Genetic and protein interactions are essential to regulate cellular machinery. Their identification has become an important aim of systems biology research. In recent years, a variety of computational network inference algorithms have been employed to reconstruct gene regulatory networks from post-genomic data. However, precisely predicting these regulatory networks remains a challenge. We began our study by assessing the ability of various network inference algorithms to accurately predict gene regulatory interactions using benchmark simulated datasets. It was observed from our analysis that different algorithms have strengths and weaknesses when identifying regulatory networks, with a gene-pair interaction (edge) predicted by one algorithm not always necessarily consistent with the other. An edge not predicted by most inference algorithms may be an important one, and should not be missed. The naïve consensus (intersection) method is perhaps the most conservative approach and can be used to address this concern by extracting the edges consistently predicted across all inference algorithms; however, it lacks credibility as it does not provide a quantifiable measure for edge weights. Existing quantitative consensus approaches, such as the inverse-variance weighted method (IVWM) and the Borda count election method (BCEM), have been previously implemented to derive consensus networks from diverse datasets. However, the former method was biased towards finding local solutions in the whole network, and the latter considered species diversity to build the consensus network. In this thesis we proposed a novel consensus approach, in which we used Fishers Combined Probability Test (FCPT) to combine the statistical significance values assigned to each network edge by a number of different networking algorithms to produce a consensus network. We tested our method by applying it to a variety of in silico benchmark expression datasets of different dimensions and evaluated its performance against individual inference methods, Bayesian models and also existing qualitative and quantitative consensus techniques. We also applied our approach to real experimental data from the yeast (S. cerevisiae) network as this network has been comprehensively elucidated previously. Our results demonstrated that the FCPT-based consensus method outperforms single algorithms in terms of robustness and accuracy. In developing the consensus approach, we also proposed a scoring technique that quantifies biologically meaningful hierarchical modular networks.

Modeling gene regulatory networks has become a problem of great interest in biology and medical research. Most common methods for learning regulatory dependencies rely on observations in the form of gene expression data. In this dissertation, computational models for gene regulation have been developed based on constrained regression by integrating comprehensive gene expression data for M. tuberculosis with genome-scale ChIP-Seq interaction data. The resulting models confirmed predictive power for expression in independent stress conditions and identified mechanisms driving hypoxic adaptation and lipid metabolism in M. tuberculosis. I then used the regulatory network model for M. tuberculosis to identify factors responding to stress conditions and drug treatments, revealing drug synergies and conditions that potentiate drug treatments. These results can guide and optimize design of drug treatments for this pathogen. I took the next step in this direction, by proposing a new probabilistic framework for learning modular structures in gene regulatory networks from gene expression and protein-DNA interaction data, combining the ideas of module networks and stochastic blockmodels. These models also capture combinatorial interactions between regulators. Comparisons with other network modeling methods that rely solely on expression data, showed the essentiality of integrating ChIP-Seq data in identifying direct regulatory links in M. tuberculosis. Moreover, this work demonstrates the theoretical advantages of integrating ChIP-Seq data for the class of widely-used module network models. The systems approach and statistical modeling presented in this dissertation can also be applied to problems in other organisms. A similar approach was taken to model the regulatory network controlling genes with circadian gene expression in Neurospora crassa, through integrating time-course expression data with ChIP-Seq data. The models explained combinatorial regulations leading to different phase differences in circadian rhythms. The Neurospora crassa network model also works as a tool to manipulate the phases of target genes.

