Millions of dollars change hands daily through online auction markets. Online trading communities like eBay and Amazon.com are emerging as increasingly important factors of the economy. Various Reputation systems are important components in such electronic markets. Existing evidence suggests that there are a number of problems with such systems. This paper presents an empirical exploration of reputation systems. Two studies of Tradera’s discussion forums are reported. The result of the first, pilot study suggests that both sellers and buyers are worried about getting a retaliatory negative feedback if they leave a negative feedback for an unsatisfactory transaction from their trading parties. Retaliation from the non-paying bidders seems to be the most severe threat and trouble for sellers. A set of negative feedbacks were then gathered from Tradera and data were manually analyzed in order to verify the results from the preliminary study. The results from the second study confirmed the result of the pilot study. A general evaluation of Tradera’s current reputation system is made based on the results of the second study. This paper aims to make a contribution to the literature on online reputation system by developing a typology of seller complaints about Tradera buyers and providing a tentative definition of retaliatory negative feedback based on the findings of both studies. Proposed solutions to the problems of non-payment and feedback retaliation are also presented.

Doctor of Philosophy / Department of Psychology / Patrick A. Knight / Over 50 years of research has supported the positive relationship between feedback and performance improvement. A recent meta-analysis suggests that feedback may not be beneficial for performance, and that it may actually be harmful for performance (Kluger & DeNisi, 1996). This study suggests that these inconsistencies exist because positive and negative feedback are treated like opposite sides of the same scale. In reality, positive and negative feedback are two very different types of information and should be treated differently. Current research examines feedback delivered interpersonally. When delivering feedback this way, positive feedback is often accepted while negative feedback is rejected. The current study states that alternate delivery methods may be better for the acceptance and use of negative feedback. It is suggested that negative feedback received directly from the task itself may be more accepted, more intrinsically motivating, and result in less negative emotion for receivers than negative feedback from interpersonal sources. Two hundred and two university students participated in a simple computer simulation task. They received feedback regarding their performance and then participated in the task a second time. Results revealed no differences between conditions in acceptance, possibly a result of task. When receiving negative feedback from the task, participants experienced greater intrinsic motivation than when receiving negative feedback from interpersonal sources. Finally, negative feedback from the task resulted in less negative emotion than negative feedback from interpersonal sources. By removing the interpersonal interaction, the task removes a great deal of negative emotion associated with the supervisor. This study revealed great potential for the task as a source of negative feedback. Although the workforce may not be ready for a full task-feedback system, it may serve as a good supplement for interpersonal feedback and worthy of future research in the field setting.

Yes / The extracellular signal-regulated kinase 1/2 (ERK1/2) mitogen-activated protein kinase (MAPK) signalling pathway regulates many cellular functions, including proliferation, differentiation, and transformation. To reliably convert external stimuli into specific cellular responses and to adapt to environmental circumstances, the pathway must be integrated into the overall signalling activity of the cell. Multiple mechanisms have evolved to perform this role. In this review, we will focus on negative feedback mechanisms and examine how they shape ERK1/ 2 MAPK signalling. We will first discuss the extensive number of negative feedback loops targeting the different components of the ERK1/2 MAPK cascade, specifically the direct posttranslational modification of pathway components by downstream protein kinases and the induction of de novo gene synthesis of specific pathway inhibitors. We will then evaluate how negative feedback modulates the spatiotemporal signalling dynamics of the ERK1/2 pathway regarding signalling amplitude and duration as well as subcellular localisation. Aberrant ERK1/2 activation results in deregulated proliferation and malignant transformation in model systems and is commonly observed in human tumours. Inhibition of the ERK1/2 pathway thus represents an attractive target for the treatment of malignant tumours with increased ERK1/2 activity. We will, therefore, discuss the effect of ERK1/2 MAPK feedback regulation on cancer treatment and how it contributes to reduced clinical efficacy of therapeutic agents and the development of drug resistance.

No description available.

