Assessing the functional coherence of modules found in multiple-evidence networks from Arabidopsis

<p>Abstract</p> <p>Background</p> <p>Combining multiple evidence-types from different information sources has the potential to reveal new relationships in biological systems. The integrated information can be represented as a relationship network, and clustering the network can suggest possible functional modules. The value of such modules for gaining insight into the underlying biological processes depends on their functional coherence. The challenges that we wish to address are to define and quantify the functional coherence of modules in relationship networks, so that they can be used to infer function of as yet unannotated proteins, to discover previously unknown roles of proteins in diseases as well as for better understanding of the regulation and interrelationship between different elements of complex biological systems.</p> <p>Results</p> <p>We have defined the functional coherence of modules with respect to the Gene Ontology (GO) by considering two complementary aspects: (i) the fragmentation of the GO functional categories into the different modules and (ii) the most representative functions of the modules. We have proposed a set of metrics to evaluate these two aspects and demonstrated their utility in <it>Arabidopsis thaliana</it>. We selected 2355 proteins for which experimentally established protein-protein interaction (PPI) data were available. From these we have constructed five relationship networks, four based on single types of data: PPI, co-expression, co-occurrence of protein names in scientific literature abstracts and sequence similarity and a fifth one combining these four evidence types. The ability of these networks to suggest biologically meaningful grouping of proteins was explored by applying Markov clustering and then by measuring the functional coherence of the clusters.</p> <p>Conclusions</p> <p>Relationship networks integrating multiple evidence-types are biologically informative and allow more proteins to be assigned to a putative functional module. Using additional evidence types concentrates the functional annotations in a smaller number of modules without unduly compromising their consistency. These results indicate that integration of more data sources improves the ability to uncover functional association between proteins, both by allowing more proteins to be linked and producing a network where modular structure more closely reflects the hierarchy in the gene ontology.</p

Systems responses to progressive water stress in durum wheat

Durum wheat is susceptible to terminal drought which can greatly decrease grain yield. Breeding to improve crop yield is hampered by inadequate knowledge of how the physiological and metabolic changes caused by drought are related to gene expression. To gain better insight into mechanisms defining resistance to water stress we studied the physiological and transcriptome responses of three durum breeding lines varying for yield stability under drought. Parents of a mapping population (Lahn x Cham1) and a recombinant inbred line (RIL2219) showed lowered flag leaf relative water content, water potential and photosynthesis when subjected to controlled water stress time transient experiments over a six-day period. RIL2219 lost less water and showed constitutively higher stomatal conductance, photosynthesis, transpiration, abscisic acid content and enhanced osmotic adjustment at equivalent leaf water compared to parents, thus defining a physiological strategy for high yield stability under water stress. Parallel analysis of the flag leaf transcriptome under stress uncovered global trends of early changes in regulatory pathways, reconfiguration of primary and secondary metabolism and lowered expression of transcripts in photosynthesis in all three lines. Differences in the number of genes, magnitude and profile of their expression response were also established amongst the lines with a high number belonging to regulatory pathways. In addition, we documented a large number of genes showing constitutive differences in leaf transcript expression between the genotypes at control non-stress conditions. Principal Coordinates Analysis uncovered a high level of structure in the transcriptome response to water stress in each wheat line suggesting genome-wide co-ordination of transcription. Utilising a systems-based approach of analysing the integrated wheat's response to water stress, in terms of biological robustness theory, the findings suggest that each durum line transcriptome responded to water stress in a genome-specific manner which contributes to an overall different strategy of resistance to water stress

Homologie en Programmation Génétique<br />Application à la résolution d'un problème inverse

Evolutionary Algorithms (EA) are search methods working iteratively on a population of potential solutions that are randomly selected and modified. Genetic Programming (GP) is an EA that allows automatic search for programs, usually represented as syntax trees (TGP) or linear sequences (LGP). Two mechanisms perform the random variations needed to obtain new programs : the mutation operator (local variation) and the crossover operator (programs recombination). The crossover operator blindly exchanges parts of programs without taking the context into account, this is a "brutal" operation that may be responsible of the uncontrolled growth of programs during evolution. Mainly inspired by the homologous recombinaison of DNA strands, we introduce the Maximum Homologous Crossover for LGP. The MHC ensures, thanks to a measure of similarity, that recombinaison of programs is respectful. We show on classical GP benchmarks, e.g. the symbolic regression problem, that when using MHC the search process is less brutal and that an accurate control of programs size is also possible. These results are used to address a real world problem : the inversion of atmospheric components. We show that, with a constant computational effort, it is also possible to find teams of inversion predictors that outperform standard models.Les Algorithmes Évolutionnaires (AE) sont des méthodes de recherche par itération de sélections et de variations aléatoires sur une population de solutions potentielles. La Programmation Génétique (PG) est un AE qui permet la recherche automatique de programmes et qui manipule des représentations complexes : arbres (PGA) ou listes de longueur variables (PGL). Les variations aléatoires permettant de créer de nouveaux programmes peuvent être des modifications locales (mutations) ou des recombinaisons de programmes (croisements). L'opérateur de croisement recombine aléatoirement des sous-parties de programmes sans tenir compte du contexte : c'est une opération «brutale» qui est une des causes supposées de la croissance incontrôlée de la taille des programmes. Inspirés par la recombinaison homologue de l'ADN, nous définissons, le Croisement par Maximum d'Homologie (CMH) pour la PGL. A partir d'une mesure de similarité entre les expressions à recombiner, le CMH favorise les échanges qui respectent les structures communes préexistantes. La capacité du CMH à effectuer une recherche moins brutale et à permettre un contrôle précis de la taille des programmes est mise en évidence sur des problèmes classiques de PG comme l'approximation de fonctions par régression symbolique. En partant des différents résultats obtenus, nous appliquons notre méthode à la résolution d'un problème réel : l'inversion des composantes atmosphériques. De plus, nous montrons comment, à coût constant, il est possible de rechercher des combinaisons de modèles inverses dont les performances sont supérieures aux modèles standards

