Mean Squared Residue Based Biclustering Algorithms for the Analysis of Gene Expression Data

Computational Biology is the research are that contributes to the analysis of biological data through the development of algorithms which will address significant research problems.The data from molecular biology includes DNA,RNA ,Protein and Gene expression data.Gene Expression Data provides the expression level of genes under different conditions.Gene expression is the process of transcribing the DNA sequence of a gene into mRNA sequences which in turn are later translated into proteins.The number of copies of mRNA produced is called the expression level of a gene.Gene expression data is organized in the form of a matrix. Rows in the matrix represent genes and columns in the matrix represent experimental conditions.Experimental conditions can be different tissue types or time points.Entries in the gene expression matrix are real values.Through the analysis of gene expression data it is possible to determine the behavioral patterns of genes such as similarity of their behavior,nature of their interaction,their respective contribution to the same pathways and so on. Similar expression patterns are exhibited by the genes participating in the same biological process.These patterns have immense relevance and application in bioinformatics and clinical research.Theses patterns are used in the medical domain for aid in more accurate diagnosis,prognosis,treatment planning.drug discovery and protein network analysis.To identify various patterns from gene expression data,data mining techniques are essential.Clustering is an important data mining technique for the analysis of gene expression data.To overcome the problems associated with clustering,biclustering is introduced.Biclustering refers to simultaneous clustering of both rows and columns of a data matrix. Clustering is a global whereas biclustering is a local model.Discovering local expression patterns is essential for identfying many genetic pathways that are not apparent otherwise.It is therefore necessary to move beyond the clustering paradigm towards developing approaches which are capable of discovering local patterns in gene expression data.A biclusters is a submatrix of the gene expression data matrix.The rows and columns in the submatrix need not be contiguous as in the gene expression data matrix.Biclusters are not disjoint.Computation of biclusters is costly because one will have to consider all the combinations of columans and rows in order to find out all the biclusters.The search space for the biclustering problem is 2 m+n where m and n are the number of genes and conditions respectively.Usually m+n is more than 3000.The biclustering problem is NP-hard.Biclustering is a powerful analytical tool for the biologist.The research reported in this thesis addresses the problem of biclustering.Ten algorithms are developed for the identification of coherent biclusters from gene expression data.All these algorithms are making use of a measure called mean squared residue to search for biclusters.The objective here is to identify the biclusters of maximum size with the mean squared residue lower than a given threshold. All these algorithms begin the search from tightly coregulated submatrices called the seeds.These seeds are generated by K-Means clustering algorithm.The algorithms developed can be classified as constraint based,greedy and metaheuristic.Constarint based algorithms uses one or more of the various constaints namely the MSR threshold and the MSR difference threshold.The greedy approach makes a locally optimal choice at each stage with the objective of finding the global optimum.In metaheuristic approaches particle Swarm Optimization(PSO) and variants of Greedy Randomized Adaptive Search Procedure(GRASP) are used for the identification of biclusters.These algorithms are implemented on the Yeast and Lymphoma datasets.Biologically relevant and statistically significant biclusters are identified by all these algorithms which are validated by Gene Ontology database.All these algorithms are compared with some other biclustering algorithms.Algorithms developed in this work overcome some of the problems associated with the already existing algorithms.With the help of some of the algorithms which are developed in this work biclusters with very high row variance,which is higher than the row variance of any other algorithm using mean squared residue, are identified from both Yeast and Lymphoma data sets.Such biclusters which make significant change in the expression level are highly relevant biologically.