A fundamental challenge in biology is to understand the complex gene regulatory networks which control tissue development in the mammalian embryo, and maintain homoeostasis in the adult. The cell fate decisions underlying these processes are ultimately made at the level of individual cells. Recent experimental advances in biology allow researchers to obtain gene expression profiles at single-cell resolution over thousands of cells at once. These single-cell measurements provide snapshots of the states of the cells that make up a tissue, instead of the population-level averages provided by conventional high-throughput experiments. The aim of this PhD was to investigate the possibility of using this new high resolution data to reconstruct mechanistic computational models of gene regulatory networks. In this thesis I introduce the idea of viewing single-cell gene expression profiles as states of an asynchronous Boolean network, and frame model inference as the problem of reconstructing a Boolean network from its state space. I then give a scalable algorithm to solve this synthesis problem. In order to achieve scalability, this algorithm works in a modular way, treating different aspects of a graph data structure separately before encoding the search for logical rules as Boolean satisfiability problems to be dispatched to a SAT solver. Together with experimental collaborators, I applied this method to understanding the process of early blood development in the embryo, which is poorly understood due to the small number of cells present at this stage. The emergence of blood from Flk1+ mesoderm was studied by single cell expression analysis of 3934 cells at four sequential developmental time points. A mechanistic model recapitulating blood development was reconstructed from this data set, which was consistent with known biology and the bifurcation of blood and endothelium. Several model predictions were validated experimentally, demonstrating that HoxB4 and Sox17 directly regulate the haematopoietic factor Erg, and that Sox7 blocks primitive erythroid development. A general-purpose graphical tool was then developed based on this algorithm, which can be used by biological researchers as new single-cell data sets become available. This tool can deploy computations to the cloud in order to scale up larger high-throughput data sets. The results in this thesis demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the gene regulatory networks that underpin organogenesis. Rapid technological advances in our ability to perform single-cell profiling suggest that my tool will be applicable to other organ systems and may inform the development of improved cellular programming strategies.

Modelling interactions between genes and their regulators is fundamental to understanding how, for example a disease progresses, or the impact of inserting a synthetic circuit into a cell. We use an existing method to infer regulatory networks under multiple conditions: the Joint Graphical Lasso (JGL), a shrinkage based Gaussian graphical model. We apply this method to two data sets: one, a publicly available set of microarray experiments perturbing the gram-positive bacteria Bacillus subtilis under multiple experimental conditions; the second, a set of RNA-seq samples of Mouse (Mus musculus) embryonic fibroblasts (MEFs) infected with different strains of the parasite Toxoplasma gondii. In both cases we infer a subset of the regulatory networks using relatively small sample sizes. For the Bacillus subtilis analysis we focused on the use of these regulatory networks in synthetic biology and found examples of transcriptional units active only under a subset of conditions, this information can be useful when designing circuits to have condition dependent behaviour. We developed methods for large network decomposition that made use of the condition information and showed a greater specificity of identifying single transcriptional units from the larger network using our method. Through annotating these results with known information we were able to identify novel connections and found supporting evidence for a selection of these from publicly available experimental results. Biological data collection is typically expensive and due to the relatively small sample sizes of our MEF data set we developed a novel empirical Bayes method for reducing the false discovery rate when estimating block diagonal covariance matrices. Using these methods we were able to infer regulatory networks for the host infected with either the ME49 or RH strain of the parasite. This enabled the identification of known and novel regulatory mechanisms. The Toxoplasma gondii parasite has shown to subvert host function using similar mechanisms as cancers and through our analysis we were able to identify genes, networks and ontologies associated with cancer, including connections that have not previously been associated with T. gondii infection. Finally a Shiny application was developed as an online resource giving access to the Bacillus subtilis inferred networks with interactive methods for exploring the networks including expansion of sub networks and large network decomposition.