The purpose of this experimental study is to examine the effects of recasts on narrowing overgeneralized grammar in the second language (L2). The study involved testing three major hypotheses of the mechanisms underlying recasts: the direct contrast hypothesis (Saxton, 1997, 2000), the additional input hypothesis (Gass, 1997; Gass & Mackey, 2007; Long, 1996, 2007), and the enhanced salience hypothesis (Leeman, 2003). Two structures (adjective ordering and indirect passives) were selected for this study, mainly because it was assumed that Japanese learners of English might produce overgeneralized rules that allow incorrect structures because of their first language (L1) influence. The participants were 97 Japanese university students learning English as a foreign language in Japan. They were randomly assigned to four treatment groups: recast (the REC Group), non-contingent positive evidence (the POS Group), recast plus additional input (the REC+ Group), and input with enhanced salience (the SAL Group). A pretest, posttest, and delayed-posttest design were employed. The measurement instruments were an oral production task, elicited imitation task, and untimed grammaticality judgment task, each of which was designed to elicit participants’ implicit and explicit knowledge about adjective ordering and indirect passives. Thus, the independent variable was the treatment conditions, and the dependent variable were the test scores regarding ungrammaticality of the overgeneralized rules of the target structures. After data screening, the data from 75 of the 97 participants were analyzed for adjective ordering, and the data from 90 participants were analyzed for indirect passives. The results showed that the POS Group did not improve on all the measures for adjective ordering and indirect passives; thus, it was suggested that positive evidence was not sufficient for the participants to narrow overgeneralized rules for the target structures. The findings indicated that for adjective ordering, medium effect sizes for the comparison of the POS and REC Groups were obtained on the grammaticality judgment tests for the pretest-posttest and pretest-delayed posttest comparisons. Thus, based on these effect sizes, the direct contrast hypothesis was partially supported (i.e., for one of the two structures and one measure of the three tests). Furthermore, on the basis of the results that the REC and REC+ Groups did not differ significantly on any measure and that on the adjective-ordering grammaticality judgment tests, the comparison between the REC+ Group and the POS Group obtained a medium effect size for the pretest-delayed posttest comparison, the provision of recasts in the REC and REC+ Groups was effective at least for the adjective-ordering grammaticality judgment tests; however, additional input alone did not have an impact on L2 learners’ retreat from the overgeneralized rules. Finally, the results showed that the POS and SAL Groups did not differ significantly and that there existed a difference in the performance on the adjective-ordering grammaticality judgment tests between the REC Group and the SAL Groups. Salience might not be effective in helping L2 learners retreat from overgeneralized rules, and the enhanced salience hypothesis can be interpreted as being limited to learning some linguistic structures. In conclusion, the present study provides empirical evidence that L2 learners can persist in using incorrect overgeneralized rules due to L1 rules and that ten tokens of the target structures are not effective for L2 learners to retreat from the overgeneralized rules. Furthermore, the findings lend support to the direct contrast hypothesis as a mechanism underlying recasts for one of the two target structures. / Teaching & Learning

Heuristic estimates of probabilities may be an obstacle to decision making within High Reliability Organizations. Accident reports have found that two from each other separate phenomenon, Blame Culture and Type 1 processing constitutes a particularily serious threat to decision making. The present study (N = 70) investigated if a perceived risk of negative feedback and cognitive load would lead to more heuristic estimates on the Conjunction Fallacy. Three experiment conditions were included in the study: Negative feedback, cognitive load and control. The results were non-significant for both negative feedback and cognitive load. Furthermore, the estimated negative affect was higher when violations to the Conjunction Rule was made. Previous studies showing that high scores on the Cognitive Reflection Test (CRT) indicate less sensitivity to conjunction fallacies, were replicated. The present study concluded that the CRT may be a strong predictor of the Conjunction Fallacy.

