QAPgrid: A Two Level QAP-Based Approach for Large-Scale Data Analysis and Visualization

Background: The visualization of large volumes of data is a computationally challenging task that often promises rewarding new insights. There is great potential in the application of new algorithms and models from combinatorial optimisation. Datasets often contain “hidden regularities” and a combined identification and visualization method should reveal these structures and present them in a way that helps analysis. While several methodologies exist, including those that use non-linear optimization algorithms, severe limitations exist even when working with only a few hundred objects. Methodology/Principal Findings: We present a new data visualization approach (QAPgrid) that reveals patterns of similarities and differences in large datasets of objects for which a similarity measure can be computed. Objects are assigned to positions on an underlying square grid in a two-dimensional space. We use the Quadratic Assignment Problem (QAP) as a mathematical model to provide an objective function for assignment of objects to positions on the grid. We employ a Memetic Algorithm (a powerful metaheuristic) to tackle the large instances of this NP-hard combinatorial optimization problem, and we show its performance on the visualization of real data sets. Conclusions/Significance: Overall, the results show that QAPgrid algorithm is able to produce a layout that represents the relationships between objects in the data set. Furthermore, it also represents the relationships between clusters that are feed into the algorithm. We apply the QAPgrid on the 84 Indo-European languages instance, producing a near-optimal layout. Next, we produce a layout of 470 world universities with an observed high degree of correlation with the score used by the Academic Ranking of World Universities compiled in the The Shanghai Jiao Tong University Academic Ranking of World Universities without the need of an ad hoc weighting of attributes. Finally, our Gene Ontology-based study on Saccharomyces cerevisiae fully demonstrates the scalability and precision of our method as a novel alternative tool for functional genomics

Recent advances in clustering methods for protein interaction networks

The increasing availability of large-scale protein-protein interaction data has made it possible to understand the basic components and organization of cell machinery from the network level. The arising challenge is how to analyze such complex interacting data to reveal the principles of cellular organization, processes and functions. Many studies have shown that clustering protein interaction network is an effective approach for identifying protein complexes or functional modules, which has become a major research topic in systems biology. In this review, recent advances in clustering methods for protein interaction networks will be presented in detail. The predictions of protein functions and interactions based on modules will be covered. Finally, the performance of different clustering methods will be compared and the directions for future research will be discussed

Distribution and Activation of Catecholaminergic Neurons in the Brain of Male Plainfin Midshipman Fish: Divergence in Behavior and Reproductive Phenotype

The plainfin midshipman fish, Porichthys notatus, provides an excellent opportunity for delimiting the influence of neurochemical content on vertebrate vocal behavior, in part because the production and recognition of social-acoustic signals is vital to their reproductive behavior. There are two distinct reproductive male morphs that follow divergent developmental trajectories with corresponding alternative reproductive tactics: type I males are the territorial/nesting morph that vocally court females during the summer breeding season while type II males do not court females, but instead sneak spawn in competition with type I males. Catecholaminergic neurons, which synthesize and release the neurotransmitters dopamine or noradrenaline, are well-established modulators of various motivated vertebrate sociosexual behaviors, including intraspecific vocal communication. Tyrosine hydroxylase (TH) is the rate-limiting enzyme in catecholamine synthesis, and TH immunoreactivity (-ir) can be utilized to demarcate neurons in the brain that produce and release dopamine and noradrenaline. Key components of the sexually polymorphic neural circuitry essential to midshipman vocal-acoustic behavior express robust TH-ir innervation, overlap with the social behavior network, and are conserved (in part) across vertebrate taxa. The primary goal of this work was to determine if differential distribution and activation of catecholamines in the brain serve as a substrate for variation in alternative reproductive tactics and vocal behavior between type I and type II male midshipman. Firstly, an intrasexual morphometric comparison of TH-ir neuron number and fiber density revealed that type II males had a greater TH-ir innervation within and in close proximity to the hindbrain vocal pattern generator. Secondly, using the immediate early gene protein cFos as a proxy for neural activation, it was found that two forebrain dopaminergic nuclei were more active in type II males that were exposed to playbacks of conspecific hums compared to ambient noise. Thirdly, cFos-ir induction within diencephalic dopaminergic neurons and brainstem noradrenergic neurons shared positive relationships with the total amount of time type I males spent humming. Furthermore, it was found that exposure to acoustic stimuli with different valences (hums, grunts, or ambient noise) as well as divergent states of calling behavior (humming versus non-humming) evoked contrastive shifts in functional connectivity among TH-ir and social behavior network nuclei. Taken together, this work provides cogent evidence that the differential distribution and activation of catecholaminergic neurons may contribute to both processing of social-acoustic signals and divergent intrasexual behavior expressed as alternative reproductive tactics in midshipman fish