CAPM und Behavioral Finance - Versuch einer Synthese

Seit Etablierung der ersten Börsen als Marktplatz für fungible Güter sind Marktteilnehmer und die Wissenschaft bemüht, Erklärungen für das Zustandekommen von Marktpreisen zu finden. Im Laufe der Zeit wurden diverse Modelle entwickelt. Allen voran ist das neoklassische Capital Asset Pricing Modell (CAPM) zu nennen. Die Neoklassik sieht den Akteur an den Finanzmärkten als emotionslosen und streng rationalen Entscheider, dem sog. homo oeconomicus. Psychologische Einflussfaktoren bei der Preisbildung bleiben unbeachtet. Mit der Behavioral Finance hat sich ein neuer Zweig zur Erklärung von Börsenkursen und deren Bewegungen entwickelt. Die Behavioral Finance sprengt die enge Sichtweise der Neoklassik und geht davon aus, dass psychologische Effekte die Entscheidung der Finanzakteure beeinflussen und dabei zu teilweise irrational und emotional geprägten Kursänderungen führen. Eines der Hauptprobleme der Behavioral Finance liegt allerdings in der fehlenden formellen Ermittelbarkeit und Testbarkeit der einzelnen psychologischen Effekte. Anders als beim CAPM, wo die einzelnen Parameter klar mathematisch bestimmbar sind, besteht die Behavioral Finance im Wesentlichen aus psychologischen Definitionen von kursbeeinflussenden Effekten. Die genaue Wirkrichtung und Intensität der Effekte kann, mangels geeigneter Modelle, nicht ermittelt werden. Ziel der Arbeit ist es, eine Abwandlung des CAPM zu ermitteln, die es ermöglicht, neoklassische Annahmen durch die Erkenntnisse des Behavioral Finance zu ergänzen. Mittels der technischen Analyse von Marktpreisen wird versucht die Effekte der Behavioral Finance formell darstellbar und berechenbar zu machen. Von Praktikern wird die technische Analyse dazu verwendet, aus Kursverläufen die Stimmungen und Intentionen der Marktteilnehmer abzuleiten. Eine wissenschaftliche Fundierung ist bislang unterblieben. Ausgehend von den Erkenntnissen der Behavioral Finance und der technischen Analyse wird das klassische CAPM um psychologische Faktoren ergänzt, indem ein Multi-Beta-CAPM (Behavioral-Finance-CAPM) definiert wird, in das psychologisch fundierte Parameter der technischen Analyse einfließen. In Anlehnung an den CAPM-Test von FAMA und FRENCH (1992) werden das klassische CAPM und das Behavioral-Finance-CAPM getestet und der psychologische Erklärungsgehalt der technischen Analyse untersucht. Im Untersuchungszeitraum kann dem Behavioral-Finance-CAPM ein deutlich höherer Erklärungsgehalt gegenüber dem klassischen CAPM zugesprochen werden.

Physiological analysis of central and peripheral insect circadian pacemaker neurons

