Time-lapse and probabilistic inversion strategies for plane-wave electromagnetic data.

L'utilisation efficace des systèmes géothermaux, la séquestration du CO2 pour limiter le changement climatique et la prévention de l'intrusion d'eau salée dans les aquifères costaux ne sont que quelques exemples qui démontrent notre besoin en technologies nouvelles pour suivre l'évolution des processus souterrains à partir de la surface. Un défi majeur est d'assurer la caractérisation et l'optimisation des performances de ces technologies à différentes échelles spatiales et temporelles. Les méthodes électromagnétiques (EM) d'ondes planes sont sensibles à la conductivité électrique du sous-sol et, par conséquent, à la conductivité électrique des fluides saturant la roche, à la présence de fractures connectées, à la température et aux matériaux géologiques. Ces méthodes sont régies par des équations valides sur de larges gammes de fréquences, permettant détudier de manières analogues des processus allant de quelques mètres sous la surface jusqu'à plusieurs kilomètres de profondeur. Néanmoins, ces méthodes sont soumises à une perte de résolution avec la profondeur à cause des propriétés diffusives du champ électromagnétique. Pour cette raison, l'estimation des modèles du sous-sol par ces méthodes doit prendre en compte des informations a priori afin de contraindre les modèles autant que possible et de permettre la quantification des incertitudes de ces modèles de façon appropriée. Dans la présente thèse, je développe des approches permettant la caractérisation statique et dynamique du sous-sol à l'aide d'ondes EM planes. Dans une première partie, je présente une approche déterministe permettant de réaliser des inversions répétées dans le temps (time-lapse) de données d'ondes EM planes en deux dimensions. Cette stratégie est basée sur l'incorporation dans l'algorithme d'informations a priori en fonction des changements du modèle de conductivité électrique attendus. Ceci est réalisé en intégrant une régularisation stochastique et des contraintes flexibles par rapport à la gamme des changements attendus en utilisant les multiplicateurs de Lagrange. J'utilise des normes différentes de la norme l2 pour contraindre la structure du modèle et obtenir des transitions abruptes entre les régions du model qui subissent des changements dans le temps et celles qui n'en subissent pas. Aussi, j'incorpore une stratégie afin d'éliminer les erreurs systématiques de données time-lapse. Ce travail a mis en évidence l'amélioration de la caractérisation des changements temporels par rapport aux approches classiques qui réalisent des inversions indépendantes à chaque pas de temps et comparent les modèles. Dans la seconde partie de cette thèse, j'adopte un formalisme bayésien et je teste la possibilité de quantifier les incertitudes sur les paramètres du modèle dans l'inversion d'ondes EM planes. Pour ce faire, je présente une stratégie d'inversion probabiliste basée sur des pixels à deux dimensions pour des inversions de données d'ondes EM planes et de tomographies de résistivité électrique (ERT) séparées et jointes. Je compare les incertitudes des paramètres du modèle en considérant différents types d'information a priori sur la structure du modèle et différentes fonctions de vraisemblance pour décrire les erreurs sur les données. Les résultats indiquent que la régularisation du modèle est nécessaire lorsqu'on a à faire à un large nombre de paramètres car cela permet d'accélérer la convergence des chaînes et d'obtenir des modèles plus réalistes. Cependent, ces contraintes mènent à des incertitudes d'estimations plus faibles, ce qui implique des distributions a posteriori qui ne contiennent pas le vrai modèledans les régions ou` la méthode présente une sensibilité limitée. Cette situation peut être améliorée en combinant des méthodes d'ondes EM planes avec d'autres méthodes complémentaires telles que l'ERT. De plus, je montre que le poids de régularisation des paramètres et l'écart-type des erreurs sur les données peuvent être retrouvés par une inversion probabiliste. Finalement, j'évalue la possibilité de caractériser une distribution tridimensionnelle d'un panache de traceur salin injecté dans le sous-sol en réalisant une inversion probabiliste time-lapse tridimensionnelle d'ondes EM planes. Etant donné que les inversions probabilistes sont très coûteuses en temps de calcul lorsque l'espace des paramètres présente une grande dimension, je propose une stratégie de réduction du modèle ou` les coefficients de décomposition des moments de Legendre du panache de traceur injecté ainsi que sa position sont estimés. Pour ce faire, un modèle de résistivité de base est nécessaire. Il peut être obtenu avant l'expérience time-lapse. Un test synthétique montre que la méthodologie marche bien quand le modèle de résistivité de base est caractérisé correctement. Cette méthodologie est aussi appliquée à un test de trac¸age par injection d'une solution saline et d'acides réalisé dans un système géothermal en Australie, puis comparée à une inversion time-lapse tridimensionnelle réalisée selon une approche déterministe. L'inversion probabiliste permet de mieux contraindre le panache du traceur salin gr^ace à la grande quantité d'informations a priori incluse dans l'algorithme. Néanmoins, les changements de conductivités nécessaires pour expliquer les changements observés dans les données sont plus grands que ce qu'expliquent notre connaissance actuelle des phénomenès physiques. Ce problème peut être lié à la qualité limitée du modèle de résistivité de base utilisé, indiquant ainsi que des efforts plus grands devront être fournis dans le futur pour obtenir des modèles de base de bonne qualité avant de réaliser des expériences dynamiques. Les études décrites dans cette thèse montrent que les méthodes