Monte Carlo (MC) simulations have been used to study the structure of an intermediate thermal phase of poly(R-octadecyl ç,D-glutamate). This is a comblike poly(ç-peptide) able to adopt a biphasic structure that has been described as a layered arrangement of backbone helical rods immersed in a paraffinic pool of polymethylene side chains. Simulations were performed at two different temperatures (348 and 363 K), both of them above the melting point of the paraffinic phase, using the configurational bias MC algorithm. Results indicate that layers are constituted by a side-by-side packing of 17/5 helices. The organization of the interlayer paraffinic region is described in atomistic terms by examining the torsional angles and the end-to-end distances for the octadecyl side chains. Comparison with previously reported comblike poly(â-peptide)s revealed significant differences in the organization of the alkyl side chains.

Computational modeling of resting-state activity demonstrates markers of normalcy in children with prenatal or perinatal stroke.

Children who sustain a prenatal or perinatal brain injury in the form of a stroke develop remarkably normal cognitive functions in certain areas, with a particular strength in language skills. A dominant explanation for this is that brain regions from the contralesional hemisphere "take over" their functions, whereas the damaged areas and other ipsilesional regions play much less of a role. However, it is difficult to tease apart whether changes in neural activity after early brain injury are due to damage caused by the lesion or by processes related to postinjury reorganization. We sought to differentiate between these two causes by investigating the functional connectivity (FC) of brain areas during the resting state in human children with early brain injury using a computational model. We simulated a large-scale network consisting of realistic models of local brain areas coupled through anatomical connectivity information of healthy and injured participants. We then compared the resulting simulated FC values of healthy and injured participants with the empirical ones. We found that the empirical connectivity values, especially of the damaged areas, correlated better with simulated values of a healthy brain than those of an injured brain. This result indicates that the structural damage caused by an early brain injury is unlikely to have an adverse and sustained impact on the functional connections, albeit during the resting state, of damaged areas. Therefore, these areas could continue to play a role in the development of near-normal function in certain domains such as language in these children.

Performance Analysis of Two Quantum Reaction Dynamics Codes: Time-Dependent and Time-Independent Strategies

The computer simulation of reaction dynamics has nowadays reached a remarkable degree of accuracy. Triatomic elementary reactions are rigorously studied with great detail on a straightforward basis using a considerable variety of Quantum Dynamics computational tools available to the scientific community. In our contribution we compare the performance of two quantum scattering codes in the computation of reaction cross sections of a triatomic benchmark reaction such as the gas phase reaction Ne + H2+ %12. NeH++ H. The computational codes are selected as representative of time-dependent (Real Wave Packet [ ]) and time-independent (ABC [ ]) methodologies. The main conclusion to be drawn from our study is that both strategies are, to a great extent, not competing but rather complementary. While time-dependent calculations advantages with respect to the energy range that can be covered in a single simulation, time-independent approaches offer much more detailed information from each single energy calculation. Further details such as the calculation of reactivity at very low collision energies or the computational effort related to account for the Coriolis couplings are analyzed in this paper.

Disentangling the formation of contrasting tree line physiognomies combining model selection and Bayesian parameterization for simulation models.

Alpine tree-line ecotones are characterized by marked changes at small spatial scales that may result in a variety of physiognomies. A set of alternative individual-based models was tested with data from four contrasting Pinus uncinata ecotones in the central Spanish Pyrenees to reveal the minimal subset of processes required for tree-line formation. A Bayesian approach combined with Markov chain Monte Carlo methods was employed to obtain the posterior distribution of model parameters, allowing the use of model selection procedures. The main features of real tree lines emerged only in models considering nonlinear responses in individual rates of growth or mortality with respect to the altitudinal gradient. Variation in tree-line physiognomy reflected mainly changes in the relative importance of these nonlinear responses, while other processes, such as dispersal limitation and facilitation, played a secondary role. Different nonlinear responses also determined the presence or absence of krummholz, in agreement with recent findings highlighting a different response of diffuse and abrupt or krummholz tree lines to climate change. The method presented here can be widely applied in individual-based simulation models and will turn model selection and evaluation in this type of models into a more transparent, effective, and efficient exercise.

Understanding Optical Trapping Phenomena: a Simulation for Undergraduates

Optical trapping is an attractive and multidisciplinary topic that has become the center of attention to a large number of researchers. Moreover, it is a suitable subject for advanced students that requires a knowledge of a wide range of topics. As a result, it has been incorporated into some syllabuses of both undergraduate and graduate programs. In this paper, basic concepts in laser trapping theory are reviewed. To provide a better understanding of the underlying concepts for students, a Java application for simulating the behavior of a dielectric particle trapped in a highly focused beam has been developed. The program illustrates a wide range of theoretical results and features, such as the calculation of the force exerted by a beam in the Mie and Rayleigh regimes or the calibration of the trap stiffness. Some examples that are ready to be used in the classroom or in the computer lab are also supplied.

Flocking behaviour: Agent-based simulation and hierarchical leadership.

We have studied how leaders emerge in a group as a consequence of interactions among its members. We propose that leaders can emerge as a consequence of a self-organized process based on local rules of dyadic interactions among individuals. Flocks are an example of self-organized behaviour in a group and properties similar to those observed in flocks might also explain some of the dynamics and organization of human groups. We developed an agent-based model that generated flocks in a virtual world and implemented it in a multi-agent simulation computer program that computed indices at each time step of the simulation to quantify the degree to which a group moved in a coordinated way (index of flocking behaviour) and the degree to which specific individuals led the group (index of hierarchical leadership). We ran several series of simulations in order to test our model and determine how these indices behaved under specific agent and world conditions. We identified the agent, world property, and model parameters that made stable, compact flocks emerge, and explored possible environmental properties that predicted the probability of becoming a leader.