Alle bisher untersuchten Lebewesen besitzen (circadiane) innere Uhren, die eine endogene Perioden-länge von ungefähr 24 Stunden generieren. Eine innere Uhr kann über Zeitgeber mit der Umwelt synchronisiert werden und ermöglicht dem Organismus, rhythmische Umweltveränderungen vorweg zu nehmen. Neben einem zentralen Schrittmacher, der Physiologie und Verhalten des Organismus steuert, gibt es in unterschiedlichen Organen auch periphere Uhren, die die zeitlichen Abläufe in der spezifischen Funktion dieser Organe steuern. In dieser Arbeit sollten zentrale und periphere Schrittmacherneurone von Insekten physiologisch untersucht und verglichen werden. Die Neurone der akzessorischen Medulla (AME) von Rhyparobia maderae dienten als Modellsystem für zentrale Schrittmacher, während olfaktorische Rezeptorneurone (ORNs) von Manduca sexta als Modellsystem für periphere Schrittmacher dienten. Die zentralen Schrittmacherneurone wurden in extrazellulären Ableitungen an der isolierten AME (Netzwerkebene) und in Patch-Clamp Experimenten an primären AME Zellkulturen (Einzelzellebene) untersucht. Auf Netzwerkebene zeigten sich zwei charakteristische Aktivitätsmuster: regelmäßige Aktivität und Wechsel zwischen hoher und niedriger Aktivität (Oszillationen). Es wurde gezeigt, dass Glutamat ein Neurotransmitter der weitverbreiteten inhibitorischen Synapsen der AME ist, und dass in geringem Maße auch exzitatorische Synapsen vorkommen. Das Neuropeptid pigment-dispersing factor (PDF), das von nur wenigen AME Neuronen exprimiert wird und ein wichtiger Kopplungsfaktor im circadianen System ist, führte zu Hemmungen, Aktivierungen oder Oszillationen. Die Effekte waren transient oder langanhaltend und wurden wahrscheinlich durch den sekundären Botenstoff cAMP vermittelt. Ein Zielmolekül von cAMP war vermutlich exchange protein directly activated by cAMP (EPAC). Auf Einzelzellebene wurde gezeigt, dass die meisten AME Neurone depolarisiert waren und deshalb nicht feuerten. Die Analyse von Strom-Spannungs-Kennlinien und pharmakologische Experimente ergaben, dass unterschiedliche Ionenkanäle vorhanden waren (Ca2+, Cl-, K+, Na+ Kanäle sowie nicht-spezifische Kationenkanäle). Starke, bei hohen Spannungen aktivierende Ca2+ Ströme (ICa) könnten eine wichtige Rolle bei Ca2+-abhängiger Neurotransmitter-Ausschüttung, Oszillationen, und Aktionspotentialen spielen. PDF hemmte unterschiedliche Ströme (ICa, IK und INa) und aktivierte nicht-spezifische Kationenströme (Ih). Es wurde angenommen, dass simultane PDF-abhängige Hyper- und Depolarisationen rhythmische Membranpotential-Oszillationen verursachen. Dieser Mechanismus könnte eine Rolle bei PDF-abhängigen Synchronisationen spielen. Die Analyse peripherer Schrittmacherneurone konzentrierte sich auf die Charakterisierung des olfaktorischen Corezeptors von M. sexta (MsexORCO). In anderen Insekten ist ORCO für die Membran-Insertion von olfaktorischen Rezeptoren (ORs) erforderlich. ORCO bildet Komplexe mit den ORs, die in heterologen Expressionssystemen als Ionenkanäle fungieren und Duft-Antworten vermitteln. Es wurde die Hypothese aufgestellt, dass MsexORCO in pheromonsensitiven ORNs in vivo nicht als Teil eines ionotropen Rezeptors sondern als Schrittmacherkanal fungiert, der unterschwellige Membranpotential-Oszillationen generiert. MsexORCO wurde mit vermeintlichen Pheromonrezeptoren in human embryonic kidney (HEK 293) Zellen coexprimiert. Immuncytochemie und Ca2+ Imaging Experimente zeigten sehr schwache Expressionsraten. Trotzdem war es möglich zu zeigen, dass MsexORCO wahrscheinlich ein spontan-aktiver, Ca2+-permeabler Ionenkanal ist, der durch den ORCO-Agonisten VUAA1 und cyclische Nucleotide aktiviert wird. Außerdem wiesen die Experimente darauf hin, dass MsexOR-1 offensichtlich der Bombykal-Rezeptor ist. Eine weitere Charakterisierung von MsexORCO in primären M. sexta ORN Zellkulturen konnte nicht vollendet werden, weil die ORNs nicht signifikant auf ORCO-Agonisten oder -Antagonisten reagierten.

A behavioral comparison between motorcyclists and a matched group of non-motorcycling car drivers: factors influencing accident risk

Motorcyclists and a matched group of non-motorcycling car drivers were assessed on behavioral measures known to relate to accident involvement. Using a range of laboratory measures, we found that motorcyclists chose faster speeds than the car drivers, overtook more, and pulled into smaller gaps in traffic, though they did not travel any closer to the vehicle in front. The speed and following distance findings were replicated by two further studies involving unobtrusive roadside observation. We suggest that the increased risk-taking behavior of motorcyclists was only likely to account for a small proportion of the difference in accident risk between motorcyclists and car drivers. A second group of motorcyclists was asked to complete the simulator tests as if driving a car. They did not differ from the non-motorcycling car drivers on the risk-taking measures but were better at hazard perception. There were also no differences for sensation seeking, mild social deviance, and attitudes to riding/driving, indicating that the risk-taking tendencies of motorcyclists did not transfer beyond motorcycling, while their hazard perception skill did. (C) 2002 Elsevier Science Ltd. All rights reserved.

