In the past two decades, molecular cell biology has transitioned from a traditional descriptive science into a quantitative science that systematically measures cellular dynamics on different levels of genome, transcriptome and proteome. Along with this transition emerges the interdisciplinary field of systems biology, which aims to unravel complex interactions in biological systems through integrating experimental data into qualitative or quantitative models and computer simulations. In this dissertation, we applied various systems biology tools to investigate two important problems with respect to cellular activation dynamics and reprograming. Specifically, in the first section of the dissertation, we focused on lipopolysaccharide (LPS)-mediated priming and tolerance: a reprogramming in cytokine production in macrophages pretreated with specific doses of LPS. Though both priming and tolerance are important in the immune system's response to pathogens, the molecular mechanisms still remain unclear. We computationally investigated all network topologies and dynamics that are able to generate priming or tolerance in a generic three-node model. Accordingly, we found three basic priming mechanisms and one tolerance mechanism. Existing experimental evidence support these in silico found mechanisms. In the second part of the dissertation, we applied stochastic modeling and simulations to investigate the phenotypic transition of bacteria E.coli between normally-growing cells and persister cells (growth-arrested phenotype), and how this process can contribute to drug resistance. We built up a complex computational model capturing the molecular mechanism on both single cell level and population level. The paper also proposed a novel way to accelerate the phenotypic transition from persister cells to normally growing cell under resonance activation. The general picture of phenotypic transitions should be applicable to a broader context of biological systems, such as T cell differentiation and stem cell reprogramming. / Ph. D.

MicroRNAs represent a special class of small (~21–25 nucleotides) non-coding RNA molecules which exert powerful post-transcriptional control over gene expression in eukaryotes. Indeed microRNAs likely represent the most abundant class of regulators in animal gene regulatory networks. This study describes the recovery and network analyses of a suite of homologous microRNA targets recovered through two different prediction methods for whole gene regions across twelve Drosophila species. Phylogenetic criteria under an accepted tree topology were used as a reference frame to 1) make inference into microRNA-target predictions, 2) study mathematical properties of microRNA-gene regulatory networks, 3) and conduct novel phylogenetic analyses using character data derived from weighted edges of the microRNA-target networks. This study investigates the evidences of natural selection and phylogenetic signatures inherent within the microRNA regulatory networks and quantifies time and mutation necessary to rewire a microRNA regulatory network. Selective factors that appear to operate upon seed aptamers include cooperativity (redundancy) of interactions and transcript length. Topological analyses of microRNA regulatory networks recovered significant enrichment for a motif possessing a redundant link in all twelve species sampled. This would suggest that optimization of the whole interactome topology itself has been historically subject to natural selection where resilience to attack have offered selective advantage. It seems that only a modest number of microRNA–mRNA interactions exhibit conservation over Drosophila cladogenesis. The decrease in conserved microRNA-target interactions with increasing phylogenetic distance exhibited a cure typical of a saturation phenomena. Scale free properties of a network intersection of microRNA target predictions methods were found to transect taxonomic hierarchy.

