Analyzing the dependence structure of microarray data: a copula–based approach

The main aim of this Ph.D. dissertation is the study of clustering dependent data by means of copula functions with particular emphasis on microarray data. Copula functions are a popular multivariate modeling tool in each field where the multivariate dependence is of great interest and their use in clustering has not been still investigated. The first part of this work contains the review of the literature of clustering methods, copula functions and microarray experiments. The attention focuses on the K–means (Hartigan, 1975; Hartigan and Wong, 1979), the hierarchical (Everitt, 1974) and the model–based (Fraley and Raftery, 1998, 1999, 2000, 2007) clustering techniques because their performance is compared. Then, the probabilistic interpretation of the Sklar’s theorem (Sklar’s, 1959), the estimation methods for copulas like the Inference for Margins (Joe and Xu, 1996) and the Archimedean and Elliptical copula families are presented. In the end, applications of clustering methods and copulas to the genetic and microarray experiments are highlighted. The second part contains the original contribution proposed. A simulation study is performed in order to evaluate the performance of the K–means and the hierarchical bottom–up clustering methods in identifying clusters according to the dependence structure of the data generating process. Different simulations are performed by varying different conditions (e.g., the kind of margins (distinct, overlapping and nested) and the value of the dependence parameter ) and the results are evaluated by means of different measures of performance. In light of the simulation results and of the limits of the two investigated clustering methods, a new clustering algorithm based on copula functions (‘CoClust’ in brief) is proposed. The basic idea, the iterative procedure of the CoClust and the description of the written R functions with their output are given. The CoClust algorithm is tested on simulated data (by varying the number of clusters, the copula models, the dependence parameter value and the degree of overlap of margins) and is compared with the performance of model–based clustering by using different measures of performance, like the percentage of well–identified number of clusters and the not rejection percentage of H0 on . It is shown that the CoClust algorithm allows to overcome all observed limits of the other investigated clustering techniques and is able to identify clusters according to the dependence structure of the data independently of the degree of overlap of margins and the strength of the dependence. The CoClust uses a criterion based on the maximized log–likelihood function of the copula and can virtually account for any possible dependence relationship between observations. Many peculiar characteristics are shown for the CoClust, e.g. its capability of identifying the true number of clusters and the fact that it does not require a starting classification. Finally, the CoClust algorithm is applied to the real microarray data of Hedenfalk et al. (2001) both to the gene expressions observed in three different cancer samples and to the columns (tumor samples) of the whole data matrix.

Light energy management in peach: utilization, photoprotection , photodamage and recovery. Maximizing light absorption in orchard is not always the best solution