Uma das principais áreas de pesquisa em Biologia de Sistemas refere-se à descoberta de redes biológicas a partir de conjuntos de dados de microarrays. Estas redes consistem de um grande número de genes cujos níveis de expressão afetam os outros genes de vários modos. Nesta tese, apresenta-se uma nova maneira de analisar os conjuntos de dados de microarrays, com base nos diferentes tipos de ciclos encontrados entre os genes das redes de co-expressão construídas com dados quantificados obtidos a partir dos microarrays. A entrada do método de análise é formada pelos dados brutos, um conjunto de genes de interesse (por exemplo, genes de uma via conhecida) e uma função (ativador ou inibidor) destes genes. A saída do método é um conjunto de ciclos. Um ciclo é um caminho fechado com todos os vértices (exceto o primeiro e o último) distintos. Graças à nova forma de encontrar relações entre os genes, é possível uma interpretação mais robusta das correlações dos genes, porque os ciclos estão associados a mecanismos de feedback, que são muito comuns em redes biológicas. A hipótese é que feedbacks negativos permitem encontrar relações entre os genes que podem ajudar a explicar a estabilidade do processo regulatório dentro da célula. Ciclos de feedback positivo, por outro lado, podem mostrar a quantidade de desequilíbrio de uma determinada célula em um determinado momento. A análise baseada em ciclos permite identificar a relação estequiométrica entre os genes da rede. Esta metodologia proporciona uma melhor compreensão da biologia do tumor. Portanto, as principais contribuições desta tese são: (i) um novo método de análise baseada em ciclos; (ii) um novo método de classificação; (iii) e, finalmente, aplicação dos métodos e a obtenção de resultados práticos. A metodologia proposta foi utilizada para analisar os genes de quatro redes fortemente relacionadas com o câncer - apoptose, glicólise, ciclo celular e NF B - em tecidos do tipo mais agressivo de tumor cerebral (Gliobastoma multiforme - GBM) e em tecidos cerebrais saudáveis. A maioria dos pacientes com GBM morrem em menos de um ano, essencialmente nenhum paciente tem sobrevivência a longo prazo, por isso estes tumores têm atraído atenção significativa. Os principais resultados nesta tese mostram que a relação estequiométrica entre genes envolvidos na apoptose, glicólise, ciclo celular e NF B está desequilibrada em amostras de GBM em comparação as amostras de controle. Este desequilíbrio pode ser medido e explicado pela identificação de um percentual maior de ciclos positivos nas redes das primeiras amostras. Esta conclusão ajuda a entender mais sobre a biologia deste tipo de tumor. O método de classificação baseado no ciclo proposto obteve as mesmas métricas de desempenho como uma rede neural, um método clássico de classificação. No entanto, o método proposto tem uma vantagem significativa em relação às redes neurais. O método de classificação proposto não só classifica as amostras, fornecendo diagnóstico, mas também explica porque as amostras foram classificadas de uma certa maneira em termos dos mecanismos de feedback que estão presentes/ausentes. Desta forma, o método fornece dicas para bioquímicos sobre possíveis experiências laboratoriais, bem como sobre potenciais genes alvo de terapias. / One of the main research areas in Systems Biology concerns the discovery of biological networks from microarray datasets. These networks consist of a great number of genes whose expression levels affect each other in various ways. We present a new way of analyzing microarray datasets, based on the different kind of cycles found among genes of the co-expression networks constructed using quantized data obtained from the microarrays. The input of the analysis method is formed by raw data, a set of interest genes (for example, genes from a known pathway) and a function (activator or inhibitor) of these genes. The output of the method is a set of cycles. A cycle is a closed walk, in which all vertices (except the first and last) are distinct. Thanks to the new way of finding relations among genes, a more robust interpretation of gene correlations is possible, because cycles are associated with feedback mechanisms that are very common in biological networks. Our hypothesis is that negative feedbacks allow finding relations among genes that may help explaining the stability of the regulatory process within the cell. Positive feedback cycles, on the other hand, may show the amount of imbalance of a certain cell in a given time. The cycle-based analysis allows identifying the stoichiometric relationship between the genes of the network. This methodology provides a better understanding of the biology of tumors. As a consequence, it may enable the development of more effective treatment therapies. Furthermore, cycles help differentiate, measure and explain the phenomena identified in healthy and diseased tissues. Cycles may also be used as a new method for classification of samples of a microarray (cancer diagnosis). Compared to other classification methods, cycle-based classification provides a richer explanation of the proposed classification, that can give hints on the possible therapies. Therefore, the main contributions of this thesis are: (i) a new cycle-based analysis method; (ii) a new microarray samples classification method; (iii) and, finally, application and achievement of practical results. We use the proposed methodology to analyze the genes of four networks closely related with cancer - apoptosis, glucolysis, cell cycle and NF B - in tissues of the most aggressive type of brain tumor (Gliobastoma multiforme – GBM) and in healthy tissues. Because most patients with GBMs die in less than a year, and essentially no patient has long-term survival, these tumors have drawn significant attention. Our main results show that the stoichiometric relationship between genes involved in apoptosis, glucolysis, cell cycle and NF B pathways is unbalanced in GBM samples versus control samples. This dysregulation can be measured and explained by the identification of a higher percentage of positive cycles in these networks. This conclusion helps to understand more about the biology of this tumor type. The proposed cycle-based classification method achieved the same performance metrics as a neural network, a classical classification method. However, our method has a significant advantage with respect to neural networks. The proposed classification method not only classifies samples, providing diagnosis, but also explains why samples were classified in a certain way in terms of the feedback mechanisms that are present/absent. This way, the method provides hints to biochemists about possible laboratory experiments, as well as on potential drug target genes.