Dans les agroécosystèmes, les réseaux trophiques sont souvent structurés à partir de la plante d’intérêt agronomique, qui permet aux herbivores qui lui sont associés de se développer, notamment les bioagresseurs. La monoculture de bananiers a permis au charançon du bananier (Cosmopolites sordidus) de prospérer. Les larves de C. sordidus se nourrissent exclusivement de bananiers et provoquent leur chute, réduisant fortement le rendement dans la plupart des régions de production. Cette thèse a cherché à élucider la structure et le fonctionnement du réseau trophique de la bananeraie et particulièrement les interactions trophiques qui lient le C. sordidus aux autres espèces. L’objectif appliqué en ligne de mire était de favoriser les prédateurs généralistes pour augmenter la régulation naturelle de C. sordidus.1. Quel est l’effet de l’ajout d’une plante de couverture sur la prédation de C. sordidus ? En utilisant une variété de méthodes – isotopes stables, piégeage, infestation artificielle de bananiers, nous avons testé avec succès l’hypothèse selon laquelle l’enherbement induit, via le développement de proies alternatives, un changement de régime alimentaire des prédateurs généralistes, une augmentation de leurs abondances et une plus forte prédation des oeufs de C. sordidus.2. Quel est la structure du réseau trophique ? Nous avons combiné le séquençage haut-débit (technologie 454) avec le concept de codes-barres à ADN pour identifier les proies présentes dans le contenu stomacal des consommateurs. Nous avons utilisé un marqueur chloroplastique (boucle P6 trnL) pour identifier le bol alimentaire des herbivores, et un marqueur mitochondrial (mini-CO1) pour les prédateurs. Cette approche a permis de détecter des espèces qui n’avaient pas été échantillonnées, d’identifier les prédateurs naturels de C. sordidus au champ, et de quantifier les interactions à l’échelle des populations.3. Comment la structure du réseau trophique peut-elle influencer la régulation de C. sordidus ? Nous avons cherché les différents éléments structuraux (motifs) présents dans le réseau trophique de deux agroécosystèmes bananiers (sur sol nu et sur sol enherbé), et analysé leurs fonctions. Nous avons notamment décelé un motif composé de 4 espèces (2 ressources et 2 consommateurs) qui est représenté en grand nombre par rapport à un modèle neutre de réseau trophique. Ce motif s’est révélé systématiquement déséquilibré en faveur d’une proie, ce qui démontre qu’une distribution asymétrique des forces d’interactions permet de structurer le réseau. L’analyse de la position de C. sordidus dans les motifs décelés a permis de révéler ses interactions préférentielles avec les autres espèces de la communauté.Cette thèse montre comment le couplage de méthodes innovantes et complémentaires permet d’avoir une approche globale du fonctionnement trophique de l’agroécosystème. Les résultats montrent l’importance des ressources primaires (autres que la plante cultivée) sur la structuration du réseau trophique des arthropodes et sur le potentiel de régulation des bioagresseurs. Ce travail illustre également le lien entre la structure globale d’une communauté et l’évaluation des fonctions qui y sont associées / In agroecosystems, food webs are often structured from the crop, which enables the associated herbivores, including pests, to develop. For instance, monoculture in banana fields allowed the development of the banana weevil (Cosmopolites sordidus) populations. Borrowing larvae of C. sordidus cause banana plants topple over, which dampens the yield in most production areas. In this Ph.D. thesis, we attempted to disclose the structure and function of the banana food web, and particularly the trophic interactions that link banana weevil to others species. The applied perspective was to enhance population of generalist predators in order to increase the natural regulation of the pest.1. What is the effect of adding a cover crop on the predation of the pest?By using a variety of methods - stable isotopes analyses, trapping, artificial infestation of banana trees, we successfully tested the hypothesis according to which the addition of a cover crop, by enabling population of alternative preys to develop in the system, induces a change in predator diet, an increase of predator densities, and a greater predation rate on the eggs of C. sordidus.2. How is structured the food web?We combined next generation sequencing (454 technology) with the DNA barcoding concept to identify prey into gut contents of consumers. We used a chloroplastic marker (trnL) to identify the diet of herbivores, and a mitochondrial marker (CO1) for predators. This approach enabled the detection of unexpected species, the identification of the natural enemies of the pest, and the weighting of trophic interactions at the population scale.3. How can food web structure influence