Tesis sobre el tema "Rareté des données"
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Leroy, Boris. "Utilisation des bases de données biodiversité pour la conservation des taxons d’invertébrés : indices de rareté des assemblages d’espèces et modèles de prédiction de répartition d’espèces". Paris, Muséum national d'histoire naturelle, 2012. http://www.theses.fr/2012MNHN0033.
Texto completoInvertebrate taxa are underrepresented in conservation biology. To improve their inclusion, we aimed at providing principles and tools for their conservation. We analysed biodiversity database —defined as databases compiling species occurrences in space and time— which are the only sources of data for most invertebrate taxa. We applied important principles of data quality, and used a metric to quantify the completeness of biodiversity databases. We first developed a new tool at the assemblage level on the basis of databases of spiders and marine invertebrates: the Index of Relative Rarity. This index integrates a flexible parameter (the rarity cutoff) which allows fitting the index with respect to the considered taxon, geographic area and spatial scale. We then improved this index by including multiple scales or multiple phyla to assess the rarity of assemblages. We then developed tools at the species level: species distribution models. Using spiders as an example, we proposed an appropriate application for conservation purposes, to (1) define conservation priorities for species and (2) identify where conservation actions are most likely to succeed. The principles and methods that we developed allow an appropriate use of available biodiversity databases for conservation, are transferable to other invertebrate taxa and are innovative tools for conservation programs across multiple spatial scales
Michellier, Caroline. "Contribuer à la prévention des risques d'origine géologique :l'évaluation de la vulnérabilité des populations dans un contexte de rareté de données. Les cas de Goma et Bukavu (RDCongo)". Doctoral thesis, Universite Libre de Bruxelles, 2017. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/257755.
Texto completoDoctorat en Sciences
info:eu-repo/semantics/nonPublished
Li, Chuyuan. "Facing Data Scarcity in Dialogues for Discourse Structure Discovery and Prediction". Electronic Thesis or Diss., Université de Lorraine, 2023. http://www.theses.fr/2023LORR0107.
Texto completoA document is more than a random combination of sentences. It is, instead, a cohesive entity where sentences interact with each other to create a coherent structure and convey specific communicative goals. The field of discourse examines the sentence organization within a document, aiming to reveal its underlying structural information. Discourse analysis plays a crucial role in Natural Language Processing (NLP) and has demonstrated its usefulness in various downstream applications like summarization and question answering. Existing research efforts have focused on automatically extracting discourse structures through tasks such as discourse relation identification and discourse parsing. However, these data-driven methods have predominantly been applied to monologue scenarios, leading to limited availability and generalizability of discourse parsers for dialogues. In this thesis, we address this challenging problem: discourse analysis in dialogues, which presents unique difficulties due to the scarcity of suitable annotated data.We approach discourse analysis along two research lines: “Discourse Feature Discovery” and “Discourse Structure Prediction”. In the first research line, we conduct experiments to investigate linguistic markers, both lexical and non-lexical, in text classification tasks. We are particularly interested in the context of mental disorder identification since it reflects a realistic scenario. To address the issue of data sparsity, we propose techniques for enhancing data representation and feature engineering. Our results demonstrate that non-lexical and discourse-level (even though shallow) features are reliable indicators in developing more general and robust classifiers. In the second research line, our objective is to directly predict the discourse structure of a given document. We adopt the Segmented Discourse Representation Theory (SDRT) framework, which represents a document as a graph. The task of extracting this graph-like structure using machine learning techniques is commonly known as discourse parsing. Taking inspiration from recent studies that investigate the inner workings of Transformer-based models (“BERTology”'), we leverage discourse information encoded in Pre-trained Language Models (PLMs) such as Bidirectional Encoder Representations from Transformers (BERT) and propose innovative extraction methods that require minimal supervision. Our discourse parsing approach involves two steps: first, we predict the discourse structure, and then we identify the relations within the structure. This two-stage process allows for a comprehensive analysis of the parser's performance at each stage. Using self-supervised learning strategies, our parser achieves encouraging results for the full parsing. We conduct extensive analyses to evaluate the parser's performance across different discourse structures and propose directions for future improvements
Falip, Joris. "Structuration de données multidimensionnelles : une approche basée instance pour l'exploration de données médicales". Thesis, Reims, 2019. http://www.theses.fr/2019REIMS014/document.
Texto completoA posteriori use of medical data accumulated by practitioners represents a major challenge for clinical research as well as for personalized patient follow-up. However, health professionals lack the appropriate tools to easily explore, understand and manipulate their data. To solve this, we propose an algorithm to structure elements by similarity and representativeness. This method allows individuals in a dataset to be grouped around representative and generic members who are able to subsume the elements and summarize the data. This approach processes each dimension individually before aggregating the results and is adapted to high-dimensional data and also offers transparent, interpretable and explainable results. The results we obtain are suitable for exploratory analysis and reasoning by analogy: the structure is similar to the organization of knowledge and decision-making process used by experts. We then propose an anomaly detection algorithm that allows complex and high-dimensional anomalies to be detected by analyzing two-dimensional projections. This approach also provides interpretable results. We evaluate these two algorithms on real and simulated high-dimensional data with up to thousands of dimensions. We analyze the properties of graphs resulting from the structuring of elements. We then describe a medical data pre-processing tool and a web application for physicians. Through this intuitive tool, we propose a visual structure of the elements to ease the exploration. This decision support prototype assists medical diagnosis by allowing the physician to navigate through the data and explore similar patients. It can also be used to test clinical hypotheses on a cohort of patients
Maaroufi, Meriem. "Interopérabilité des données médicales dans le domaine des maladies rares dans un objectif de santé publique". Thesis, Paris 6, 2016. http://www.theses.fr/2016PA066275/document.