A via RAS/RAF/MEK/ERK é frequentemente hiperativada em diversos tumores. Em leucemias sua ativação pode ocorrer, dentre outros mecanismos, a partir de mutações pontuais nos genes da família RAS, que são relevantes nas leucemias linfóide e mielóide agudas (LLA e LMA), ou a partir da atividade da tirosina-quinase BCR-ABL, que é responsável por promover a tumorigênese na leucemia mielóide crônica (LMC) e em alguns casos de LLA. A hiperativação dessa via estimula a proliferação celular e, consequentemente, a produção de espécies reativas de oxigênio (ROS), que é um dos principais mecanismos envolvidos com a indução de senescência celular em tumores. Assim sendo, as células tumorais que apresentam o gene RAS mutado são criticamente dependentes de mecanismos de feedback para regular a ativação da via. Jang et al. demonstraram que a ubiquitina-ligase HUWE1 atua em um mecanismo de feedback negativo que controla a ativação de ERK1/2 e apesar de amplamente estudada no contexto da tumorigênese, a atuação dessa molécula em eventos relacionados à leucemogênese ainda não foi descrita. No presente estudo, linhagens celulares leucêmicas e células tronco e progenitoras hematopoiéticas humanas (HSPCs) com mutação KRASG12V foram transduzidas com partículas lentivirais miR-E para o silenciamento gênico de HUWE1. Ensaios de proliferação celular, apoptose, análise do ciclo celular, produção de ROS e análise da expressão gênica e proteica foram realizados nas linhagens celulares; análise do crescimento cumulativo, área de formação de cobblestones, capacidade clonogênica e análise do perfil de diferenciação celular foram realizados nas HSPCs. Nas linhagens celulares observouse que o silenciamento de HUWE1 reduziu a capacidade proliferativa das linhagens Nalm-6, K562 e THP-1, porém não causou nenhum prejuízo à capacidade proliferativa da linhagem HL-60. Além disso, causou a redução da produção de ROS (p<0,05), associada à redução das taxas de apoptose (p<0,01), principalmente na linhagem K562, na qual também promoveu a ativação de ERK1/2 . Em HSPCs, observou-se a redução da capacidade proliferativa das culturas que expressavam o oncogene KRASG12V associado ao silenciamento de HUWE1. Nas mesmas condições foi observada uma drástica redução na capacidade clonogênica das HSPCs (p<0,001), em especial as do tipo BFU-E. O silenciamento de HUWE1 também alterou o perfil de diferenciação celular para a linhagem monocítica. Os resultados sugerem que HUWE1 pode participar do processo de leucemogênese e diferenciação de HSPCs humanas participando na modulação da via RAS/RAF/MEK/ERK. / The RAS/RAF/MEK/ERK pathway is frequently hyperactivated in several tumors. In leukemia, this activation can arise, among other mechanisms, from point mutations in the RAS genes, which are important in acute lymphoid leukemia (ALL) and acute myeloid leukemia (AML), or from chromosomal translocations such as the BCR-ABL gene, which is a driver mutation in chronic myeloid leukemia (CML) and some cases of ALL. The hyperactivation of this pathway stimulates cell proliferation and, consequently, the production of reactive oxygen species (ROS), which is one of the main mechanisms involved with induction of cellular senescence in tumors. Thus, tumor cells that harbor the mutated RAS gene are critically dependent on feedback mechanisms to regulate pathway activation. Jang et al. demonstrated that the ubiquitinligase HUWE1 acts on a negative feedback mechanism that controls the activation of ERK1/2. Although widely studied in the context of tumorigenesis, the role of this molecule in events related to leukemogenesis has not yet been described. In this study, leukemia cell lines and human hematopoietic stem and progenitors cells (HSPCs) with KRASG12V mutation were transduced with miR-E lentiviral particles for HUWE1 knockdown. Cell proliferation, apoptosis, cell cycle analysis, ROS production and analysis of gene and protein expression were performed in cell lines; cumulative growth analysis, cobblestones area formations, clonogenic capacity and differentiation profile analysis were performed in HSPCs. In cell lines, it was observed that HUWE1 