The relation between the intercepted light and orchard productivity was considered linear, although this dependence seems to be more subordinate to planting system rather than light intensity. At whole plant level not always the increase of irradiance determines productivity improvement. One of the reasons can be the plant intrinsic un-efficiency in using energy. Generally in full light only the 5 – 10% of the total incoming energy is allocated to net photosynthesis. Therefore preserving or improving this efficiency becomes pivotal for scientist and fruit growers. Even tough a conspicuous energy amount is reflected or transmitted, plants can not avoid to absorb photons in excess. The chlorophyll over-excitation promotes the reactive species production increasing the photoinhibition risks. The dangerous consequences of photoinhibition forced plants to evolve a complex and multilevel machine able to dissipate the energy excess quenching heat (Non Photochemical Quenching), moving electrons (water-water cycle , cyclic transport around PSI, glutathione-ascorbate cycle and photorespiration) and scavenging the generated reactive species. The price plants must pay for this equipment is the use of CO2 and reducing power with a consequent decrease of the photosynthetic efficiency, both because some photons are not used for carboxylation and an effective CO2 and reducing power loss occurs. Net photosynthesis increases with light until the saturation point, additional PPFD doesn’t improve carboxylation but it rises the efficiency of the alternative pathways in energy dissipation but also ROS production and photoinhibition risks. The wide photo-protective apparatus, although is not able to cope with the excessive incoming energy, therefore photodamage occurs. Each event increasing the photon pressure and/or decreasing the efficiency of the described photo-protective mechanisms (i.e. thermal stress, water and nutritional deficiency) can emphasize the photoinhibition. Likely in nature a small amount of not damaged photosystems is found because of the effective, efficient and energy consuming recovery system. Since the damaged PSII is quickly repaired with energy expense, it would be interesting to investigate how much PSII recovery costs to plant productivity. This PhD. dissertation purposes to improve the knowledge about the several strategies accomplished for managing the incoming energy and the light excess implication on photo-damage in peach. The thesis is organized in three scientific units. In the first section a new rapid, non-intrusive, whole tissue and universal technique for functional PSII determination was implemented and validated on different kinds of plants as C3 and C4 species, woody and herbaceous plants, wild type and Chlorophyll b-less mutant and monocot and dicot plants. In the second unit, using a “singular” experimental orchard named “Asymmetric orchard”, the relation between light environment and photosynthetic performance, water use and photoinhibition was investigated in peach at whole plant level, furthermore the effect of photon pressure variation on energy management was considered on single leaf. In the third section the quenching analysis method suggested by Kornyeyev and Hendrickson (2007) was validate on peach. Afterwards it was applied in the field where the influence of moderate light and water reduction on peach photosynthetic performances, water requirements, energy management and photoinhibition was studied. Using solar energy as fuel for life plant is intrinsically suicidal since the high constant photodamage risk. This dissertation would try to highlight the complex relation existing between plant, in particular peach, and light analysing the principal strategies plants developed to manage the incoming light for deriving the maximal benefits as possible minimizing the risks. In the first instance the new method proposed for functional PSII determination based on P700 redox kinetics seems to be a valid, non intrusive, universal and field-applicable technique, even because it is able to measure in deep the whole leaf tissue rather than the first leaf layers as fluorescence. Fluorescence Fv/Fm parameter gives a good estimate of functional PSII but only when data obtained by ad-axial and ab-axial leaf surface are averaged. In addition to this method the energy quenching analysis proposed by Kornyeyev and Hendrickson (2007), combined with the photosynthesis model proposed by von Caemmerer (2000) is a forceful tool to analyse and study, even in the field, the relation between plant and environmental factors such as water, temperature but first of all light. “Asymmetric” training system is a good way to study light energy, photosynthetic performance and water use relations in the field. At whole plant level net carboxylation increases with PPFD reaching a saturating point. Light excess rather than improve photosynthesis may emphasize water and thermal stress leading to stomatal limitation. Furthermore too much light does not promote net carboxylation improvement but PSII damage, in fact in the most light exposed plants about 50-60% of the total PSII is inactivated. At single leaf level, net carboxylation increases till saturation point (1000 – 1200 μmolm-2s-1) and light excess is dissipated by non photochemical quenching and non net carboxylative transports. The latter follows a quite similar pattern of Pn/PPFD curve reaching the saturation point at almost the same photon flux density. At middle-low irradiance NPQ seems to be lumen pH limited because the incoming photon pressure is not enough to generate the optimum lumen pH for violaxanthin de-epoxidase (VDE) full activation. Peach leaves try to cope with the light excess increasing the non net carboxylative transports. While PPFD rises the xanthophyll cycle is more and more activated and the rate of non net carboxylative transports is reduced. Some of these alternative transports, such as the water-water cycle, the cyclic transport around the PSI and the glutathione-ascorbate cycle are able to generate additional H+ in lumen in order to support the VDE activation when light can be limiting. Moreover the alternative transports seems to be involved as an important dissipative way when high temperature and sub-optimal conductance emphasize the photoinhibition risks. In peach, a moderate water and light reduction does not determine net carboxylation decrease but, diminishing the incoming light and the environmental evapo-transpiration request, stomatal conductance decreases, improving water use efficiency. Therefore lowering light intensity till not limiting levels, water could be saved not compromising net photosynthesis. The quenching analysis is able to partition absorbed energy in the several utilization, photoprotection and photo-oxidation pathways. When recovery is permitted only few PSII remained un-repaired, although more net PSII damage is recorded in plants placed in full light. Even in this experiment, in over saturating light the main dissipation pathway is the non photochemical quenching; at middle-low irradiance it seems to be pH limited and other transports, such as photorespiration and alternative transports, are used to support photoprotection and to contribute for creating the optimal trans-thylakoidal ΔpH for violaxanthin de-epoxidase. These alternative pathways become the main quenching mechanisms at very low light environment. Another aspect pointed out by this study is the role of NPQ as dissipative pathway when conductance becomes severely limiting. The evidence that in nature a small amount of damaged PSII is seen indicates the presence of an effective and efficient recovery mechanism that masks the real photodamage occurring during the day. At single leaf level, when repair is not allowed leaves in full light are two fold more photoinhibited than the shaded ones. Therefore light in excess of the photosynthetic optima does not promote net carboxylation but increases water loss and PSII damage. The more is photoinhibition the more must be the photosystems to be repaired and consequently the energy and dry matter to allocate in this essential activity. Since above the saturation point net photosynthesis is constant while photoinhibition increases it would be interesting to investigate how photodamage costs in terms of tree productivity. An other aspect of pivotal importance to be further widened is the combined influence of light and other environmental parameters, like water status, temperature and nutrition on peach light, water and phtosyntate management.