Experimental analysis of the Reynolds flocking model

The classic Reynolds flocking model is formally analysed, with results presented and discussed. Flocking behaviour was investigated through the development of two measurements of flocking, flock area and polarisation, with a view to applying the findings to robotic applications. Experiments varying the flocking simulation parameters individually and simultaneously provide new insight into the control of flock behaviour.

Separation of performance-approach and performance-avoidance achievement goals: A broader analysis

In the literature on achievement goals, performance-approach goals (striving to do better than others) and performance-avoidance goals (striving to avoid doing worse than others) tend to exhibit a moderate to high correlation, raising questions about whether the 2 goals represent distinct constructs. In the current article, we sought to examine the separability of these 2 goals using a broad factor-analytic approach that attended to issues that have been overlooked or underexamined in prior research. Five studies provided strong evidence for the separation of these 2 goal constructs: Separation was observed not only with exploratory factor analysis across different age groups and countries (Studies 1a and 1b) but also with change analysis (Study 2), ipsative factor analysis (Study 3), within-person analysis (Study 4), and behavioral genetics analysis (Study 5). We conclude by discussing the implications of the present research for the achievement goal literature, as well as the psychological literature in general.

Hidden Markov analysis describes dive patterns in semiaquatic animals

Existing methods of dive analysis, developed for fully aquatic animals, tend to focus on frequency of behaviors rather than transitions between them. They, therefore, do not account for the variability of behavior of semiaquatic animals, and the switching between terrestrial and aquatic environments. This is the first study to use hidden Markov models (HMM) to divide dives of a semiaquatic animal into clusters and thus identify the environmental predictors of transition between behavioral modes. We used 18 existing data sets of the dives of 14 American mink (Neovison vison) fitted with time-depth recorders in lowland England. Using HMM, we identified 3 behavioral states (1, temporal cluster of dives; 2, more loosely aggregated diving within aquatic activity; and 3, terminal dive of a cluster or a single, isolated dive). Based on the higher than expected proportion of dives in State 1, we conclude that mink tend to dive in clusters. We found no relationship between temperature and the proportion of dives in each state or between temperature and the rate of transition between states, meaning that in our study area, mink are apparently not adopting different diving strategies at different temperatures. Transition analysis between states has shown that there is no correlation between ambient temperature and the likelihood of mink switching from one state to another, that is, changing foraging modes. The variables provided good discrimination and grouped into consistent states well, indicating promise for further application of HMM and other state transition analyses in studies of semiaquatic animals.

Methods for the modulation and analysis of NF-κB-dependent adult neurogenesis

The hippocampus plays a pivotal role in the formation and consolidation of episodic memories, and in spatial orientation. Historically, the adult hippocampus has been viewed as a very static anatomical region of the mammalian brain. However, recent findings have demonstrated that the dentate gyrus of the hippocampus is an area of tremendous plasticity in adults, involving not only modifications of existing neuronal circuits, but also adult neurogenesis. This plasticity is regulated by complex transcriptional networks, in which the transcription factor NF-κB plays a prominent role. To study and manipulate adult neurogenesis, a transgenic mouse model for forebrain-specific neuronal inhibition of NF-κB activity can be used. In this study, methods are described for the analysis of NF-κB-dependent neurogenesis, including its structural aspects, neuronal apoptosis and progenitor proliferation, and cognitive significance, which was specifically assessed via a dentate gyrus (DG)-dependent behavioral test, the spatial pattern separation-Barnes maze (SPS-BM). The SPS-BM protocol could be simply adapted for use with other transgenic animal models designed to assess the influence of particular genes on adult hippocampal neurogenesis. Furthermore, SPS-BM could be used in other experimental settings aimed at investigating and manipulating DG-dependent learning, for example, using pharmacological agents.