knockdown reduced the proliferative capacity of Nalm-6, K562 and THP-1, but not of HL-60. Besides that, it caused a reduction in ROS production (p<0,05), associated with reduction of apoptosis rates (p<0,01), especially in K562 in which it also promoted activation of ERK1/2. In HSPCs, a reduction of the proliferative capacity was observed in cultures expressing KRASG12V in combination with HUWE1 knockdown. In the same conditions, a drastic reduction of clonogenic capacity (p<0,001), especially of BFU-E colonies, was observed. HUWE1 knockdown also changed differentiation profile to the monocytic lineage. Results suggest that HUWE1 might play a role in leukemogenesis process and differentiation of human HSPCs, acting in the modulation of RAS/RAF/MEK/ERK.

A via RAS/RAF/MEK/ERK é frequentemente hiperativada em diversos tumores. Em leucemias sua ativação pode ocorrer, dentre outros mecanismos, a partir de mutações pontuais nos genes da família RAS, que são relevantes nas leucemias linfóide e mielóide agudas (LLA e LMA), ou a partir da atividade da tirosina-quinase BCR-ABL, que é responsável por promover a tumorigênese na leucemia mielóide crônica (LMC) e em alguns casos de LLA. A hiperativação dessa via estimula a proliferação celular e, consequentemente, a produção de espécies reativas de oxigênio (ROS), que é um dos principais mecanismos envolvidos com a indução de senescência celular em tumores. Assim sendo, as células tumorais que apresentam o gene RAS mutado são criticamente dependentes de mecanismos de feedback para regular a ativação da via. Jang et al. demonstraram que a ubiquitina-ligase HUWE1 atua em um mecanismo de feedback negativo que controla a ativação de ERK1/2 e apesar de amplamente estudada no contexto da tumorigênese, a atuação dessa molécula em eventos relacionados à leucemogênese ainda não foi descrita. No presente estudo, linhagens celulares leucêmicas e células tronco e progenitoras hematopoiéticas humanas (HSPCs) com mutação KRASG12V foram transduzidas com partículas lentivirais miR-E para o silenciamento gênico de HUWE1. Ensaios de proliferação celular, apoptose, análise do ciclo celular, produção de ROS e análise da expressão gênica e proteica foram realizados nas linhagens celulares; análise do crescimento cumulativo, área de formação de cobblestones, capacidade clonogênica e análise do perfil de diferenciação celular foram realizados nas HSPCs. Nas linhagens celulares observouse que o silenciamento de HUWE1 reduziu a capacidade proliferativa das linhagens Nalm-6, K562 e THP-1, porém não causou nenhum prejuízo à capacidade proliferativa da linhagem HL-60. Além disso, causou a redução da produção de ROS (p<0,05), associada à redução das taxas de apoptose (p<0,01), principalmente na linhagem K562, na qual também promoveu a ativação de ERK1/2 . Em HSPCs, observou-se a redução da capacidade proliferativa das culturas que expressavam o oncogene KRASG12V associado ao silenciamento de HUWE1. Nas mesmas condições foi observada uma drástica redução na capacidade clonogênica das HSPCs (p<0,001), em especial as do tipo BFU-E. O silenciamento de HUWE1 também alterou o perfil de diferenciação celular para a linhagem monocítica. Os resultados sugerem que HUWE1 pode participar do processo de leucemogênese e diferenciação de HSPCs humanas participando na modulação da via RAS/RAF/MEK/ERK. / The RAS/RAF/MEK/ERK pathway is frequently hyperactivated in several tumors. In leukemia, this activation can arise, among other mechanisms, from point mutations in the RAS genes, which are important in acute lymphoid leukemia (ALL) and acute myeloid leukemia (AML), or from chromosomal translocations such as the BCR-ABL gene, which is a driver mutation in chronic myeloid leukemia (CML) and some cases of ALL. The hyperactivation of this pathway stimulates cell proliferation and, consequently, the production of reactive oxygen species (ROS), which is one of the main mechanisms involved with induction of cellular senescence in tumors. Thus, tumor cells that harbor the mutated RAS gene are critically dependent on feedback mechanisms to regulate pathway activation. Jang et al. demonstrated that the