New approaches to open problems in gene expression microarray data

In the past decade, the advent of efficient genome sequencing tools and high-throughput experimental biotechnology has lead to enormous progress in the life science. Among the most important innovations is the microarray tecnology. It allows to quantify the expression for thousands of genes simultaneously by measurin the hybridization from a tissue of interest to probes on a small glass or plastic slide. The characteristics of these data include a fair amount of random noise, a predictor dimension in the thousand, and a sample noise in the dozens. One of the most exciting areas to which microarray technology has been applied is the challenge of deciphering complex disease such as cancer. In these studies, samples are taken from two or more groups of individuals with heterogeneous phenotypes, pathologies, or clinical outcomes. these samples are hybridized to microarrays in an effort to find a small number of genes which are strongly correlated with the group of individuals. Eventhough today methods to analyse the data are welle developed and close to reach a standard organization (through the effort of preposed International project like Microarray Gene Expression Data -MGED- Society [1]) it is not unfrequant to stumble in a clinician's question that do not have a compelling statistical method that could permit to answer it.The contribution of this dissertation in deciphering disease regards the development of new approaches aiming at handle open problems posed by clinicians in handle specific experimental designs. In Chapter 1 starting from a biological necessary introduction, we revise the microarray tecnologies and all the important steps that involve an experiment from the production of the array, to the quality controls ending with preprocessing steps that will be used into the data analysis in the rest of the dissertation. While in Chapter 2 a critical review of standard analysis methods are provided stressing most of problems that In Chapter 3 is introduced a method to adress the issue of unbalanced design of miacroarray experiments. In microarray experiments, experimental design is a crucial starting-point for obtaining reasonable results. In a two-class problem, an equal or similar number of samples it should be collected between the two classes. However in some cases, e.g. rare pathologies, the approach to be taken is less evident. We propose to address this issue by applying a modified version of SAM [2]. MultiSAM consists in a reiterated application of a SAM analysis, comparing the less populated class (LPC) with 1,000 random samplings of the same size from the more populated class (MPC) A list of the differentially expressed genes is generated for each SAM application. After 1,000 reiterations, each single probe given a "score" ranging from 0 to 1,000 based on its recurrence in the 1,000 lists as differentially expressed. The performance of MultiSAM was compared to the performance of SAM and LIMMA [3] over two simulated data sets via beta and exponential distribution. The results of all three algorithms over low- noise data sets seems acceptable However, on a real unbalanced two-channel data set reagardin Chronic Lymphocitic Leukemia, LIMMA finds no significant probe, SAM finds 23 significantly changed probes but cannot separate the two classes, while MultiSAM finds 122 probes with score >300 and separates the data into two clusters by hierarchical clustering. We also report extra-assay validation in terms of differentially expressed genes Although standard algorithms perform well over low-noise simulated data sets, multi-SAM seems to be the only one able to reveal subtle differences in gene expression profiles on real unbalanced data. In Chapter 4 a method to adress similarities evaluation in a three-class prblem by means of Relevance Vector Machine [4] is described. In fact, looking at microarray data in a prognostic and diagnostic clinical framework, not only differences could have a crucial role. In some cases similarities can give useful and, sometimes even more, important information. The goal, given three classes, could be to establish, with a certain level of confidence, if the third one is similar to the first or the second one. In this work we show that Relevance Vector Machine (RVM) [2] could be a possible solutions to the limitation of standard supervised classification. In fact, RVM offers many advantages compared, for example, with his well-known precursor (Support Vector Machine - SVM [3]). Among these advantages, the estimate of posterior probability of class membership represents a key feature to address the similarity issue. This is a highly important, but often overlooked, option of any practical pattern recognition system. We focused on Tumor-Grade-three-class problem, so we have 67 samples of grade I (G1), 54 samples of grade 3 (G3) and 100 samples of grade 2 (G2). The goal is to find a model able to separate G1 from G3, then evaluate the third class G2 as test-set to obtain the probability for samples of G2 to be member of class G1 or class G3. The analysis showed that breast cancer samples of grade II have a molecular profile more similar to breast cancer samples of grade I. Looking at the literature this result have been guessed, but no measure of significance was gived before.

La sorpresa come fattore critico indicatore di sintonizzazione emotiva in bambini normali e con disturbi pervasivi dello sviluppo

The topic of this study is surprise, re gard as an evolutionary complex process, with manifold implication in different fields, from neurological, since aspecific correlate of surprise exist more or less at every level of neuronal processes (e.g. Rao e Ballard, 1999.), to behavioral , inasmuch a s our ability to quickly valuate(assess), recognize and learn from surprising events, are be regarded as pivotal for survival (e.g. Ranganath e Rainer, 2003). In particular this work, going from belief that surprise is really a psychoevolutive mechanism of primary relevance, has the objective to investigate if there may be a substantial connection between development of surprise' emotion and specific developmental problems, or, if in subjects with pervasive developmental disorders surprise may embody (represent) a essential mechanism of emotional tuning, and consequently if abnormalities in such process may be at the base of at least a part of cognitive and behavioural problems that determine (describe) this pathology. Theoretical reasons lead us to conside r this particular pathologic condition, recall to a broad area of research concern the comprehension of belief as marker of ability to reasons about mental states of others (i.e. Theory of Mind), and in addition, at the detection of specific subjects' diff iculty in this field. On the experimental side, as well as limited of this work, we have to compare comprehension and expression of surprise in a sample of 21 children with pervasive developmental disorders (PDD), with a sample of 35 children without deve lopmental problems, in a range of age 3-12. Method After the customary approach to become friendly with the child, an experimenter and an accomplice showed three boxes of nuts, easily to distinguish one from the other because of their different colours an d , working together with the child, the contents of one of the boxes were replaced and a different material (macaroni, pebbles) was put in the box. for the purpose of preparing a surprise for someone. At this stage, the accomplice excused himself/herself and left and the experimenter suggested to the child that he prepare another surprise, replacing the contents in the second box. When the accomplice came back, the child was asked to prepare a surprise for him by picking out the box that he thought was the right one for the purpose. After, and the child doesn't know it, the accomplice change the content of one of the boxes with candies and asked out to the children to open the box, in order to see if he show surprise. Result Date have obtain a significant difference between autistic and normal group, in all four tests. The expression of surprise too, is present in significantly lower degree in autistic group than in control group. Moreover, autistic children do not provide appropriate metarappresentative explanations. Conclusion Our outcome, with knowledge of the limit of our investigation at an experimental level (low number of the champions, no possibility of video registration to firm the expressions ) orient to consider eventuality that surprise, may be seen as relevant component, or indicative, in autistic spectrum disorders.