pest regulation?We searched structural elements (network motifs) occurring in the food webs of two banana agroecosystems (on bare soil and with cover crop), and we inferred the system functions. We detected the “bi-fan” size-4 motif, which occurred more frequently in the cover cropped food web than in random food webs. Interestingly, this motif was unbalanced for one of the two resources, illustrating the asymmetrical distribution of interaction strengths that shapes food web structure. The analysis of the position of C. sordidus within key motifs revealed its preferential interactions with other species of the community.This Ph.D. thesis emphasizes how linking innovative and complementary methods provides a comprehensive approach of the trophic functioning of the banana agroecosystem. Our results show the importance of primary resources (other than the cultivated crop) on the structure of arthropods’ food webs and on the pest regulation potential. This work also illustrates the link between the community structure and the evaluation of associated functions (i.e. pest regulation)

Die Organisation von Handelsstrukturen bringt seit je her weitreichende soziale, politische sowie ökonomische Implikationen mit sich. Da die zugrundeliegenden Dynamiken von Handelssystemen a priori unbekannt sind bieten Konzepte aus der Theorie komplexer Systeme nützliche Werkzeuge, um neue Muster zu entdecken, sowie neue Hypothesen zu den Vorgängen innerhalb der Handelssysteme zu entwickeln. Einen nützlichen Ansatz stellen dabei komplexe Netzwerke dar, da Handelsströme zwischen ökonomischen Einheiten sinnvoll als Knoten und Verbindungen im Netzwerk darstellbar sind. In dieser Arbeit erweitern wir spezielle Methoden auf komplexen Netzwerken, um die Netzwerk-Topologie des Handels auf globaler und auf nationaler Ebene zu untersuchen. Auf dem Level einzelner Industriesektoren erhalten wir neue Einblicke in die topologische Struktur des internationalen Handelsnetzwerks. Dazu führen wir neue Netzwerkmaße ein, welche die Funktion von Knoten in Subgraphen unter dem Blickwinkel, dass das Gesamtsystem durch ein Netzwerk aus mehreren Subnetzwerken dargestellt wird, beschreiben. Im Zuge der Globalisierung gewinnen bilaterale Handelsabkommen bei Entscheidungsträgern an Aufmerksamkeit und werden in zunehmender Zahl verhandelt. Wir entwickeln in dieser Arbeit einen neuen Ansatz, um die Auswirkungen dieser Abkommen auf die beteiligten Ökonomien zu analysieren und zu quantifizieren. Weiterhin behandeln wir die Fragestellung, in welchem Maß Handel als ein Übermittler von Nachfrage- und Angebotsveränderungen auf andere Industrien angesehen werden kann. Schließlich betrachten wir Handelsnetzwerke auf der Ebene von einzelnen Firmen und beschreiben die Funktion von einzelnen Knoten, insbesondere deren Rolle innerhalb von 3er-Motiven. Obwohl alle Methoden und Maße, die wir im Zuge dieser Arbeit einführen, aus Fragen im Kontext des Handels motiviert sind, sind die methodischen Konzepte auf komplexe Netzwerke in anderen Forschungsrichtungen anwendbar. / The organization of trade and its patterns and structures have always had far reaching implications among social, political and economic dimensions. The underlying dynamics of trade systems are often a priori unknown and concepts from complex system theory provide useful tools to discover new patterns and to develop new hypotheses on the mechanisms of the system. Complex networks offer a particularly useful approach to trade systems, as trade flows between economic entities can be intuitively and meaningfully represented as nodes and links in a network. In this thesis, we extend specific methods of complex networks with a focus on the relations between different subnetworks to investigate the network topology of trade on both the global and national scale. On an aggregation level considering individual industries as nodes, we obtain new insights about the topological structure of the international trade network by introducing new network measures that characterize the roles of nodes in subnetworks from a network of networks perspective. During the process of globalization bilateral trade agreements have received rising attention among policy makers and have been negotiated at an increasing pace. Here, we develop a framework to analyze and quantify impacts of these agreements on the involved economies. A further question that we address is to what extent trade can be regarded as a mediator of demand and supply spillovers to other industries. Finally, we look into trade networks at the scale of individual business firms and describe the role of nodes with a focus on 3-node motifs. Although all new methods and measures introduced in this thesis are motivated by questions in the context of trade, the methodological concepts are widely applicable to complex networks of other research disciplines.