Numerical Linear Algebra applications in Archaeology: the seriation and the photometric stereo problems

The aim of this thesis is to explore the application of Numerical Linear Algebra to Archaeology. An ordering problem called the seriation problem, used for dating findings and/or artifacts deposits, is analysed in terms of graph theory. In particular, a Matlab implementation of an algorithm for spectral seriation, based on the use of the Fiedler vector of the Laplacian matrix associated with the problem, is presented. We consider bipartite graphs for describing the seriation problem, since the interrelationship between the units (i.e. archaeological sites) to be reordered, can be described in terms of these graphs. In our archaeological metaphor of seriation, the two disjoint nodes sets into which the vertices of a bipartite graph can be divided, represent the excavation sites and the artifacts found inside them. Since it is a difficult task to determine the closest bipartite network to a given one, we describe how a starting network can be approximated by a bipartite one by solving a sequence of fairly simple optimization problems. Another numerical problem related to Archaeology is the 3D reconstruction of the shape of an object from a set of digital pictures. In particular, the Photometric Stereo (PS) photographic technique is considered

A Transcription Factor Map as Revealed by a Genome-Wide Gene Expression Analysis of Whole-Blood mRNA Transcriptome in Multiple Sclerosis

Background: Several lines of evidence suggest that transcription factors are involved in the pathogenesis of Multiple Sclerosis (MS) but complete mapping of the whole network has been elusive. One of the reasons is that there are several clinical subtypes of MS and transcription factors that may be involved in one subtype may not be in others. We investigate the possibility that this network could be mapped using microarray technologies and contemporary bioinformatics methods on a dataset derived from whole blood in 99 untreated MS patients (36 Relapse Remitting MS, 43 Primary Progressive MS, and 20 Secondary Progressive MS) and 45 age-matched healthy controls. Methodology/Principal Findings: We have used two different analytical methodologies: a non-standard differential expression analysis and a differential co-expression analysis, which have converged on a significant number of regulatory motifs that are statistically overrepresented in genes that are either differentially expressed (or differentially co-expressed) in cases and controls (e.g., V$KROX_Q6, p-value ,3.31E-6; V$CREBP1_Q2, p-value ,9.93E-6, V$YY1_02, p-value ,1.65E-5). Conclusions/Significance: Our analysis uncovered a network of transcription factors that potentially dysregulate several genes in MS or one or more of its disease subtypes. The most significant transcription factor motifs were for the Early Growth Response EGR/KROX family, ATF2, YY1 (Yin and Yang 1), E2F-1/DP-1 and E2F-4/DP-2 heterodimers, SOX5, and CREB and ATF families. These transcription factors are involved in early T-lymphocyte specification and commitment as well as in oligodendrocyte dedifferentiation and development, both pathways that have significant biological plausibility in MS causation

Evolutionary Computation

This book presents several recent advances on Evolutionary Computation, specially evolution-based optimization methods and hybrid algorithms for several applications, from optimization and learning to pattern recognition and bioinformatics. This book also presents new algorithms based on several analogies and metafores, where one of them is based on philosophy, specifically on the philosophy of praxis and dialectics. In this book it is also presented interesting applications on bioinformatics, specially the use of particle swarms to discover gene expression patterns in DNA microarrays. Therefore, this book features representative work on the field of evolutionary computation and applied sciences. The intended audience is graduate, undergraduate, researchers, and anyone who wishes to become familiar with the latest research work on this field

Social context and status affect behavior, physiology and brain activity of the highly social cichlid fish, Astatotilapia burtoni