A partial dependence factorial analysis to deal with selection bias in observational studis

This thesis presents a creative and practical approach to dealing with the problem of selection bias. Selection bias may be the most important vexing problem in program evaluation or in any line of research that attempts to assert causality. Some of the greatest minds in economics and statistics have scrutinized the problem of selection bias, with the resulting approaches – Rubin’s Potential Outcome Approach(Rosenbaum and Rubin,1983; Rubin, 1991,2001,2004) or Heckman’s Selection model (Heckman, 1979) – being widely accepted and used as the best fixes. These solutions to the bias that arises in particular from self selection are imperfect, and many researchers, when feasible, reserve their strongest causal inference for data from experimental rather than observational studies. The innovative aspect of this thesis is to propose a data transformation that allows measuring and testing in an automatic and multivariate way the presence of selection bias. The approach involves the construction of a multi-dimensional conditional space of the X matrix in which the bias associated with the treatment assignment has been eliminated. Specifically, we propose the use of a partial dependence analysis of the X-space as a tool for investigating the dependence relationship between a set of observable pre-treatment categorical covariates X and a treatment indicator variable T, in order to obtain a measure of bias according to their dependence structure. The measure of selection bias is then expressed in terms of inertia due to the dependence between X and T that has been eliminated. Given the measure of selection bias, we propose a multivariate test of imbalance in order to check if the detected bias is significant, by using the asymptotical distribution of inertia due to T (Estadella et al. 2005) , and by preserving the multivariate nature of data. Further, we propose the use of a clustering procedure as a tool to find groups of comparable units on which estimate local causal effects, and the use of the multivariate test of imbalance as a stopping rule in choosing the best cluster solution set. The method is non parametric, it does not call for modeling the data, based on some underlying theory or assumption about the selection process, but instead it calls for using the existing variability within the data and letting the data to speak. The idea of proposing this multivariate approach to measure selection bias and test balance comes from the consideration that in applied research all aspects of multivariate balance, not represented in the univariate variable- by-variable summaries, are ignored. The first part contains an introduction to evaluation methods as part of public and private decision process and a review of the literature of evaluation methods. The attention is focused on Rubin Potential Outcome Approach, matching methods, and briefly on Heckman’s Selection Model. The second part focuses on some resulting limitations of conventional methods, with particular attention to the problem of how testing in the correct way balancing. The third part contains the original contribution proposed , a simulation study that allows to check the performance of the method for a given dependence setting and an application to a real data set. Finally, we discuss, conclude and explain our future perspectives.

Isospin dependence of the Ar+Ni fusion-evaporation cross section

The fundamental goal of this thesis is the determination of the isospin dependence of the Ar+Ni fusion-evaporation cross section. Three Ar isotope beams, with energies of about 13AMeV, have been accelerated and impinged onto isotopically enriched Ni targets, in order to produce Pd nuclei, with mass number varying from 92 to 104. The measurements have been performed by the high performance 4pi detector INDRA, coupled with the magnetic spectrometer VAMOS. Even if the results are very preliminary, the obtained fusion-evaporation cross sections behaviour gives a hint at the possible isospin dependence of the fusion-evaporation cross sections.

Experimental analysis of coaxial jets: instability, flow and mixing characterization

The velocity and mixing field of two turbulent jets configurations have been experimentally characterized by means of cold- and hot-wire anemometry in order to investigate the effects of the initial conditions on the flow development. In particular, experiments have been focused on the effect of the separation wall between the two streams on the flow field. The results of the experiments have pointed out that the wake behind a thick wall separating wall has a strong influence on the flow field evolution. For instance, for nearly unitary velocity ratios, a clear vortex shedding from the wall is observable. This phenomenon enhances the mixing between the inner and outer shear layer. This enhancement in the fluctuating activity is a consequence of a local absolute instability of the flow which, for a small range of velocity ratios, behaves as an hydrodynamic oscillator with no sensibility to external perturbations. It has been suggested indeed that this absolute instability can be used as a passive method to control the flow evolution. Finally, acoustic excitation has been applied to the near field in order to verify whether or not the observed vortex shedding behind the separating wall is due to a global oscillating mode as predicted by the theory. A new scaling relationship has been also proposed to determine the preferred frequency for nearly unitary velocity ratios. The proposed law takes into account both the Reynolds number and the velocity ratio dependence of this frequency and, therefore, improves all the previously proposed relationships.