Magister Scientiae - MSc (Pharmacy Administration and Policy Regulation) / Due to inadequacy of data on the effectiveness of medicines regulatory systems in Zambia, this study was framed. The aim was to evaluate legislative provisions for medicines regulation under three legalregulatory- frameworks in place over the period from 1995 to 2015. The study was structured in two distinct phases: the first involved document review of available legislation and secondary data relevant to the subject matter, covering the study period; the second involved a questionnaire survey for health practitioners to gather opinions on the effectiveness of the medicines regulatory systems in Zambia. Assessment of secondary data reported by Ministry of Health, and World Health Organisation on treatment outcomes and medicines regulation was conducted. Reviewed data showed relative reduction in incidence of some selected diseases of national importance. It was also evident that the regulatory systems had improved considerably over the study period. Responses from Health Practitioners and other players in the health and pharmaceutical sectors indicated that they were aware of medicines regulatory requirements, supported the need for medicines regulation, and indicated the need for regional collaboration and increased public awareness raising as means for improving current medicines regulatory systems. It was recommended that more comprehensive studies be undertaken to establish causal relationships between medicines regulatory systems, and disease outcomes. A further recommendation was made to implement more integrated information management systems in the Ministry of Health, and the Zambia Medicines Regulatory Authority.

When creating and administering regulations, regulators have to demonstrate that regulations accomplish intended societal outcomes at costs that do not outweigh their benefits. While regulators have this responsibility as custodians of the regulatory ecosystem, they are also required to create and administer regulations transparently and impartially, addressing the needs and concerns of all stakeholders involved. This is in addition to regulators having to deal with various administrative bottlenecks, competing internal priorities, as well as financial and human resource limitations. Nonetheless, governments, regulated parties, citizens and interest groups can each express different views on the relevance and performance of a piece of regulation. These views range from too many regulations burdening business operations to perceptions that crises in society are the results of insufficient regulations. As such, regulators have to be innovative, employing methods that show that regulations are effective, and justify the introduction, evolution or repeal of regulations. The regulatory process has been the topic of various studies with several such studies exploring the use of information systems at the software level to confirm compliance with regulations and evaluate issues related to non-compliance. The rationale is that if information systems can improve operational functions in organizations, they can also help measure compliance. However, the research focus has been on enabling regulated parties to comply with regulations rather than on enabling regulators to assess or enforce compliance or show that regulations are effective. Regulators need to address concerns of too much regulations or too little regulations with data-driven evidence especially in this age of big data and artificial intelligence enhanced tools. A method that facilitates evidencebased decision-making using data for enacting, implementing and reviewing regulations is now inevitable. In response to the above challenges, this thesis explores the use of a goaloriented modelling method and a data analytics software, to create a method that enables monitoring, assessing and reporting on the effectiveness of regulations and regulatory initiatives. This Goal-oriented Regulatory Intelligence Method (GoRIM) provides an intelligent approach to regulatory management, as well as a feedback loop in the use of data from and within the regulatory ecosystem to create and administer regulations. To demonstrate its applicability, GoRIM was applied to three case studies involving regulators in three different real regulatory scenarios, and its feasibility and utility were evaluated. The results indicate that regulators found GoRIM promising in enabling them to show, with evidence, whether their regulations are effective.

Submitted by Rafaela Moraes (rafaela.moraes@fgv.br) on 2016-09-12T13:53:36Z No. of bitstreams: 1 Dissertação final - Eduardo Nunes - 110911.pdf: 2445774 bytes, checksum: 5a9e59fca83a6a50ff485c12ef6ce047 (MD5) / Approved for entry into archive by Rafaela Moraes (rafaela.moraes@fgv.br) on 2016-09-12T13:54:26Z (GMT) No. of bitstreams: 1 Dissertação final - Eduardo Nunes - 110911.pdf: 2445774 bytes, checksum: 5a9e59fca83a6a50ff485c12ef6ce047 (MD5) / Approved for entry into archive by Rafaela Moraes (rafaela.moraes@fgv.br) on 2016-09-12T13:55:06Z (GMT) No. of bitstreams: 1 Dissertação final - Eduardo Nunes - 110911.pdf: 2445774 bytes, checksum: 5a9e59fca83a6a50ff485c12ef6ce047 (MD5) / Made available in DSpace on 2016-09-12T13:55:45Z (GMT). No. of bitstreams: 1 Dissertação final - Eduardo Nunes - 110911.pdf: 2445774 bytes, checksum: 5a9e59fca83a6a50ff485c12ef6ce047 (MD5) Previous issue date: 2011 / The regulatory system varies depending on the country's institutional endowment. A component of the regulatory system is regulatory governance, namely the set of safeguards that limit discretionary actions of the regulator. In Brazil, one of the safeguards is the institutional design of regulatory agencies. This design consists of a series of factors among which stands out autonomy, commonly divided into administrative, financial and political. The ultimate goal of this study is to evaluate the financial autonomy of federal regulatory agencies. The greater financial autonomy is, the more robust regulatory governance tends to be, because the institutional design plays a better role as safeguard. Strengthened governance contributes to the stability of rules, reduces regulatory risk and enhances the attraction of private investments, which ultimately leverage the country's economic development. To achieve the ultimate goal, it will be held an exploratory, descriptive and explanatory research. The means used are bibliographic, documentary and multiple cases. Each case is selected in a non-probabilistic way by typicality and accessibility, in that order, in order to reach contrasting results (theoretical replication). These criteria determine the choice of all federal regulatory agencies, with the exception of ANAC, because of the accessibility of its budgetary and financial data. Thus, from data of ANEEL, ANATEL, ANP, ANVISA, ANS, ANA, ANTAQ, ANTT and ANCINE for the years 2002 to 2010, four indicators are calculated: budget availability, budget execution, financial execution, and budget and financial overlay. The averages of these partial indicators comprise a comprehensive indicator of financial autonomy. The results are compared between the agencies, between the generations of the agencies and between the sectors of activity of the agencies, using the technique of analysis of variance with a significance level of five percent. The evaluation of the financial autonomy of federal regulatory agencies is unexpected. Rejecting the initial hypotheses, the regulatory agencies of first generation have inferior results to those agencies from second and third generation, and infrastructure agencies have inferior results to social agencies. These results highlight the need to revise the model of budgetary and financial management designed for federal regulatory agencies. The legal provision of own sources of funds is not sufficient to ensure the financial autonomy of agencies to the extent that the central government makes use of increasingly frequent resources impoundments. / O sistema regulatório varia conforme a dotação institucional do país. Um componente do sistema regulatório é a governança regulatória, isto é, o conjunto de salvaguardas que limita ações discricionárias do regulador. No caso brasileiro, uma das salvaguardas é o desenho institucional das agências reguladoras. Este desenho é formado por uma série de elementos entre os quais se destaca a autonomia, comumente dividida em administrativa, financeira e política. O objetivo final deste estudo é avaliar a autonomia financeira das agências reguladoras federais. Quanto maior a autonomia financeira, mais robusta tende a ser a governança regulatória, pois melhor é o papel desempenhado pelo desenho institucional das agências como salvaguarda. Fortalecida, a governança contribui para a estabilidade de regras, reduz o risco regulatório e potencializa a atração de investimentos privados, o que, em última análise, alavanca o desenvolvimento econômico do país. Para alcançar o objetivo final, realiza-se pesquisa exploratória, descritiva e explicativa. Os meios utilizados são bibliográficos, documentais e estudo de múltiplos casos. Cada caso é selecionado de forma não probabilística por tipicidade e por acessibilidade, nesta ordem, a fim de se chegar a resultados contrastantes (replicação teórica). Estes critérios determinam a escolha de todas as agências reguladoras federais, com exceção da ANAC, em virtude da acessibilidade de seus dados orçamentários e financeiros. Assim, a partir dos dados da ANEEL, ANATEL, ANP, ANVISA, ANS, ANA, ANTAQ, ANTT e ANCINE referentes aos anos de 2002 a 2010, são calculados quatro indicadores: de disponibilidade orçamentária, de execução orçamentária, de execução financeira e de sobreposição orçamentária e financeira. As médias aritméticas desses indicadores parciais compõem um indicador global de autonomia financeira. Os resultados encontrados são comparados entre as agências, entre as gerações das agências e entre os setores de atuação das agências, utilizando-se a técnica da análise de variância a um nível de significância de cinco por cento. A avaliação da autonomia financeira das agências reguladoras federais é surpreendente. Rejeitando as hipóteses iniciais, as agências reguladoras de primeira geração obtêm resultados inferiores às agências de segunda e terceira geração, e as agências de infraestrutura resultados inferiores às agências sociais. Estes resultados evidenciam a necessidade de revisão do modelo de gestão orçamentária e financeira concebido para as agências reguladoras federais. A previsão legal de fontes próprias de recursos não é suficiente para assegurar a autonomia financeira das agências na medida em que o governo central faz uso cada vez mais frequente de contingenciamentos de recursos.