Complexity underlying life is largely governed by the dynamics of interaction within and between living and nonliving entities. Evolutionary strategy games are extensively used in modelling and understanding complex behaviors in a wide range of fields including theoretical biology, social interactions, economics, politics, defense and security. Strategy games are said to distill the key elements of interactions be- tween real-world entities and organizations - one of the challenges lies in determining the mapping of complex real life situation dynamics to that of a certain game. That leads us to the two major research questions outlined below. In this thesis, we are taking evolutionary games a step further to investigate the interplay between local and global dynamics, where local dynamics are repre- sented by locally pairwise interactions among the population's players governed by the Iterated Prisoner's Dilemma game. To represent the global dynamics, two main modelling ideas are proposed, in the first model; a mixed evolutionary game is in- troduced where players are competing globally on the population level in a minority game. The interplay between local and global dynamics in this model represents the interplay between different scopes of competition between the same players. Sec- ondly, we introduce a model for studying the effect of sharing global information concerning a population of players, shedding light on how global information can alter the emerging dynamics of local interactions. Furthermore, the thesis addresses the question of whether games - with different dynamics - have unique signatures (footprints) that can be used in recognizing and differentiating among them, and whether these footprints are consistent along the evolutionary path of these games. We show here that by building winning networks between players, and determining network motifs of these winning networks, we can obtain motifs' counts signals that are sufficient to categorize and recognize the game's utility matrix used by the players. We also demonstrate that these footprints - motifs' counts - are consistent along the evolutionary path of the games, due to a hyper-cyclic behavior that exists between strategies. Finally, we show that this approach is capable of identifying whether a certain population is driven by local dynamics or both local and global dynamics using the proposed mixed game.

Submitted by Daniel Chada (danielc2112@gmail.com) on 2017-01-10T13:25:02Z No. of bitstreams: 1 chada.phd.2017.01.09.pdf: 5177057 bytes, checksum: a6174d9f2ba0b373776e750def2a23aa (MD5) / Approved for entry into archive by ÁUREA CORRÊA DA FONSECA CORRÊA DA FONSECA (aurea.fonseca@fgv.br) on 2017-01-12T14:03:51Z (GMT) No. of bitstreams: 1 chada.phd.2017.01.09.pdf: 5177057 bytes, checksum: a6174d9f2ba0b373776e750def2a23aa (MD5) / Made available in DSpace on 2017-01-23T11:48:10Z (GMT). No. of bitstreams: 1 chada.phd.2017.01.09.pdf: 5177057 bytes, checksum: a6174d9f2ba0b373776e750def2a23aa (MD5) Previous issue date: 2016-12-08 / Este trabalho consiste em três contribuições independentes do âmbito da modelagem cognitiva ao campo de management science. O primeiro aborda Experience Recognition, uma teoria inicialmente introduzida por Linhares e Freitas [91]. Aqui ela é estendida e delineada, além de se discutir suas contribuições para a ciência cognitiva e management science. A segunda contribuição introduz a framework cognitiva chamada Rotational Sparse Distributed Memory, e fornece uma aplicação-exemplo de suas características como substrato para um fortemente relevante campo da management science: redes semânticas. A contribuição final aplica Rotational Sparse Distributed Memory para a modelagem de motifs de rede, flexibilidade dinâmica e organização hierárquica, três resultados de forte impacto na literatura recente de neurociência. A relevância de uma abordagem baseada na modelagem neurocientífica para a decision science é discutida. / This work is comprised of three independent contributions from the realm of cognitive modeling to management science. The first addresses Experience Recognition, a theory first introduced by Linhares and Freitas [91]. Here it is extended and better defined, and also its contribution to cognitive science and management science are discussed. The second contribution introduces a cognitive framework called Rotational Sparse Distributed Memory, and provides a sample application of its characteristics as a substrate for a highly relevant subject in management science: semantic networks. The final contribution applies Rotational Sparse Distributed Memory to modeling network motifs, dynamic flexibility and hierarchical organization, all highly impactful results in recent neuroscience literature. The relevance of a neuroscientific modeling approach towards a cognitive view of decision science are discussed.