Texto completoThe digitalization of healthcare is on and multiple e-health projects are unceasingly coming up. In the rare diseases context, a field that has become a public health policy priority in France, e-health could be a solution to improve rare diseases epidemiology and to propose a better care for patients. The national data bank for rare diseases (BNDMR) offers the centralization of these epidemiological studies conduction for all rare diseases and all affected patients followed in the French healthcare system. The BNDMR must grow in a dense and heterogeneous digital landscape. Developing the BNDMR interoperability is the objective of this thesis’ work. How to identify patients, including fetuses? How to federate patients’ identities to avoid duplicates creation? How to link patients’ data to allow studies’ conduction? In response to these questions, we propose a universal method for patients’ identification that meets the requirements of health data protection. Which data should be collected in the national data bank? How to improve and facilitate the development of interoperability between these data and those from the wide range of the existing systems? In response to these questions, we first propose the collection of a standardized minimum data set for all rare diseases. The implementation of international standards provides a first step toward interoperability. We then propose to move towards the discovery of mappings between heterogeneous data sources. Minimizing human intervention by adopting automated alignment techniques and making these alignments’ results reliable and exploitable were the main motivations of our proposal
Alamé, Melissa. "Intégration de données et caractérisation du microenvironnement tumoral de tumeurs rares". Thesis, Montpellier, 2020. http://www.theses.fr/2020MONTT046.
Texto completoThe development of high-throughput technologies, especially Next Generation Sequencing, has triggered considerable advances in tumor understanding and molecular classification. Patient subgroups for a same tumor have been defined and characterized. Those subgroups are typically associated with a particular prognosis or eligible to a specific targeted therapy. These progresses paved the way towards personalized medicine.The understanding of the contribution of the tumor microenvironment (TME) to disease aggressiveness, progression, and therapy resistance is another revolution in cancer biology and patient care. The contribution of the aforementioned high-throughput technologies was essential. At the era of immunotherapy, the sub-classification of tumors based on their TME composition identified patient subgroups correlated to survival and to their response to this particular class of drugs. Despite a formidable community effort, the molecular and immunological classification of tumors has not been completed for every cancer, some rare and aggressive entities still require thorough characterization. Moreover, most TME studies have focused on the cellular composition and they neglected the mapping of the intercellular communications networks occurring in neoplasms. The advent of single-cell technologies is filling this gap, but with a strong focus on the most frequent cancers.In my thesis, I have both deployed advanced data integration methods and a novel approach to infer ligand-receptor networks relied on a database (LRdb), which is developed by the Colinge Lab, to characterize the TME of two rare tumors, Salivary Duct Carcinoma (SDC) and Primary Central Nervous System Diffuse Large B-Cell Lymphoma (PCNSL). I have combined classical – yet advanced – bioinformatic and multivariate statistics methods integrating bulk transcriptomics and proteomics data, including fresh and TCGA data. Those computational techniques were supplemented with immunofluorescence and immunohistochemistry coupled with digital imaging to obtain experimental validations. To accommodate limited patient cohorts, I have searched for highly coherent messages at all the levels of my analyses. I also devoted important efforts relating our findings with the literature to put them in a clinical perspective. In particular, our approach revealed TME groups of tumors with particular prognosis, immune evasion and therapy resistance mechanisms, several clinical biomarkers, and new therapeutic perspectives
Garcelon, Nicolas. "Problématique des entrepôts de données textuelles : dr Warehouse et la recherche translationnelle sur les maladies rares". Thesis, Sorbonne Paris Cité, 2017. http://www.theses.fr/2017USPCB257/document.