ubiquitinligase HUWE1 acts on a negative feedback mechanism that controls the activation of ERK1/2. Although widely studied in the context of tumorigenesis, the role of this molecule in events related to leukemogenesis has not yet been described. In this study, leukemia cell lines and human hematopoietic stem and progenitors cells (HSPCs) with KRASG12V mutation were transduced with miR-E lentiviral particles for HUWE1 knockdown. Cell proliferation, apoptosis, cell cycle analysis, ROS production and analysis of gene and protein expression were performed in cell lines; cumulative growth analysis, cobblestones area formations, clonogenic capacity and differentiation profile analysis were performed in HSPCs. In cell lines, it was observed that HUWE1 knockdown reduced the proliferative capacity of Nalm-6, K562 and THP-1, but not of HL-60. Besides that, it caused a reduction in ROS production (p<0,05), associated with reduction of apoptosis rates (p<0,01), especially in K562 in which it also promoted activation of ERK1/2. In HSPCs, a reduction of the proliferative capacity was observed in cultures expressing KRASG12V in combination with HUWE1 knockdown. In the same conditions, a drastic reduction of clonogenic capacity (p<0,001), especially of BFU-E colonies, was observed. HUWE1 knockdown also changed differentiation profile to the monocytic lineage. Results suggest that HUWE1 might play a role in leukemogenesis process and differentiation of human HSPCs, acting in the modulation of RAS/RAF/MEK/ERK.

Uma das principais áreas de pesquisa em Biologia de Sistemas refere-se à descoberta de redes biológicas a partir de conjuntos de dados de microarrays. Estas redes consistem de um grande número de genes cujos níveis de expressão afetam os outros genes de vários modos. Nesta tese, apresenta-se uma nova maneira de analisar os conjuntos de dados de microarrays, com base nos diferentes tipos de ciclos encontrados entre os genes das redes de co-expressão construídas com dados quantificados obtidos a partir dos microarrays. A entrada do método de análise é formada pelos dados brutos, um conjunto de genes de interesse (por exemplo, genes de uma via conhecida) e uma função (ativador ou inibidor) destes genes. A saída do método é um conjunto de ciclos. Um ciclo é um caminho fechado com todos os vértices (exceto o primeiro e o último) distintos. Graças à nova forma de encontrar relações entre os genes, é possível uma interpretação mais robusta das correlações dos genes, porque os ciclos estão associados a mecanismos de feedback, que são muito comuns em redes biológicas. A hipótese é que feedbacks negativos permitem encontrar relações entre os genes que podem ajudar a explicar a estabilidade do processo regulatório dentro da célula. Ciclos de feedback positivo, por outro lado, podem mostrar a quantidade de desequilíbrio de uma determinada célula em um determinado momento. A análise baseada em ciclos permite identificar a relação estequiométrica entre os genes da rede. Esta metodologia proporciona uma melhor compreensão da biologia do tumor. Portanto, as principais contribuições desta tese são: (i) um novo método de análise baseada em ciclos; (ii) um novo método de classificação; (iii) e, finalmente, aplicação dos métodos e a obtenção de resultados práticos. A metodologia proposta foi utilizada para analisar os genes de quatro redes fortemente relacionadas com o câncer - apoptose, glicólise, ciclo celular e NF B - em tecidos do tipo mais agressivo de tumor cerebral (Gliobastoma multiforme - GBM) e em tecidos cerebrais saudáveis. A maioria dos pacientes com GBM morrem em menos de um ano, essencialmente nenhum paciente tem sobrevivência a longo prazo, por isso estes tumores têm atraído atenção significativa. Os principais resultados nesta tese mostram que a relação estequiométrica entre genes envolvidos na apoptose, glicólise, ciclo celular e NF B está desequilibrada em amostras de GBM em comparação as amostras de controle. Este desequilíbrio pode ser medido e explicado pela identificação de um percentual maior de ciclos positivos nas redes das primeiras amostras. Esta conclusão ajuda a entender mais sobre a