Studio e sviluppo di sistemi RFID in banda UHF

The recent widespread diffusion of radio-frequency identification (RFID) applications operating in the UHF band has been supported by both the request for greater interrogation ranges and greater and faster data exchange. UHF-RFID systems, exploiting a physical interaction based on Electromagnetic propagation, introduce many problems that have not been fully explored for the previous generations of RFID systems (e.g. HF). Therefore, the availability of reliable tools for modeling and evaluating the radio-communication between Reader and Tag within an RFID radio-link are needed. The first part of the thesis discuss the impact of real environment on system performance. In particular an analytical closed form formulation for the back-scattered field from the Tag antenna and the formulation for the lower bound of the BER achievable at the Reader side will be presented, considering different possible electromagnetic impairments. By means of the previous formulations, of the analysis of the RFID link operating in near filed conditions and of some electromagnetic/system-level co-simulations, an in-depth study of the dimensioning parameters and the actual performance of the systems will be discussed and analyzed, showing some relevant properties and trade-offs in transponder and reader design. Moreover a new low cost approach to extend the read range of the RFID UHF passive systems will be discussed. Within the scope to check the reliability of the analysis approaches and of innovative proposals, some reference transponder antennas have been designed and extensive measurement campaign has been carried out with satisfactory results. Finally, some commercial ad-hoc transponder for industrial application have been designed within the cooperation with Datalogic s.p.a., some guidelines and results will be briefly presented.

Security control brought back to the user

The activity of the Ph.D. student Juri Luca De Coi involved the research field of policy languages and can be divided in three parts. The first part of the Ph.D. work investigated the state of the art in policy languages, ending up with: (i) identifying the requirements up-to-date policy languages have to fulfill; (ii) defining a policy language able to fulfill such requirements (namely, the Protune policy language); and (iii) implementing an infrastructure able to enforce policies expressed in the Protune policy language. The second part of the Ph.D. work focused on simplifying the activity of defining policies and ended up with: (i) identifying a subset of the controlled natural language ACE to express Protune policies; (ii) implementing a mapping between ACE policies and Protune policies; and (iii) adapting the ACE Editor to guide users step by step when defining ACE policies. The third part of the Ph.D. work tested the feasibility of the chosen approach by applying it to meaningful real-world problems, among which: (i) development of a security layer on top of RDF stores; and (ii) efficient policy-aware access to metadata stores. The research activity has been performed in tight collaboration with the Leibniz Universität Hannover and further European partners within the projects REWERSE, TENCompetence and OKKAM.

Hybrid Methods for Resource Allocation and Scheduling Problems in Deterministic and Stochastic Environments

This work presents exact, hybrid algorithms for mixed resource Allocation and Scheduling problems; in general terms, those consist into assigning over time finite capacity resources to a set of precedence connected activities. The proposed methods have broad applicability, but are mainly motivated by applications in the field of Embedded System Design. In particular, high-performance embedded computing recently witnessed the shift from single CPU platforms with application-specific accelerators to programmable Multi Processor Systems-on-Chip (MPSoCs). Those allow higher flexibility, real time performance and low energy consumption, but the programmer must be able to effectively exploit the platform parallelism. This raises interest in the development of algorithmic techniques to be embedded in CAD tools; in particular, given a specific application and platform, the objective if to perform optimal allocation of hardware resources and to compute an execution schedule. On this regard, since embedded systems tend to run the same set of applications for their entire lifetime, off-line, exact optimization approaches are particularly appealing. Quite surprisingly, the use of exact algorithms has not been well investigated so far; this is in part motivated by the complexity of integrated allocation and scheduling, setting tough challenges for ``pure'' combinatorial methods. The use of hybrid CP/OR approaches presents the opportunity to exploit mutual advantages of different methods, while compensating for their weaknesses. In this work, we consider in first instance an Allocation and Scheduling problem over the Cell BE processor by Sony, IBM and Toshiba; we propose three different solution methods, leveraging decomposition, cut generation and heuristic guided search. Next, we face Allocation and Scheduling of so-called Conditional Task Graphs, explicitly accounting for branches with outcome not known at design time; we extend the CP scheduling framework to effectively deal with the introduced stochastic elements. Finally, we address Allocation and Scheduling with uncertain, bounded execution times, via conflict based tree search; we introduce a simple and flexible time model to take into account duration variability and provide an efficient conflict detection method. The proposed approaches achieve good results on practical size problem, thus demonstrating the use of exact approaches for system design is feasible. Furthermore, the developed techniques bring significant contributions to combinatorial optimization methods.