Molecular dynamics simulation of the spherical electrical double layer of a soft nanoparticle. Effect of the surface and counterion valence

Molecular dynamics simulations were performed to study the ion and water distribution around a spherical charged nanoparticle. A soft nanoparticle model was designed using a set of hydrophobic interaction sites distributed in six concentric spherical layers. In order to simulate the effect of charged functionalyzed groups on the nanoparticle surface, a set of charged sites were distributed in the outer layer. Four charged nanoparticle models, from a surface charge value of −0.035 Cm−2 to − 0.28 Cm−2, were studied in NaCl and CaCl2 salt solutions at 1 M and 0.1 M concentrations to evaluate the effect of the surface charge, counterion valence, and concentration of added salt. We obtain that Na + and Ca2 + ions enter inside the soft nanoparticle. Monovalent ions are more accumulated inside the nanoparticle surface, whereas divalent ions are more accumulated just in the plane of the nanoparticle surface sites. The increasing of the the salt concentration has little effect on the internalization of counterions, but significantly reduces the number of water molecules that enter inside the nanoparticle. The manner of distributing the surface charge in the nanoparticle (uniformly over all surface sites or discretely over a limited set of randomly selected sites) considerably affects the distribution of counterions in the proximities of the nanoparticle surface.

Effect of the surface charge discretization on electric double layers. A Monte Carlo simulation study

The structure of the electric double layer in contact with discrete and continuously charged planar surfaces is studied within the framework of the primitive model through Monte Carlo simulations. Three different discretization models are considered together with the case of uniform distribution. The effect of discreteness is analyzed in terms of charge density profiles. For point surface groups,a complete equivalence with the situation of uniformly distributed charge is found if profiles are exclusively analyzed as a function of the distance to the charged surface. However, some differences are observed moving parallel to the surface. Significant discrepancies with approaches that do not account for discreteness are reported if charge sites of finite size placed on the surface are considered.

An integrative computational analysis provides evidence for FBN1-associated network deregulation in trisomy 21

Although approximately 50% of Down Syndrome (DS) patients have heart abnormalities, they exhibit an overprotection against cardiac abnormalities related with the connective tissue, for example a lower risk of coronary artery disease. A recent study reported a case of a person affected by DS who carried mutations in FBN1, the gene causative for a connective tissue disorder called Marfan Syndrome (MFS). The fact that the person did not have any cardiac alterations suggested compensation effects due to DS. This observation is supported by a previous DS meta-analysis at the molecular level where we have found an overall upregulation of FBN1 (which is usually downregulated in MFS). Additionally, that result was cross-validated with independent expression data from DS heart tissue. The aim of this work is to elucidate the role of FBN1 in DS and to establish a molecular link to MFS and MFS-related syndromes using a computational approach. To reach that, we conducted different analytical approaches over two DS studies (our previous meta-analysis and independent expression data from DS heart tissue) and revealed expression alterations in the FBN1 interaction network, in FBN1 co-expressed genes and FBN1-related pathways. After merging the significant results from different datasets with a Bayesian approach, we prioritized 85 genes that were able to distinguish control from DS cases. We further found evidence for several of these genes (47%), such as FBN1, DCN, and COL1A2, being dysregulated in MFS and MFS-related diseases. Consequently, we further encourage the scientific community to take into account FBN1 and its related network for the study of DS cardiovascular characteristics.

How to report multiple outcome metrics in virtual reality simulation

Background Virtual reality (VR) simulation is increasingly used in surgical disciplines. Since VR simulators measure multiple outcomes, standardized reporting is needed. Methods We present an algorithm for combining multiple VR outcomes into dimension summary measures, which are then integrated into a meaningful total score. We reanalyzed the data of two VR studies applying the algorithm. Results The proposed algorithm was successfully applied to both VR studies. Conclusions The algorithm contributes to standardized and transparent reporting in VR-related research.

Using computational fluid dynamics to predict head losses in the auxiliary elements of a microirrigation sand filter

It is often assumed that total head losses in a sand filter are solely due to the filtration media and that there are analytical solutions, such as the Ergun equation, to compute them. However, total head losses are also due to auxiliary elements (inlet and outlet pipes and filter nozzles), which produce undesirable head losses because they increase energy requirements without contributing to the filtration process. In this study, ANSYS Fluent version 6.3, a commercial computational fluid dynamics (CFD) software program, was used to compute head losses in different parts of a sand filter. Six different numerical filter models of varying complexities were used to understand the hydraulic behavior of the several filter elements and their importance in total head losses. The simulation results show that 84.6% of these were caused by the sand bed and 15.4% were due to auxiliary elements (4.4% in the outlet and inlet pipes, and 11.0% in the perforated plate and nozzles). Simulation results with different models show the important role of the nozzles in the hydraulic behavior of the sand filter. The relationship between the passing area through the nozzles and the passing area through the perforated plate is an important design parameter for the reduction of total head losses. A reduced relationship caused by nozzle clogging would disproportionately increase the total head losses in the sand filter

Bidding support for computational resources

Peer-reviewed