d'ondes EM planes sont très utiles pour caractériser et suivre les variations temporelles du sous-sol sur de larges échelles. Les présentes approches améliorent l'évaluation des modèles obtenus, autant en termes d'incorporation d'informations a priori, qu'en termes de quantification d'incertitudes a posteriori. De plus, les stratégies développées peuvent être appliquées à d'autres méthodes géophysiques, et offrent une grande flexibilité pour l'incorporation d'informations additionnelles lorsqu'elles sont disponibles. -- The efficient use of geothermal systems, the sequestration of CO2 to mitigate climate change, and the prevention of seawater intrusion in coastal aquifers are only some examples that demonstrate the need for novel technologies to monitor subsurface processes from the surface. A main challenge is to assure optimal performance of such technologies at different temporal and spatial scales. Plane-wave electromagnetic (EM) methods are sensitive to subsurface electrical conductivity and consequently to fluid conductivity, fracture connectivity, temperature, and rock mineralogy. These methods have governing equations that are the same over a large range of frequencies, thus allowing to study in an analogous manner processes on scales ranging from few meters close to the surface down to several hundreds of kilometers depth. Unfortunately, they suffer from a significant resolution loss with depth due to the diffusive nature of the electromagnetic fields. Therefore, estimations of subsurface models that use these methods should incorporate a priori information to better constrain the models, and provide appropriate measures of model uncertainty. During my thesis, I have developed approaches to improve the static and dynamic characterization of the subsurface with plane-wave EM methods. In the first part of this thesis, I present a two-dimensional deterministic approach to perform time-lapse inversion of plane-wave EM data. The strategy is based on the incorporation of prior information into the inversion algorithm regarding the expected temporal changes in electrical conductivity. This is done by incorporating a flexible stochastic regularization and constraints regarding the expected ranges of the changes by using Lagrange multipliers. I use non-l2 norms to penalize the model update in order to obtain sharp transitions between regions that experience temporal changes and regions that do not. I also incorporate a time-lapse differencing strategy to remove systematic errors in the time-lapse inversion. This work presents improvements in the characterization of temporal changes with respect to the classical approach of performing separate inversions and computing differences between the models. In the second part of this thesis, I adopt a Bayesian framework and use Markov chain Monte Carlo (MCMC) simulations to quantify model parameter uncertainty in plane-wave EM inversion. For this purpose, I present a two-dimensional pixel-based probabilistic inversion strategy for separate and joint inversions of plane-wave EM and electrical resistivity tomography (ERT) data. I compare the uncertainties of the model parameters when considering different types of prior information on the model structure and different likelihood functions to describe the data errors. The results indicate that model regularization is necessary when dealing with a large number of model parameters because it helps to accelerate the convergence of the chains and leads to more realistic models. These constraints also lead to smaller uncertainty estimates, which imply posterior distributions that do not include the true underlying model in regions where the method has limited sensitivity. This situation can be improved by combining planewave EM methods with complimentary geophysical methods such as ERT. In addition, I show that an appropriate regularization weight and the standard deviation of the data errors can be retrieved by the MCMC inversion. Finally, I evaluate the possibility of characterizing the three-dimensional distribution of an injected water plume by performing three-dimensional time-lapse MCMC inversion of planewave EM data. Since MCMC inversion involves a significant computational burden in high parameter dimensions, I propose a model reduction strategy where the coefficients of a Legendre moment decomposition of the injected water plume and its location are estimated. For this purpose, a base resistivity model is needed which is obtained prior to the time-lapse experiment. A synthetic test shows that the methodology works well when the base resistivity model is correctly characterized. The methodology is also applied to an injection experiment performed in a geothermal system in Australia, and compared to a three-dimensional time-lapse inversion performed within a deterministic framework. The MCMC inversion better constrains the water plumes due to the larger amount of prior information that is included in the algorithm. The conductivity changes needed to explain the time-lapse data are much larger than what is physically possible based on present day understandings. This issue may be related to the base resistivity model used, therefore indicating that more efforts should be given to obtain high-quality base models prior to dynamic experiments. The studies described herein give clear evidence that plane-wave EM methods are useful to characterize and monitor the subsurface at a wide range of scales. The presented approaches contribute to an improved appraisal of the obtained models, both in terms of the incorporation of prior information in the algorithms and the posterior uncertainty quantification. In addition, the developed strategies can be applied to other geophysical methods, and offer great flexibility to incorporate additional information when available.