Monitoring Genetic Variations in Variable Length Evolutionary Algorithms

International audienceInitially, Artificial Evolution focuses on Evolutionary Algorithms handling solutions coded in fixed length structures. In this context, the role of crossover is clearly the mixing of information between solutions. The development of Evolutionary Algorithms operating on structures with variable length, of which genetic programming is one of the most representative instances, opens new questions on the effects of crossover. Beside mixing, two new effects are identified : the diffusion of information inside solutions and the variation of the solutions sizes. In this paper, we propose a experimental framework to study these three effects and apply it on three different crossovers for genetic programming : the Standard Crossover, the One-Point Crossover and the Maximum Homologous Crossover. Exceedingly different behaviors are reported leading us to consider the necessary future decoupling of the mixing, the diffusion and the size variation

How ambiguous is the inverse problem of ocean color in coastal waters?

International audienceThe inverse problem of ocean color consists in deriving the inherent optical properties (IOP) of marine particles from a reflectance spectrum measured at the sea surface. Such a problem is ill-posed or ambiguous because of the nonuniqueness of the solution; that is, several combinations of IOP values can lead to a unique reflectance spectrum. Currently, great efforts are made in the development of inverse methods to accurately retrieve the IOPs. However, many fewer studies have been devoted to the analysis of the ambiguities, which affect yet the error on the IOPs retrieval. In this paper, the ambiguities related to the ocean color problem in coastal waters are characterized and their implications for inverse modeling are studied. A synthetic data set is created on the basis of radiative transfer modeling. The simulations are constrained using in situ observations and statistical rules to make the data set realistic. The ambiguity rate of remote sensing reflectance (Rrs) spectra is around 90%, thus meaning that the ocean color problem is extremely ambiguous. The influence of the ambiguities on the IOPs retrieval is evaluated. It is demonstrated that the error that is ascribed to the occurrence of ambiguity is equal to the dispersion of all the plausible IOPs solutions. The ambiguity error made on the total absorption coefficient is shown to be greater in highly absorbing water mass. On the other hand, the ambiguity error made on the total backscattering coefficient is higher in turbid scattering waters. Finally, different strategies to reduce the effects of ambiguities are discussed

Ambiguities in the inversion of the Ocean Colour: Problems and Solutions

The inverse problem of ocean colour consists in deriving the inherent optical properties (IOP) of marine particles from a reflectance spectrum measured at the sea surface. Such a problem is ill-posed or ambiguous because of the non-uniqueness of the solution; i.e. several combinations ofIOP values can lead to a unique reflectance spectrum. Currently, great efforts are made in the development of inverse methods to accurately retrieve the IOP. However, much less studies have been devoted to the analysis of the ambiguities, which affect yet the error on the IOP retrieval. In this paper, a set a measures suitable to characterized the ambiguities of an inverse problem are introduced and used to describe the ocean colour problem. The ambiguities of the IOP retrieval are evaluated and their implications for inverse modelling are studied. Finally, different strategies to reduce the effects of ambiguities are discussed

Sensitivity of the retrieval of the inherent optical properties of marine particles in coastal waters to the directional variations and the polarization of the reflectance

International audience[1] The influences of the directional variations and the polarization of the marine reflectance on the retrieval of the inherent optical properties (IOP) (i.e., absorption, scattering, and backscattering coefficients) of water constituents in coastal waters are examined. First, an inversion algorithm based on artificial neural network (NN) methodology is developed using a synthetic data set. The simulations were carried out using a radiative transfer model that accounts for the polarization state of light in the ocean. The simulated data included various directional effects of the particles. The data set is also constrained by observations collected in optically representative coastal waters. In particular, the relationships that exist between the IOP were taken into account, thus making the data set realistic. The results showed that the total IOP were correctly retrieved while the performance of the algorithm to derive the IOP of each water component significantly degrades. However, the inclusion of the directional variations and the polarization of the reflectance in the algorithm improved the accuracy of retrieval of the scattering properties by 15% - 60% and 65% - 75%, respectively. The phytoplankton and noncovarying particles (i.e., nonalgal particles) scattering and backscattering coefficients were derived with an accuracy of 25% and 15% respectively. These results demonstrate the potential of using the polarized signal to separate the total IOP into contribution of biogenic and highly refractive particles in coastal waters. Therefore the development of in situ instrumentation able to measure the polarization properties of the particles is recommended