Analysis and manipulation of the structure of odor plumes from a piezo-electric release system and measurements of upwind flight of male Almond Moths, Cadra cautella, to pheromone plumes

We investigated the plume structure of a piezo-electric sprayer system, set up to release ethanol in a wind tunnel, using a fast response mini-photoionizaton detector. We recorded the plume structure of four different piezo-sprayer configurations: the sprayer alone; with a 1.6-mm steel mesh shield; with a 3.2-mm steel mesh shield; and with a 5 cm circular upwind baffle. We measured a 12 × 12-mm core at the center of the plume, and both a horizontal and vertical cross-section of the plume, all at 100-, 200-, and 400-mm downwind of the odor source. Significant differences in plume structure were found among all configurations in terms of conditional relative mean concentration, intermittency, ratio of peak concentration to conditional mean concentration, and cross-sectional area of the plume. We then measured the flight responses of the almond moth, Cadra cautella, to odor plumes generated with the sprayer alone, and with the upwind baffle piezo-sprayer configuration, releasing a 13:1 ratio of (9Z,12E)-tetradecadienyl acetate and (Z)-9-tetradecenyl acetate diluted in ethanol at release rates of 1, 10, 100, and 1,000 pg/min. For each configuration, differences in pheromone release rate resulted in significant differences in the proportions of moths performing oriented flight and landing behaviors. Additionally, there were apparent differences in the moths’ behaviors between the two sprayer configurations, although this requires confirmation with further experiments. This study provides evidence that both pheromone concentration and plume structure affect moth orientation behavior and demonstrates that care is needed when setting up experiments that use a piezo-electric release system to ensure the optimal conditions for behavioral observations.

Utilizing insect behavior in chemical detection by a behavioral biosensor

Traditionally, biosensors have been defined as consisting of two parts; a biological part, which is used to detect chemical or physical changes in the environment, and a corresponding electronic component, which tranduces the signal into an electronically readable format. Biosensors are used for detection of volatile compounds often at a level of sensitivity unattainable by traditional analytical techniques. Classical biosensors and traditional analytical techniques do not allow an ecological context to be imparted to the volatile compound/s under investigation. Therefore, we propose the use of behavioral biosensors, in which a whole organism is utilized for the analysis of chemical stimuli. In this case, the organism detects a chemical or physical change and demonstrates this detection through modifications of its behavior; it is the organism's behavior itself that defines the biosensor. In this review, we evaluate the use and future prospects of behavioral biosensors, with a particular focus on parasitic wasps.

Investigating the Effects of Mifepristone (RU486) in the Behavioral, Hormonal and Central Responses to Acute Stress

Depression is associated with glucocorticoid hypersecretion, due to dysfunction of the hypothalamo-pituitary-adrenocorticol axis (HPA-axis). Because excess glucocorticoids are associated with depressive-like features in humans, glucocorticoid receptor antagonists are currently being tested for antidepressant efficacy in clinical trials. In the current study the hypothesis that mifepristone (RU486), a glucocorticoid receptor antagonist, would decrease the neuroendocrine and central HPA-axis responses to an acute stressor and attentuate depressive like behavior in an animal model of behavioral helplessness (forced swim test) was tested. Adult male rats were treated with 10 mglkg RU486 (subcutaneous) for five days and then exposed to a IO-minute forced swim test (FST), conducted in Plexiglas cylinders. FST sessions were videotaped for later analysis of behavioral immobility. Plasma ACTH and corticosterone CORT were measured at 15min and 90min after FST cessation. Animals were perfused and brains were collected for immunocytochemical assessment of c-Fos expression in the medial prefrontal cortex (mPFC), a brain region implicated in both depression and central control of the HPA axis. RU486 significantly decreased peak ACTH and CORT concentrations following FST exposure. In addition, glucocorticoid negative feedback was at1enuated in RU486-treated animals exposed to the FST. Exposure to FST alone induced c-FOS expression in the mPFC, as measured by the number of c-Fos positive neurons. Treatment with RU486 significantly increased the number of rnPFC c-Fos positive cell following FST exposure. The behavioral data obtained from FST paradigm, demonstrated that RU486 decreased immobility in the FST illustrating the potential efficacy of this drug as an antidepressant. Collectively these data suggest that RU486 dampens HPA-axis responses to stress, possibly by enhancing the excitability of stress-inhibitory neurons in the mPFC. This is particularly exciting, given the fact that this neural region is associated with decreased neural activity during depression in humans.