Broadening the horizon--level 2.5 of the HUPO-PSI format for molecular interactions.

BACKGROUND: Molecular interaction Information is a key resource in modern biomedical research. Publicly available data have previously been provided in a broad array of diverse formats, making access to this very difficult. The publication and wide implementation of the Human Proteome Organisation Proteomics Standards Initiative Molecular Interactions (HUPO PSI-MI) format in 2004 was a major step towards the establishment of a single, unified format by which molecular interactions should be presented, but focused purely on protein-protein interactions. RESULTS: The HUPO-PSI has further developed the PSI-MI XML schema to enable the description of interactions between a wider range of molecular types, for example nucleic acids, chemical entities, and molecular complexes. Extensive details about each supported molecular interaction can now be captured, including the biological role of each molecule within that interaction, detailed description of interacting domains, and the kinetic parameters of the interaction. The format is supported by data management and analysis tools and has been adopted by major interaction data providers. Additionally, a simpler, tab-delimited format MITAB2.5 has been developed for the benefit of users who require only minimal information in an easy to access configuration. CONCLUSION: The PSI-MI XML2.5 and MITAB2.5 formats have been jointly developed by interaction data producers and providers from both the academic and commercial sector, and are already widely implemented and well supported by an active development community. PSI-MI XML2.5 enables the description of highly detailed molecular interaction data and facilitates data exchange between databases and users without loss of information. MITAB2.5 is a simpler format appropriate for fast Perl parsing or loading into Microsoft Excel.

microRNAs in colon cancer: a roadmap for discovery.

Cancer omics data are exponentially created and associated with clinical variables, and important findings can be extracted based on bioinformatics approaches which can then be experimentally validated. Many of these findings are related to a specific class of non-coding RNA molecules called microRNAs (miRNAs) (post-transcriptional regulators of mRNA expression). The related research field is quite heterogeneous and bioinformaticians, clinicians, statisticians and biologists, as well as data miners and engineers collaborate to cure stored data and on new impulses coming from the output of the latest Next Generation Sequencing technologies. Here we review the main research findings on miRNA of the first 10 years in colon cancer research with an emphasis on possible uses in clinical practice. This review intends to provide a road map in the jungle of publications of miRNA in colorectal cancer, focusing on data availability and new ways to generate biologically relevant information out of these huge amounts of data.

On some numerical aspects of an active strain model in cardiac mechanics

We are interested in the development, implementation and testing of an orthotropic model for cardiac contraction based on an active strain decomposition. Our model addresses the coupling of a transversely isotropic mechanical description at the cell level, with an orthotropic constitutive law for incompressible tissue at the macroscopic level. The main differences with the active stress model are addressed in detail, and a finite element discretization using Taylor-Hood and MINI elements is proposed and illustrated with numerical examples.

Focal dystonia and the Sensory-Motor Integrative Loop for Enacting (SMILE).

