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Search Results: 1 - 10 of 1461 matches for " Filippo Castiglione "
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Forecasting price increments using an artificial Neural Network
Filippo Castiglione
Physics , 2000,
Abstract: Financial forecasting is a difficult task due to the intrinsic complexity of the financial system. In the present paper we relate our experience using neural nets as financial time series forecast method. In particular we show that a neural net able to forecast the sign of the price increments with a success rate slightly above 50 percent can be found.
Diffusion and Aggregation in an Agent Based Model of Stock Market Fluctuations
Filippo Castiglione
Quantitative Finance , 2000, DOI: 10.1142/S0129183100000754
Abstract: We describe a new model to simulate the dynamic interactions between market price and the decisions of two different kind of traders. They possess spatial mobility allowing to group together to form coalitions. Each coalition follows a strategy chosen from a proportional voting ``dominated'' by a leader's decision. The interplay of both kind of agents gives rise to complex price dynamics that is consistent with the main stylized facts of financial time series.
Criticality of Timing for Anti-HIV Therapy Initiation
Filippo Castiglione,Paola Paci
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0015294
Abstract: The time of initiation of antiretroviral therapy in HIV-1 infected patients has a determinant effect on the viral dynamics. The question is, how far can the therapy be delayed? Is sooner always better? We resort to clinical data and to microsimulations to forecast the dynamics of the viral load at therapy interruption after prolonged antiretroviral treatment. A computational model previously evaluated, produces results that are statistically adherent to clinical data. In addition, it allows a finer grain analysis of the impact of the therapy initiation point to the disease course. We find a swift increase of the viral density as a function of the time of initiation of the therapy measured when the therapy is stopped. In particular there is a critical time delay with respect to the infection instant beyond which the therapy does not affect the viral rebound. Initiation of the treatment is beneficial because it can down-regulate the immune activation, hence limiting viral replication and spread.
Identifying Correlations between Chromosomal Proximity of Genes and Distance of Their Products in Protein-Protein Interaction Networks of Yeast
Daniele Santoni, Filippo Castiglione, Paola Paci
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0057707
Abstract: In this article we present evidence for a relationship between chromosome gene loci and the topological properties of the protein-protein interaction network corresponding to the set of genes under consideration. Specifically, for each chromosome of the Saccharomyces cerevisiae genome, the distribution of the intra-chromosome inter-gene distances was analyzed and a positive correlation with the distance among the corresponding proteins of the protein-protein interaction network was found. In order to study this relationship we used concepts based on non-parametric statistics and information theory. We provide statistical evidence that if two genes are closely located, then it is likely that their protein products are closely located in the protein-protein interaction network, or in other words, that they are involved in the same biological process.
Computational Immunology Meets Bioinformatics: The Use of Prediction Tools for Molecular Binding in the Simulation of the Immune System
Nicolas Rapin,Ole Lund,Massimo Bernaschi,Filippo Castiglione
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0009862
Abstract: We present a new approach to the study of the immune system that combines techniques of systems biology with information provided by data-driven prediction methods. To this end, we have extended an agent-based simulator of the immune response, C-ImmSim, such that it represents pathogens, as well as lymphocytes receptors, by means of their amino acid sequences and makes use of bioinformatics methods for T and B cell epitope prediction. This is a key step for the simulation of the immune response, because it determines immunogenicity. The binding of the epitope, which is the immunogenic part of an invading pathogen, together with activation and cooperation from T helper cells, is required to trigger an immune response in the affected host. To determine a pathogen's epitopes, we use existing prediction methods. In addition, we propose a novel method, which uses Miyazawa and Jernigan protein–protein potential measurements, for assessing molecular binding in the context of immune complexes. We benchmark the resulting model by simulating a classical immunization experiment that reproduces the development of immune memory. We also investigate the role of major histocompatibility complex (MHC) haplotype heterozygosity and homozygosity with respect to the influenza virus and show that there is an advantage to heterozygosity. Finally, we investigate the emergence of one or more dominating clones of lymphocytes in the situation of chronic exposure to the same immunogenic molecule and show that high affinity clones proliferate more than any other. These results show that the simulator produces dynamics that are stable and consistent with basic immunological knowledge. We believe that the combination of genomic information and simulation of the dynamics of the immune system, in one single tool, can offer new perspectives for a better understanding of the immune system.