Electrothermal characterization and nonlinear modelling of GaN transistors for telecommunication circuit design

This thesis starts showing the main characteristics and application fields of the AlGaN/GaN HEMT technology, focusing on reliability aspects essentially due to the presence of low frequency dispersive phenomena which limit in several ways the microwave performance of this kind of devices. Based on an equivalent voltage approach, a new low frequency device model is presented where the dynamic nonlinearity of the trapping effect is taken into account for the first time allowing considerable improvements in the prediction of very important quantities for the design of power amplifier such as power added efficiency, dissipated power and internal device temperature. An innovative and low-cost measurement setup for the characterization of the device under low-frequency large-amplitude sinusoidal excitation is also presented. This setup allows the identification of the new low frequency model through suitable procedures explained in detail. In this thesis a new non-invasive empirical method for compact electrothermal modeling and thermal resistance extraction is also described. The new contribution of the proposed approach concerns the non linear dependence of the channel temperature on the dissipated power. This is very important for GaN devices since they are capable of operating at relatively high temperatures with high power densities and the dependence of the thermal resistance on the temperature is quite relevant. Finally a novel method for the device thermal simulation is investigated: based on the analytical solution of the tree-dimensional heat equation, a Visual Basic program has been developed to estimate, in real time, the temperature distribution on the hottest surface of planar multilayer structures. The developed solver is particularly useful for peak temperature estimation at the design stage when critical decisions about circuit design and packaging have to be made. It facilitates the layout optimization and reliability improvement, allowing the correct choice of the device geometry and configuration to achieve the best possible thermal performance.

Computational Modeling of Cardiac Excitation-Contraction Coupling in Physiological and Pathological Conditions

The cardiomyocyte is a complex biological system where many mechanisms interact non-linearly to regulate the coupling between electrical excitation and mechanical contraction. For this reason, the development of mathematical models is fundamental in the field of cardiac electrophysiology, where the use of computational tools has become complementary to the classical experimentation. My doctoral research has been focusing on the development of such models for investigating the regulation of ventricular excitation-contraction coupling at the single cell level. In particular, the following researches are presented in this thesis: 1) Study of the unexpected deleterious effect of a Na channel blocker on a long QT syndrome type 3 patient. Experimental results were used to tune a Na current model that recapitulates the effect of the mutation and the treatment, in order to investigate how these influence the human action potential. Our research suggested that the analysis of the clinical phenotype is not sufficient for recommending drugs to patients carrying mutations with undefined electrophysiological properties. 2) Development of a model of L-type Ca channel inactivation in rabbit myocytes to faithfully reproduce the relative roles of voltage- and Ca-dependent inactivation. The model was applied to the analysis of Ca current inactivation kinetics during normal and abnormal repolarization, and predicts arrhythmogenic activity when inhibiting Ca-dependent inactivation, which is the predominant mechanism in physiological conditions. 3) Analysis of the arrhythmogenic consequences of the crosstalk between β-adrenergic and Ca-calmodulin dependent protein kinase signaling pathways. The descriptions of the two regulatory mechanisms, both enhanced in heart failure, were integrated into a novel murine action potential model to investigate how they concur to the development of cardiac arrhythmias. These studies show how mathematical modeling is suitable to provide new insights into the mechanisms underlying cardiac excitation-contraction coupling and arrhythmogenesis.

Numerical and Analytical Methods for Laser-Plasma Acceleration Physics

Theories and numerical modeling are fundamental tools for understanding, optimizing and designing present and future laser-plasma accelerators (LPAs). Laser evolution and plasma wave excitation in a LPA driven by a weakly relativistically intense, short-pulse laser propagating in a preformed parabolic plasma channel, is studied analytically in 3D including the effects of pulse steepening and energy depletion. At higher laser intensities, the process of electron self-injection in the nonlinear bubble wake regime is studied by means of fully self-consistent Particle-in-Cell simulations. Considering a non-evolving laser driver propagating with a prescribed velocity, the geometrical properties of the non-evolving bubble wake are studied. For a range of parameters of interest for laser plasma acceleration, The dependence of the threshold for self-injection in the non-evolving wake on laser intensity and wake velocity is characterized. Due to the nonlinear and complex nature of the Physics involved, computationally challenging numerical simulations are required to model laser-plasma accelerators operating at relativistic laser intensities. The numerical and computational optimizations, that combined in the codes INF&RNO and INF&RNO/quasi-static give the possibility to accurately model multi-GeV laser wakefield acceleration stages with present supercomputing architectures, are discussed. The PIC code jasmine, capable of efficiently running laser-plasma simulations on Graphics Processing Units (GPUs) clusters, is presented. GPUs deliver exceptional performance to PIC codes, but the core algorithms had to be redesigned for satisfying the constraints imposed by the intrinsic parallelism of the architecture. The simulation campaigns, run with the code jasmine for modeling the recent LPA experiments with the INFN-FLAME and CNR-ILIL laser systems, are also presented.