Performing accurate movements requires preparation, execution, and monitoring mechanisms. The first two are coded by the motor system, the latter by the sensory system. To provide an adaptive neural basis to overt behaviors, motor and sensory information has to be properly integrated in a reciprocal feedback loop. Abnormalities in this sensory-motor loop are involved in movement disorders such as focal dystonia, a hyperkinetic alteration affecting only a specific body part and characterized by sensory and motor deficits in the absence of basic motor impairments. Despite the fundamental impact of sensory-motor integration mechanisms on daily life, the general principles of healthy and pathological anatomic-functional organization of sensory-motor integration remain to be clarified. Based on the available data from experimental psychology, neurophysiology, and neuroimaging, we propose a bio-computational model of sensory-motor integration: the Sensory-Motor Integrative Loop for Enacting (SMILE). Aiming at direct therapeutic implementations and with the final target of implementing novel intervention protocols for motor rehabilitation, our main goal is to provide the information necessary for further validating the SMILE model. By translating neuroscientific hypotheses into empirical investigations and clinically relevant questions, the prediction based on the SMILE model can be further extended to other pathological conditions characterized by impaired sensory-motor integration.

Suboptimal filtering and nonlinear time scale transformation for the analysis of multiexponential decays

Multiexponential decays may contain time-constants differing in several orders of magnitudes. In such cases, uniform sampling results in very long records featuring a high degree of oversampling at the final part of the transient. Here, we analyze a nonlinear time scale transformation to reduce the total number of samples with minimum signal distortion, achieving an important reduction of the computational cost of subsequent analyses. We propose a time-varying filter whose length is optimized for minimum mean square error

Comparative gene finding in chicken indicates that we are closing in on the set of multi-exonic widely expressed human genes.

The recent availability of the chicken genome sequence poses the question of whether there are human protein-coding genes conserved in chicken that are currently not included in the human gene catalog. Here, we show, using comparative gene finding followed by experimental verification of exon pairs by RT-PCR, that the addition to the multi-exonic subset of this catalog could be as little as 0.2%, suggesting that we may be closing in on the human gene set. Our protocol, however, has two shortcomings: (i) the bioinformatic screening of the predicted genes, applied to filter out false positives, cannot handle intronless genes; and (ii) the experimental verification could fail to identify expression at a specific developmental time. This highlights the importance of developing methods that could provide a reliable estimate of the number of these two types of genes.

Etude de l'activation et de l'inactivation pH-dépendantes des canaux ASICs (Acide-Sensing Ion Channels)