Food waste in lower-middle income households: a qualitative analysis of antecedents and a typology of food wasters

Esta dissertação doutoral, com base em dados empíricos coletados com 50 mães distribuídas no Brasil (n = 30) e nos EUA (n = 20), tem como objetivo fornecer uma melhor compreensão do desperdício de alimento no contexto da baixa renda. A tese é composta por três artigos, que combinados, cumprem os objetivos de identificar os antecedentes do desperdício de alimento e delinear uma tipologia dos desperdiçadores de alimento. Adicionalmente, contextualiza o desperdício global e um capítulo propõe uma agenda futura para estudos sobre desperdício de alimento no âmbito do consumidor. O desperdício de alimento nas famílias, enquanto tema de pesquisa, oferece a oportunidade para o trabalho acadêmico em marketing cumprir os critérios de relevância social, gerencial e para políticas públicas. No primeiro estudo, descrevem-se os fatores do chamado "paradoxo do desperdício de alimento", a identificação e análise do desperdício de alimento em famílias com restrições orçamentárias, enquanto apresentam-se o itinerário do consumo de alimentos e os antecedentes do desperdício. Este primeiro artigo, elaborado com dados coletados em famílias brasileiras, ilustra também o papel das normas culturais, tais como o preparo abundante de alimento para mostrar hospitalidade ou como forma de não ser percebido como pobre, no aumento do desperdício. No segundo artigo, uma grounded-theory (teoria fundamentada nos dados) destaca o papel do afeto e da abundância no desperdício de alimento familiar. Para enriquecer as contribuições teóricas, este segundo estudo apresenta um framework com seis dimensões do desperdício de alimento (1. Afeto; 2. Abundância; 3. Multiplicidade de escolhas; 4. Conveniência; 5. Procrastinação; 6. Rotina sem planejamento). Baseado em dados empíricos coletados em famílias americanas, este estudo proporciona novas explicações, a exemplo de como o estoque abundante de comfort foods - uma forma de impulsionar tanto emoções positivas para si quanto mostrar afeto para crianças – pode gerar mais desperdício de alimentos. Em síntese, o segundo artigo identifica uma consequência negativa do afeto e da abundância de alimentos no contexto familiar, e apresenta um framework teoricamente relevante. Finalmente, o terceiro artigo, a partir do conjunto de dados dos estudos anteriores e de nova coleta com dez famílias, propõe uma tipologia comportamental do desperdício de alimento, uma contribuição original aos estudos de comportamento do consumidor. A identificação de cinco tipos de desperdiçadores de alimentos - (1) Mães carinhosas; (2) Cozinheiras abundantes; (3) Desperdiçadoras de sobras; (4) Procrastinadoras; (5) Mães versáteis - contribui para a teoria, enquanto implicações potenciais para educadores nutricionais e agentes públicos são exploradas a partir dos resultados. Como uma forma de explicar as características de cada um dos cinco tipos identificados, compara-se aspectos das amostras brasileira e norte-americana, que apresentam similaridades no comportamento de desperdício de alimento. Os níveis de desperdício percebidos por país também são comparados. Em suma, os achados dos três artigos podem contribuir para maximizar os resultados de campanhas de conscientização voltadas à mitigação do desperdício de alimento, e apresentam ideias para varejistas interessados em iniciativas de sustentabilidade. Mais abrangentemente, os resultados apresentados também podem ser aplicados para incrementar programas de combate à fome e projetos de educação nutricional realizados pelo setor público ou ONGs.

Speculative bubbles and contagion: analysis of volatility's clusters during the DotCom bubble based on the dynamic conditional correlation model

Reviewing the de nition and measurement of speculative bubbles in context of contagion, this paper analyses the DotCom bubble in American and European equity markets using the dynamic conditional correlation (DCC) model proposed by (Engle and Sheppard 2001) as on one hand as an econometrics explanation and on the other hand the behavioral nance as an psychological explanation. Contagion is de ned in this context as the statistical break in the computed DCCs as measured by the shifts in their means and medians. Even it is astonishing, that the contagion is lower during price bubbles, the main nding indicates the presence of contagion in the di¤erent indices among those two continents and proves the presence of structural changes during nancial crisis

Correlations among behavior, performance and environment in broiler breeders using multivariate analysis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)