Esta dissertação tem como objetivo geral analisar se e de que modo o cooperativismo pode ser um meio eficiente para auxiliar a concretização do ideal democrático de uma economia de mercado com inclusão econômica e social, oportunizando o desenvolvimento de caráter endógeno, em um modelo desenvolvimentista com participação da sociedade civil e novas formas de organização econômica, favorecendo a emergência de uma nova classe empresarial. Como objetivos específicos, figuram analisar as origens do cooperativismo e as conformações específicas deste sistema, enquanto valores e ideais de sociedade; analisar os aspectos econômicos e institucionais do cooperativismo; analisar o cooperativismo na atual Constituição brasileira, de acordo com os valores que regem essa norma e sua relevância teleológica; bem como, formular sugestões de princípios de organização institucional do cooperativismo, para potencializar seu emprego como meio de concretizar os ideais democráticos e suprir carências brasileiras, como as existentes nas áreas de educação, infraestrutura e saúde. São empregadas conjuntamente diretrizes teóricas tanto da área econômica quanto de áreas correlatas ao tema, com o intuito de demonstrar a possibilidade de adoção do cooperativismo como ferramenta de desenvolvimento social. O trabalho é composto por quatro partes, sendo a primeira focada na análise das origens do cooperativismo. Na segunda parte, são analisados os aspectos econômicos e institucionais do cooperativismo. Esse item do trabalho foi complementado por três anexos de cunho jurídico: um sobre a evolução da legislação referente ao cooperativismo no Brasil, o segundo sobre a personalidade jurídica das cooperativas e o terceiro sobre as sociedades cooperativas no Código Civil. Na terceira parte, consta a análise do cooperativismo na Constituição Federal de 1988. Na quarta seção, são formuladas propostas de princípios de organização institucional do cooperativismo. Mais precisamente, dado que o ambiente e os arranjos institucionais têm acentuada influência sobre o comportamento dos agentes econômicos, são citadas propostas para mitigar eventuais dificuldades microeconômicas próprias das cooperativas, bem como para constituir incentivos na adoção do cooperativismo como ferramenta auxiliar na concretização dos ideais democráticos e na supressão das carências atuais existentes no Brasil. / This paper has as its main objective to analyze whether and how cooperativism can be an efficient means to assist the realization of the democratic ideal of a market economy with economic and social inclusions, providing opportunities for the development of endogenous character, in a developmental model with participation of civil society and new forms of economic organization, favoring the emergence of a new entrepreneurial class. Specific objectives include analyzing the origins of the cooperativism and the specific conformations of this system, while values and ideals of society; analyze the economic and institutional aspects of cooperativism; analyze cooperativism in the current Brazilian Constitution, in accordance with the values that govern this standard and its teleological significance; as well as make suggestions of principles of institutional organization of cooperativism to enhance their employment as a means of achieving democratic ideals and meet Brazilian needs, as those existing in the areas of education, infrastructure and health. They are employed together both theoretical guidelines of the economic area as well as of those related to correlated areas, in order to demonstrate the possibility of adoption of cooperativism as a tool for social development. The paper consists of four parts, the first focused on the analysis of the origins of cooperativism. In the second part, the economic and institutional aspects of cooperativism are analyzed. This item was complemented by three appendixes of legal nature: one on the evolution of the legislation on cooperativism in Brazil, the second about the legal status of cooperatives and the third on the cooperative societies in the Civil Code. The third part consists in the analysis of cooperativism in the Federal Constitution of 1988. In the fourth section, proposed principles of institutional organization of cooperativism are formulated. More precisely, since the environment and institutional arrangements have marked influence on the behavior of economic agents, proposals are cited to mitigate eventual microeconomic difficulties characteristic of cooperatives, as well as provide incentives for the adoption of cooperativism as an auxiliary tool in the realization of democratic ideals and suppression of current deficiencies in Brazil.