Group living confers many benefits while at the same time exposing group members to intense competition for resources and status within the group. Monitoring the social environment involves not only participating in many fast paced social interactions but also monitoring the relationships and status of other group members. In chapter 1, we use a network analysis approach to study replicate communities of the cichlid fish, Astatotilapia burtoni, which live in fast-paced social groups with a complex dominance hierarchy among males. We found several correlations between an individual’s behavior, their position in the social hierarchy and the social environment. In addition, we found that community properties are a key parameter that predicts both cortisol and testosterone levels. In chapter 2 we extend this paradigm and look at the effects of social status within a community on brain activity as measured by cytochrome oxidase histochemistry. In addition, we examined brain activity in transitioning animals as measured by cytochrome oxidase and egr-1 induction. We find that social status has a variety of subtle effects on brain activity. Finally, we tested the role of the sex steroid hormones estradiol and testosterone on social transition using an aromatase inhibitor as well as an androgen receptor antagonist. We found very few effects of blocking the nuclear androgen pathway. Blocking aromatase resulted in a hyperaggressive phenotype suggesting that estradiol plays an important role in the transition process in this species.Ecology, Evolution and Behavio

Socially driven changes in neural and behavioural plasticity in zebrafish

Tese de doutoramento, Biologia (Etologia), Universidade de Lisboa, Faculdade de Ciências, 2015Social competence, the ability of individuals to regulate the expression of their social behaviour in order to optimize their social relationships in a group, is especially benefic for individuals living in complex social environments, and implies the ability to perceive social cues and produce appropriate behavioural output responses (Social Plasticity). Numerous examples of social competence can be found in nature, where individuals extract social information from the environment, and change their behavioural response based on the collected information. At the neuronal level, two major plasticity mechanisms have been proposed to underlie social plasticity, structural reorganization and biochemical switching of the neuronal networks underlying behaviour. The neural substrate for behavioural plasticity has been identified as the social decision-making (SDM) network, such that the same neural circuitry may underlie the expression of different behaviours depending on social context. The goal of this work is to study the proximate mechanism underlying behavioural flexibility in the context of experience-dependent behavioural shifts, in an integrative framework. For this purpose we exposed male zebrafish to two types of social interactions: (1) real-opponent interactions, from which a Winner and Loser emerged; and (2) Mirror-elicited interactions, that produced individuals that did not experience a change in social status, despite expressing similar levels of aggressive behaviour to those participating in real-opponent fights. In a first set of experiments, we studied the influence of neuromodulators on social plasticity mechanisms, by characterizing the endocrine response to social challenges, as well as the social modulation of brain monoamines and nonapeptides. Next we tested the SDM network hypothesis by contrasting changes in functional localization vs. connectivity across this network. Finally we characterized changes in expression of key genes for different neuroplasticity mechanisms in response to changes in social status. Our research suggests different social plasticity mechanisms underlying Winners and Losers both at physiological and molecular levels, for Mirror-fighters, where the experience of winning or losing was decoupled for the fighting experience, few changes were detected. This, by itself suggests a pivotal role of social perception in triggering shifts between socially driven behavioural states