Modeling lymphocyte homing and encounters in lymph nodes
Valentina Baldazzi, Paola Paci, Massimo Bernaschi, Filippo Castiglione
BMC Bioinformatics , 2009, DOI: 10.1186/1471-2105-10-387
Abstract: In this paper, we present a hybrid discrete/continuous model of the lymph node, accounting for differences in cell velocity and chemotactic response, influenced by the spatial compartmentalization of the lymph node and the regulation of cells migration, encounter, and antigen presentation during the inflammation process.Our model reproduces the correct timing of an immune response, including the observed time delay between duplication of T helper cells and duplication of B cells in response to antigen exposure. Furthermore, we investigate the consequences of the absence of dendritic cells at different times during infection, and the dependence of system dynamics on the regulation of lymphocyte exit from lymph nodes. In both cases, the model predicts the emergence of an impaired immune response, i.e., the response is significantly reduced in magnitude. Dendritic cell removal is also shown to delay the response time with respect to normal conditions.Lymph nodes and Peyer's patches play key roles in the development of an appropriate and efficient immune response. Once an Antigen (Ag) is captured by Ag-processing cells, it is rapidly carried to the nearest lymph node, where it is presented to specific lymphocytes to trigger an immune response. The recognition phase must be highly efficient: within a few hours, it is necessary to find specific lymphocytes among a repertoire that includes a very large number of receptors [1,2]. The specific architecture of the lymph node and a fine-tuned balance between diffusion, chemotaxis, and receptor expression are the basis of this process.Human lymph nodes are bean-shaped structures that range in size from a few millimeters to about 1-2 cm in their normal state. Internally, two main regions can be distinguished: the medulla and the cortex. The cortex can be further divided into an inner part, the paracortex (also called the T cell area), rich in T lymphocytes and an outer area, the node cortex that includes the B cell area consisti
Modelling vaccination schedules for a cancer immunoprevention vaccine
Motta Santo,Castiglione Filippo,Lollini Pierluigi,Pappalardo Francesco
Immunome Research , 2005, DOI: 10.1186/1745-7580-1-5
Abstract: We present a systematic approach to search for an effective vaccination schedule using mathematical computerized models. Our study is based on our previous model that simulates the cancer vs immune system competition activated by tumor vaccine. This model accurately reproduces in-vivo experiments results on HER-2/neu mice treated with the immuno-prevention cancer vaccine (Triplex) for mammary carcinoma. In vivo experiments have shown the effectiveness of Triplex vaccine in protection of mice from mammary carcinoma. The full protection was conferred using chronic (prophylactic) vaccination protocol while therapeutic vaccination was less effcient. In the present paper we use the computer simulations to systematically search for a vaccination schedule which prevents solid tumor formation. The strategy we used for defining a successful vaccination schedule is to control the number of cancer cells with vaccination cycles. We found that, applying the vaccination scheme used in in-vivo experiments, the number of vaccine injections can be reduced roughly by 30%.