biologia deste tipo de tumor. O método de classificação baseado no ciclo proposto obteve as mesmas métricas de desempenho como uma rede neural, um método clássico de classificação. No entanto, o método proposto tem uma vantagem significativa em relação às redes neurais. O método de classificação proposto não só classifica as amostras, fornecendo diagnóstico, mas também explica porque as amostras foram classificadas de uma certa maneira em termos dos mecanismos de feedback que estão presentes/ausentes. Desta forma, o método fornece dicas para bioquímicos sobre possíveis experiências laboratoriais, bem como sobre potenciais genes alvo de terapias. / One of the main research areas in Systems Biology concerns the discovery of biological networks from microarray datasets. These networks consist of a great number of genes whose expression levels affect each other in various ways. We present a new way of analyzing microarray datasets, based on the different kind of cycles found among genes of the co-expression networks constructed using quantized data obtained from the microarrays. The input of the analysis method is formed by raw data, a set of interest genes (for example, genes from a known pathway) and a function (activator or inhibitor) of these genes. The output of the method is a set of cycles. A cycle is a closed walk, in which all vertices (except the first and last) are distinct. Thanks to the new way of finding relations among genes, a more robust interpretation of gene correlations is possible, because cycles are associated with feedback mechanisms that are very common in biological networks. Our hypothesis is that negative feedbacks allow finding relations among genes that may help explaining the stability of the regulatory process within the cell. Positive feedback cycles, on the other hand, may show the amount of imbalance of a certain cell in a given time. The cycle-based analysis allows identifying the stoichiometric relationship between the genes of the network. This methodology provides a better understanding of the biology of tumors. As a consequence, it may enable the development of more effective treatment therapies. Furthermore, cycles help differentiate, measure and explain the phenomena identified in healthy and diseased tissues. Cycles may also be used as a new method for classification of samples of a microarray (cancer diagnosis). Compared to other classification methods, cycle-based classification provides a richer explanation of the proposed classification, that can give hints on the possible therapies. Therefore, the main contributions of this thesis are: (i) a new cycle-based analysis method; (ii) a new microarray samples classification method; (iii) and, finally, application and achievement of practical results. We use the proposed methodology to analyze the genes of four networks closely related with cancer - apoptosis, glucolysis, cell cycle and NF B - in tissues of the most aggressive type of brain tumor (Gliobastoma multiforme – GBM) and in healthy tissues. Because most patients with GBMs die in less than a year, and essentially no patient has long-term survival, these tumors have drawn significant attention. Our main results show that the stoichiometric relationship between genes involved in apoptosis, glucolysis, cell cycle and NF B pathways is unbalanced in GBM samples versus control samples. This dysregulation can be measured and explained by the identification of a higher percentage of positive cycles in these networks. This conclusion helps to understand more about the biology of this tumor type. The proposed cycle-based classification method achieved the same performance metrics as a neural network, a classical classification method. However, our method has a significant advantage with respect to neural networks. The proposed classification method not only classifies samples, providing diagnosis, but also explains why samples were classified in a certain way in terms of the feedback mechanisms that are present/absent. This way, the method provides hints to biochemists about possible laboratory experiments, as well as on potential drug target genes.