RESUME: Etude de l'activation et de l'inactivation pH-dépendantes des canaux ASICs (Acid-Sensing Ion Channels) Benoîte BARGETON, Département de Pharmacologie et de Toxicologie, Université de Lausanne, rue du Bugnon 27, CH-1005 Lausanne, Suisse Les canaux sodiques ASICs (Acid-Sensing Ion Channels) participent à la signalisation neuronale dans les systèmes nerveux périphérique et central. Ces canaux non voltage dépendants sont impliqués dans l'apprentissage, l'expression de la peur, la neurodégénération consécutive à une attaque cérébrale et la douleur. Les bases moléculaires sous-tendant leur activité ne sont pas encore totalement comprises. Ces canaux sont activés par une acidification du milieu extracellulaire et régulés, entre autres, par des ions tels que le Ca2+, le Zn2+ et le CI". La cristallisation de ASIC inactivé a été publiée. Le canal est un trimére de sous-unités identiques ou homologues. Chaque sous-unité a été décrite en analogie à un avant bras, un poignet et une main constituée d'un pouce, d'un doigt, d'une articulation, une boule β et une paume. Nous avons appliqué une approche bioinformatique systématique pour identifier les pH senseurs putatifs de ASICIa. Le rôle des pH senseurs putatifs a été testé par mutagénèse dirigée et des modifications chimiques combinées à une analyse fonctionnelle afin de comprendre comment les variations de ρ H ouvrent ces canaux. Les pH senseurs sont des acides aspartiques et glutamiques éparpillés sur la boucle extracellulaire suggérant que les changements de pH contrôlent l'activation et l'inactivation de ASIC en (dé)protonant ces résidus en divers endroits de la protéine. Par exemple lors de l'activation, la protonation des résidus à l'interface entre le pouce, la boule β et le doigt d'une même sous-unité induit un mouvement du pouce vers la bouie β et le doigt. De même lors de l'inactivation du canal les paumes des trois sous-unités formant une cavité se rapprochent. D'après notre approche bioinformatique, aucune histidine n'est impliquée dans la détection des variations de pH extracellulaire c'est-à-dire qu'aucune histidine ne serait un pH-senseur. Deux histidines de ASIC2a lient le Zn2+ et modifient l'affinité apparente du canal pour les protons. Une seule des deux est conservée parmi tous les ASICs, hASICIa H163. Elle forme un réseau de liaison hydrogène avec ses voisins conservés. L'étude détaillée de ce domaine, Pinterzone, montre son importance dans l'expression fonctionnelle des canaux. La perturbation de ce réseau par l'introduction d'un résidu hydrophobe (cystéine) par mutagénèse dirigée diminue l'expression du canal à la membrane plasmique. La modification des cystéines introduites par des réactifs spécifiques aux groupements sulfhydryle inhibe les canaux mutés en diminuant leur probabilité d'ouverture. Ces travaux décrivent les effets de l'acidification du milieu extracellulaire sur les canaux ASICs. ABSTRACT: Study of pH-dependent activation and inactivation of ASIC channels Benoîte BARGETON, Department of Pharmacology and Toxicology, University of Lausanne, Rue du Bugnon 27, CH-1G05 Lausanne, Switzerland The ASIC (Acid-Sensing Ion Channels) sodium channels are involved in neuronal signaling in the central and peripheral nervous system. These non-voltage-gated channels are involved in learning, the expression of fear, neurodegeneration after ischemia and pain sensation. The molecular bases underlying their activity are not yet fully understood. ASICs are activated by extracellular acidification and regulated, eg by ions such as Ca2+, the Zn2+ and CI". The crystallization of inactivated ASIC has been published. The channel is a trimer of identical or homologous subunits. Each subunit has been described in analogy to a forearm, wrist and hand consisting of a thumb, a finger, a knuckle, a β-ball and a palm. We applied a systematic computational approach to identify putative pH sensor(s) of ASICIa. The role of putative pH sensors has been tested by site-directed mutagenesis and chemical modification combined with functional analysis in order to understand how changes in pH open these channels. The pH sensors are aspartic and glutamic acids distributed throughout the extracellular loop, suggesting that changes in pH control activation and inactivation of ASIC by protonation / deprotonation of many residues in different parts of the protein. During activation the protonation of various residues at the interface between the finger, the thumb and the β-ball induces the movement of the thumb toward the finger and the β-ball. During inactivation of the channel the palms of the three subunits forming a cavity approach each other. No histidine has been shown to be involved in extracellular pH changes detection, i.e. no histidine is a pH- sensor. Two histidines of ASIC2 bind Zn2+ and alter the apparent affinity of channel for protons. Only one of the two His is conserved among all ASICs, hASICIa H163. This residue is part of a network of hydrogen bonding with its conserved neighbors. The detailed study of this area, the interzone, shows its importance in the functional expression of ASICs. Disturbance of this network by the introduction of hydrophobic residues decreases the cell surface channel expression. Chemical modification of the introduced cysteines by thiol reactive compounds inhibits the mutated channels by a reduction of their open probability. These studies describe the effects of extracellular acidification on ASICs. RESUME GRAND PUBLIC: Etude de l'activation et de l'inactivation pH-dépendantes des canaux ASICs (Acid-Sensing Ion Channels) Benoîte BARGETON, Département de Pharmacologie et de Toxicologie, Université de Lausanne, rue du Bugnon 27, CH-1005 Lausanne, Suisse La transmission synaptique est un processus chimique entre deux neurones impliquant des neurotransmetteurs et leurs récepteurs. Un dysfonctionnement de certains types de synapses est à l'origine de beaucoup de troubles nerveux, tels que certaine forme d'épilepsie et de l'attention. Les récepteurs des neurotransmetteurs sont de très bonnes cibles thérapeutiques dans de nombreuses neuropathologies. Les canaux ASICs sont impliqués dans la neurodégénération consécutive à une attaque cérébrale et les bloquer pourraient permettre aux patients d'avoir moins de séquelles. Les canaux ASICs sont des détecteurs de l'acidité qui apparaît lors de situations pathologiques comme l'ischémie et l'inflammation. Ces canaux sont également impliqués dans des douleurs. Cibler spécifiquement ces canaux permettrait d'avoir de nouveaux outils thérapeutiques car à l'heure actuelle l'inhibiteur de choix, l'amiloride, bloque beaucoup d'autres canaux empêchant son utilisation pour bloquer les ASICs. C'est pourquoi il faut connaître et comprendre les bases moléculaires du fonctionnement de ces récepteurs. Les ASICs formés de trois sous-unités détectent les variations de l'acidité puis s'ouvrent transitoirement pour laisser entrer des ions chargés positivement dans la cellule ce qui active la signalisation neuronale. Afin de comprendre les bases moléculaires de l'activité des ASICs nous avons déterminé les sites de liaison des protons (pH-senseurs), ligands naturels des ASICs et décrit une zone importante pour l'expression fonctionnelle de ces canaux. Grâce à une validation systématique de résultats obtenus en collaboration avec l'Institut Suisse de Bioinformatique, nous avons décrit les pH-senseurs de ASICIa. Ces résultats, combinés à ceux d'autres groupes de recherche, nous ont permis de mieux comprendre comment les ASICs sont ouverts par une acidification du milieu extracellulaire. Une seconde étude souligne le rôle structural crucial d'une région conservée parmi tous les canaux ASICs : y toucher c'est diminuer l'activité de la protéine. Ce domaine permet l'harmonisation des changements dus à l'acidification du milieu extracellulaire au sein d'une même sous-unité c'est-à-dire qu'elle participe à l'induction de l'inactivation due à l'activation du canal Cette étude décrit donc quelle région de la protéine atteindre pour la bloquer efficacement en faisant une cible thérapeutique de choix.