Neuroendocrine regulation of social Interactions in a cichlid fish

Tese apresentada para cumprimentos dos requisitos necessários à obtenção do grau de Doutor em Biologia do Comportamento apresentada no ISPA - Instituto Universitário no ano de 2019.O estudo do comportamento animal e em particular do comportamento social tem atraído investigadores desde há muito tempo. Todos os animais interagem com os outros, característica fundamental para a sua sobrevivência e reprodução. No entanto, para obter uma total compreensão do comportamento social, é necessária a integração de seus vários componentes. Com esta tese, pretendemos clarificar este tópico, estudando como o cérebro controla o comportamento através da ação conjunta de seus circuitos neurais, genes e moléculas, e também como o ambiente social de forma recíproca influencia o cérebro. Baseado neste objetivo e usando a tilápia de Moçambique (Oreochromis mossambicus) como espécie modelo, num primeiro estudo investigámos como o comportamento social é controlado por uma rede dinâmica de regiões cerebrais, a Social Decision Making Network (SDMN). Aqui, tentámos entender quais são as pistas específicas que desencadeiam mudanças no padrão de ativação dessa rede neural, usando lutas entre machos. Os nossos resultados sugerem que é a avaliação mútua do comportamento de combate que impulsiona mudanças temporárias no estado do SDMN, e não a avaliação do resultado da luta ou apenas a expressão de comportamento agressivo. Em seguida, explorámos a modulação hormonal do comportamento social, em particular pelo neuropeptídeo vasotocina. Para isso, manipulámos o sistema da vasotocina injetando vasotocina e um antagonista específico dos receptores de vasotocina V1A em machos. Para distinguir se a vasotocina afeta o comportamento isoladamente ou em combinação com andrógenios, conduzimos esta experiência em peixes castrados e peixes controlo. Curiosamente, descobrimos que a vasotocina afetou o comportamento dos machos em relação às fêmeas, mas não em relação aos machos, e que os andrógenios e a vasotocina modularam a agressividade dos machos em relação às fêmeas. Em seguida, procurámos compreender como as interações sociais afetam os sistemas neuroendócrinos. Nesse sentido, utilizámos um paradigma de intrusões territoriais para avaliar os padrões temporais dos níveis de andrógenios e tentámos relacioná-los ao fenótipo comportamental de cada indivíduo. Obtivemos padrões distintos de resposta androgénica às interações sociais devido a diferenças individuais subjacentes em sua extensão de resposta. Este estudo oferece uma importante contribuição para a área de investigação, fornecendo possíveis razões para as discrepâncias associadas à hipótese de desafio, o principal modelo em endocrinologia comportamental que descreve a relação entre andrógenios e interações sociais. Finalmente, pensa-se que os andrógenios respondem às interações sociais como forma de preparar os indivíduos para outras interações. Assim, tentámos descobrir como um aumento de andrógenios no sangue afeta o cérebro. Para esse efeito, injetámos peixes com andrógenios e estudámos as mudanças transcriptómicas que ocorrem no cérebro usando a técnica de RNAseq, permitindo uma compreensão mais detalhada do efeito dos andrógenios no cérebro. Em suma, o comportamento social é complexo e depende de vários fatores internos e externos. Os resultados desta tese fornecem um contributo significativo para pesquisas futuras.The study of animal behavior and in specific of social behavior has attracted researchers for a long time. All animals interact with others, a feature which is fundamental to their survival and reproduction. However, to get a complete understanding of social behavior, the integration of its various components is required. In this thesis, we aimed to shed light on this topic, studying how the brain controls behavior through the concerted action of its neural circuits, genes and molecules, and also how the social environment feedbacks and impacts the brain. Grounded upon this objective and using the Mozambique tilapia (Oreochromis mossambicus) as a model species, in a first study we investigated how social behavior is controlled by a dynamic network of brain regions, the Social Decision Making Network (SDMN). Here, we tried to understand what are the specific cues that trigger changes in the pattern of activation of this neural network, by using staged fights between males. Our results suggest that it is the mutual assessment of relative fighting behavior that drives acute changes in the state of the SDMN, and not the assessment of fight outcome or just the expression of aggressive behavior. Then, we explored the hormonal modulation of social behavior, in particular of the neuropeptide vasopressin. For this purpose, we manipulated the vasotocin system by injecting vasotocin and a specific antagonist of vasotocin receptors V1A in males. To distinguish if vasotocin affected behavior alone or in combination with androgens, we conducted this experiment in both castrated and control fish. Interestingly, we found that vasotocin affected the behavior of males towards females but not towards males and that both androgens and vasotocin modulated aggressiveness towards females. Next, we sought to comprehend how social interactions affect neuroendocrine systems. In that sense, we used a paradigm of territorial intrusions to assess temporal patterns of androgen levels and tried to relate them to the behavioral phenotype of each individual. We obtained distinct patterns of androgen response to social interactions due to underlying individual differences in their scope for response. This study makes an important contribution to the field by providing possible reasons for discrepancies associated with the Challenge Hypothesis, the major framework in behavioral endocrinology which describes the relationship between androgens and social interactions. Finally, it is believed that androgens respond to social interactions as a way to prepare individuals for further interactions. Thus, we tried to uncover how an androgen surge in the blood affects the brain. To accomplish this, we injected fish with androgens and studied brain transcriptomic changes with the RNAseq technique, allowing the achievement of a thorough understanding of the effect of androgens on the brain. In sum, social behavior is complex and dependent on several internal and external factors. The findings from this thesis provide significant insights for future research.Fundação para a Ciência e Tecnologi