HIV Reservoirs and Immune Surveillance Evasion Cause the Failure of Structured Treatment Interruptions: A Computational Study
Emiliano Mancini, Filippo Castiglione, Massimo Bernaschi, Andrea de Luca, Peter M. A. Sloot
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0036108
Abstract: Continuous antiretroviral therapy is currently the most effective way to treat HIV infection. Unstructured interruptions are quite common due to side effects and toxicity, among others, and cannot be prevented. Several attempts to structure these interruptions failed due to an increased morbidity compared to continuous treatment. The cause of this failure is poorly understood and often attributed to drug resistance. Here we show that structured treatment interruptions would fail regardless of the emergence of drug resistance. Our computational model of the HIV infection dynamics in lymphoid tissue inside lymph nodes, demonstrates that HIV reservoirs and evasion from immune surveillance themselves are sufficient to cause the failure of structured interruptions. We validate our model with data from a clinical trial and show that it is possible to optimize the schedule of interruptions to perform as well as the continuous treatment in the absence of drug resistance. Our methodology enables studying the problem of treatment optimization without having impact on human beings. We anticipate that it is feasible to steer new clinical trials using computational models.
Development of Immune-Specific Interaction Potentials and Their Application in the Multi-Agent-System VaccImm
Anna Lena Woelke, Joachim von Eichborn, Manuela S. Murgueitio, Catherine L. Worth, Filippo Castiglione, Robert Preissner
PLOS ONE , 2011, DOI: 10.1371/journal.pone.0023257
Abstract: Peptide vaccination in cancer therapy is a promising alternative to conventional methods. However, the parameters for this personalized treatment are difficult to access experimentally. In this respect, in silico models can help to narrow down the parameter space or to explain certain phenomena at a systems level. Herein, we develop two empirical interaction potentials specific to B-cell and T-cell receptor complexes and validate their applicability in comparison to a more general potential. The interaction potentials are applied to the model VaccImm which simulates the immune response against solid tumors under peptide vaccination therapy. This multi-agent system is derived from another immune system simulator (C-ImmSim) and now includes a module that enables the amino acid sequence of immune receptors and their ligands to be taken into account. The multi-agent approach is combined with approved methods for prediction of major histocompatibility complex (MHC)-binding peptides and the newly developed interaction potentials. In the analysis, we critically assess the impact of the different modules on the simulation with VaccImm and how they influence each other. In addition, we explore the reasons for failures in inducing an immune response by examining the activation states of the immune cell populations in detail. In summary, the present work introduces immune-specific interaction potentials and their application to the agent-based model VaccImm which simulates peptide vaccination in cancer therapy.
Timely HAART initiation may pave the way for a better viral control
Paola Paci, Federico Martini, Massimo Bernaschi, Gianpiero D'Offizi, Filippo Castiglione
BMC Infectious Diseases , 2011, DOI: 10.1186/1471-2334-11-56
Abstract: In this article we use a computational model and clinical data to identify the role of HAART timing on the residual capability to control HIV rebound after treatment suspension. Analyses of clinical data from three groups of patients initiating HAART respectively before seroconversion (very early), during the acute phase (early) and in the chronic phase (late), evidence differences arising from the very early events of the viral infection.The computational model allows a fine grain assessment of the impact of HAART timing on the disease outcome, from acute to chronic HIV-1 infection. Both patients' data and computer simulations reveal that HAART timing may indeed affect the HIV control capability after treatment discontinuation. In particular, we find a median time to viral rebound that is significantly longer in very early than in late patients.A timing threshold is identified, corresponding to approximately three weeks post-infection, after which the capability to control HIV replication is lost. Conversely, HAART initiation occurring within three weeks from the infection could allow to preserve a significant control capability. This time could be related to the global triggering of uncontrolled immune activation, affecting residual immune competence preservation and HIV reservoir establishment.The question of when antiretroviral therapy has to be initiated remains a challenging issue. Recent studies show that the early immune response to HIV-1 infection is likely to be an important factor in determining the clinical course of disease [1]. The first weeks following HIV-1 transmission are extremely dynamic. They are associated with rapid damage to generative immune cell micro-environments and with immune responses that partially control the virus. Following HIV-1 infection, the virus first replicates locally in the mucosa and then is transported to draining lymph nodes where further amplification occurs. This initial phase of infection, until the systemic viral dis
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