On-line event detection by recursive dynamic principal component analysis and gas sensor arrays under drift conditions

Leakage detection is an important issue in many chemical sensing applications. Leakage detection hy thresholds suffers from important drawbacks when sensors have serious drifts or they are affected by cross-sensitivities. Here we present an adaptive method based in a Dynamic Principal Component Analysis that models the relationships between the sensors in the may. In normal conditions a certain variance distribution characterizes sensor signals. However, in the presence of a new source of variance the PCA decomposition changes drastically. In order to prevent the influence of sensor drifts the model is adaptive and it is calculated in a recursive manner with minimum computational effort. The behavior of this technique is studied with synthetic signals and with real signals arising by oil vapor leakages in an air compressor. Results clearly demonstrate the efficiency of the proposed method.

Resting-state temporal synchronization networks emerge from connectivity topology and heterogeneity.

Spatial patterns of coherent activity across different brain areas have been identified during the resting-state fluctuations of the brain. However, recent studies indicate that resting-state activity is not stationary, but shows complex temporal dynamics. We were interested in the spatiotemporal dynamics of the phase interactions among resting-state fMRI BOLD signals from human subjects. We found that the global phase synchrony of the BOLD signals evolves on a characteristic ultra-slow (<0.01Hz) time scale, and that its temporal variations reflect the transient formation and dissolution of multiple communities of synchronized brain regions. Synchronized communities reoccurred intermittently in time and across scanning sessions. We found that the synchronization communities relate to previously defined functional networks known to be engaged in sensory-motor or cognitive function, called resting-state networks (RSNs), including the default mode network, the somato-motor network, the visual network, the auditory network, the cognitive control networks, the self-referential network, and combinations of these and other RSNs. We studied the mechanism originating the observed spatiotemporal synchronization dynamics by using a network model of phase oscillators connected through the brain's anatomical connectivity estimated using diffusion imaging human data. The model consistently approximates the temporal and spatial synchronization patterns of the empirical data, and reveals that multiple clusters that transiently synchronize and desynchronize emerge from the complex topology of anatomical connections, provided that oscillators are heterogeneous.

Ruin Theory with Excess of Loss Reinsurance and Reinstatements

The present paper studies the probability of ruin of an insurer, if excess of loss reinsurance with reinstatements is applied. In the setting of the classical Cramer-Lundberg risk model, piecewise deterministic Markov processes are used to describe the free surplus process in this more general situation. It is shown that the finite-time ruin probability is both the solution of a partial integro-differential equation and the fixed point of a contractive integral operator. We exploit the latter representation to develop and implement a recursive algorithm for numerical approximation of the ruin probability that involves high-dimensional integration. Furthermore we study the behavior of the finite-time ruin probability under various levels of initial surplus and security loadings and compare the efficiency of the numerical algorithm with the computational alternative of stochastic simulation of the risk process. (C) 2011 Elsevier Inc. All rights reserved.

SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools.

BACKGROUND: Qualitative frameworks, especially those based on the logical discrete formalism, are increasingly used to model regulatory and signalling networks. A major advantage of these frameworks is that they do not require precise quantitative data, and that they are well-suited for studies of large networks. While numerous groups have developed specific computational tools that provide original methods to analyse qualitative models, a standard format to exchange qualitative models has been missing. RESULTS: We present the Systems Biology Markup Language (SBML) Qualitative Models Package ("qual"), an extension of the SBML Level 3 standard designed for computer representation of qualitative models of biological networks. We demonstrate the interoperability of models via SBML qual through the analysis of a specific signalling network by three independent software tools. Furthermore, the collective effort to define the SBML qual format paved the way for the development of LogicalModel, an open-source model library, which will facilitate the adoption of the format as well as the collaborative development of algorithms to analyse qualitative models. CONCLUSIONS: SBML qual allows the exchange of qualitative models among a number of complementary software tools. SBML qual has the potential to promote collaborative work on the development of novel computational approaches, as well as on the specification and the analysis of comprehensive qualitative models of regulatory and signalling networks.

EGASP: the human ENCODE Genome Annotation Assessment Project.

BACKGROUND: We present the results of EGASP, a community experiment to assess the state-of-the-art in genome annotation within the ENCODE regions, which span 1% of the human genome sequence. The experiment had two major goals: the assessment of the accuracy of computational methods to predict protein coding genes; and the overall assessment of the completeness of the current human genome annotations as represented in the ENCODE regions. For the computational prediction assessment, eighteen groups contributed gene predictions. We evaluated these submissions against each other based on a 'reference set' of annotations generated as part of the GENCODE project. These annotations were not available to the prediction groups prior to the submission deadline, so that their predictions were blind and an external advisory committee could perform a fair assessment. RESULTS: The best methods had at least one gene transcript correctly predicted for close to 70% of the annotated genes. Nevertheless, the multiple transcript accuracy, taking into account alternative splicing, reached only approximately 40% to 50% accuracy. At the coding nucleotide level, the best programs reached an accuracy of 90% in both sensitivity and specificity. Programs relying on mRNA and protein sequences were the most accurate in reproducing the manually curated annotations. Experimental validation shows that only a very small percentage (3.2%) of the selected 221 computationally predicted exons outside of the existing annotation could be verified. CONCLUSION: This is the first such experiment in human DNA, and we have followed the standards established in a similar experiment, GASP1, in Drosophila melanogaster. We believe the results presented here contribute to the value of ongoing large-scale annotation projects and should guide further experimental methods when being scaled up to the entire human genome sequence.

The caveolin-binding motif of the pathogen-related yeast protein Pry1, a member of the CAP protein superfamily, is required for in vivo export of cholesteryl acetate.

Proteins belonging to the CAP superfamily are present in all kingdoms of life and have been implicated in different physiological processes. Their molecular mode of action, however, is poorly understood. Saccharomyces cerevisiae expresses three members of this superfamily, pathogen-related yeast (Pry)1, -2, and -3. We have recently shown that Pry function is required for the secretion of cholesteryl acetate and that Pry proteins bind cholesterol and cholesteryl acetate, suggesting that CAP superfamily members may generally act to bind sterols or related small hydrophobic compounds. Here, we analyzed the mode of sterol binding by Pry1. Computational modeling indicates that ligand binding could occur through displacement of a relatively poorly conserved flexible loop, which in some CAP family members displays homology to the caveolin-binding motif. Point mutations within this motif abrogated export of cholesteryl acetate but did not affect binding of cholesterol. Mutations of residues located outside the caveolin-binding motif, or mutations in highly conserved putative catalytic residues had no effect on export of cholesteryl acetate or on lipid binding. These results indicate that the caveolin-binding motif of Pry1, and possibly of other CAP family members, is crucial for selective lipid binding and that lipid binding may occur through displacement of the loop containing this motif.