The relationship between a pathogen and its host is a complex series of events that occurs at the molecular level and is controlled by transcriptional and protein interactions. To facilitate the understanding of these mechanisms in Aspergillus flavus and Zea mays, three approaches were taken: 1) the development of a predicted interactome for Z. mays (PiZeaM), 2) the development of co-expression networks for Z. mays and A. flavus from RNA-seq data, and 3) the development of causal inference networks depicting interactions between the host and the pathogen. PiZeaM is the genome-wide roadmap of protein-protein interactions that occur within Z. mays. PiZeaM helps create a novel map of the interactions in Z. mays in response to biotic and abiotic stresses. To further support the predicted interactions, an analysis of microarray-based gene expression was used to produce a gene co-expression network. PiZeaM was able to capture conserved resistance pathways involved involved in the response to pathogens, abiotic stress and development. Gene Co-expression networks were developed by the simultaneous use of correlations to develop networks for differentially expressed genes, resistance marker genes, pathogenicity genes, and genes involved is secondary metabolism in Z. mays and A. flavus. From these networks, correlation and anti-correlation of host and pathogen gene expression was detected, revealing genes that potentially interact at different stages of pathogenesis. Finally, causal gene regulatory relationships were inferred using partial correlation analysis of Z. mays infected with A. flavus over a 3 day period. The gene regulatory network (GRN) sheds light on the specifics of the mechanisms of pathogenesis and resistance that govern the Z. mays-A. flavus interaction. The direct product of this research is the understanding of key transcription factors and signaling genes involved in resistance. This body of research highlights how PPIs and GRNs can be utilized to identify biomarkers and gene functions in both Z. mays and A. flavus.

The incidence of colorectal cancer (CRC) is increasing and the prognosis for patients with advanced or metastatic disease is relatively poor. Immunotherapies hold great promise, but deploying them effectively in CRC patients will require further knowledge of the complex cellular and molecular interactions that occur between intestinal tumours and the host immune system. The objective of this study is to understand the mechanisms by which lack of immune cell regulation in the gut can drive the formation of colon adenocarcinomas. In addition, this work aims to identify new mechanisms involved in progression to metastatic disease. Using mouse model systems, we found that aberrant activity of Treg cells deficient in IL-10 can promote inflammation-driven CRC. IL-10 deficient Tregs have increased capacity to drive tumourigenesis compared to their CD4⁺ effector T cell counterparts. RNA sequencing revealed specific upregulation of several genes, including a newly-described cytokine, in tumour-promoting Tregs. We explored cytokine regulation and the tumour microenvironment, and show that the inflammatory cytokine IL-6 and TGFÎ2 are necessary for tumour formation in this model. Moreover, disease is associated with a marked stromal cell signature that is induced as a consequence of Treg deficiency in IL-10 production. Gp38⁺ stromal cells are dominant producers of IL-6, and potent ECM modellers. Furthermore, tumours driven by IL-10 deficient Tregs express high amounts of the pro-mesenchymal transcription factor Sox4. Using combined in vitro and in vivo analyses, we confirm that Sox4 is involved in tumour growth and characterise its expression in CRC patients. Collectively, our findings suggest that Tregs and stromal cells act together to foster a microenvironment that promotes disease progression, notably through the expression of Sox4 in tumour cells. These findings open an exciting avenue to explore the phenotype of tumour-promoting Tregs and to study Sox4 function in metastatic disease.