Texto completoThe repurposing of clinical data for research has become widespread with the development of clinical data warehouses. These data warehouses are modeled to integrate and explore structured data related to thesauri. These data come mainly from machine (biology, genetics, cardiology, etc.) but also from manual data input forms. The production of care is also largely providing textual data from hospital reports (hospitalization, surgery, imaging, anatomopathologic etc.), free text areas in electronic forms. This mass of data, little used by conventional warehouses, is an indispensable source of information in the context of rare diseases. Indeed, the free text makes it possible to describe the clinical picture of a patient with more precision and expressing the absence of signs and uncertainty. Particularly for patients still undiagnosed, the doctor describes the patient's medical history outside any nosological framework. This wealth of information makes clinical text a valuable source for translational research. However, this requires appropriate algorithms and tools to enable optimized re-use by doctors and researchers. We present in this thesis the data warehouse centered on the clinical document, which we have modeled, implemented and evaluated. In three cases of use for translational research in the context of rare diseases, we attempted to address the problems inherent in textual data: (i) recruitment of patients through a search engine adapted to textual (data negation and family history detection), (ii) automated phenotyping from textual data, and (iii) diagnosis by similarity between patients based on phenotyping. We were able to evaluate these methods on the data warehouse of Necker-Enfants Malades created and fed during this thesis, integrating about 490,000 patients and 4 million reports. These methods and algorithms were integrated into the software Dr Warehouse developed during the thesis and distributed in Open source since September 2017
Garret, Philippine. "Approches bioinformatiques innovantes pour l’analyse de données de séquençage à haut-débit appliquées à l’étude de pathologies génétiques rares avec anomalies du développement". Thesis, Bourgogne Franche-Comté, 2020. http://www.theses.fr/2020UBFCK020.
Texto completoIn the last years, the advent of exome sequencing (ES) in diagnosis and in research led to the identification of the genetic bases of many Mendelian disorders, allowing many diagnostic wavering cases to be solved. Nevertheless, ES data analysis only leads to the identification of pathogenic or likely pathogenic variants in 30 to 45 % of the undiagnosed cases. Indeed, some limits exist, both at clinical, molecular and bioinformatic levels. The constant evolution of the clinical knowledge, of the number of genes involved in human diseases, and of the clinical-biological correlations, has a significant impact on data analysis, leading to a progressive improvement in diagnostic research. Limits of the current technologies, especially not covered regions, exist, but have been significantly reduced in the recent years. Although genome sequencing will solve some undiagnosed cases, especially in case of non-coding or structural variants, there is still a lot of information to be extracted and analyzed from ES data. Finally, beyond SNV and CNV analyzes, other genetic events can be involved in rare disorders, requiring a bioinformatic development to optimize results.The aim of the project was therefore to improve bioinformatic approaches of ES data analysis in order to identify new molecular mechanisms involved in rare genetic disorders and reduce diagnostic wavering.Several strategies were established. The first one consisted in reanalysing ES data from 80 undiagnosed patients, who were sequenced by the Laboratoire CERBA (CIFRE thesis). It led to the identification of 2 new candidate genes involved in ID, especially OTUD7A gene (article 1). The second strategy was the development of a bioinformatic pipeline in order to extract mitochondrial DNA data from ES data. The mitochondrial genome is not targeted by exome capture kits but can be extracted from off-target data, giving the opportunity to analyze it from preexisting ES data. From the GAD exomes cohort of undiagnosed patients, 2 causal variations were identified in 2 individuals out of 928, affected with neuro-developmental disorder. It thus solved the diagnostic wavering in 0.2 % of patients without diagnosis (article 2). The third strategy consisted in the development of a bioinformatic pipeline to identify mobile elements insertion within ES data, with the expectation that about 0.03 % of the pathogenic variants originate from de novo mobile element insertion. From the GAD exomes cohort of 3322 undiagnosed patients, this step led to the identification of two Alu element insertions in FERMT1 and GRIN2B gene exons (article 3, in process).This PhD permitted to push out some ES limits. Other perspectives exist, and are explored by the GAD team, in connection with the European Solve-RD project
Himoudi, Abdelilah. "Simulation numérique de la cinétique des ions dans les gaz rares faiblement ionisés : détermination des données de base". Toulouse 3, 1993. http://www.theses.fr/1993TOU30171.
Texto completoChennen, Kirsley. "Maladies rares et "Big Data" : solutions bioinformatiques vers une analyse guidée par les connaissances : applications aux ciliopathies". Thesis, Strasbourg, 2016. http://www.theses.fr/2016STRAJ076/document.
Texto completoOver the last decade, biomedical research and medical practice have been revolutionized by the post-genomic era and the emergence of Big Data in biology. The field of rare diseases, are characterized by scarcity from the patient to the domain knowledge. Nevertheless, rare diseases represent a real interest as the fundamental knowledge accumulated as well as the developed therapeutic solutions can also benefit to common underlying disorders. This thesis focuses on the development of new bioinformatics solutions, integrating Big Data and Big Data associated approaches to improve the study of rare diseases. In particular, my work resulted in (i) the creation of PubAthena, a tool for the recommendation of relevant literature updates, (ii) the development of a tool for the analysis of exome datasets, VarScrut, which combines multi-level knowledge to improve the resolution rate
Rida, Hania. "Nouvelles données sur les systèmes graphite-lithium-europium et graphite-lithium-calcium". Thesis, Nancy 1, 2011. http://www.theses.fr/2011NAN10019/document.
Texto completoThe molten alloy solid-liquid method containing lithium has recently enabled the synthesis of several bulk graphite intercalation compounds (GICs) in graphite-lithium-alkaline earth metal systems. As part of this thesis, this synthesis method was extended to graphite-lithium-lanthanide systems, with an additional difficulty which is the lack of knowledge of lithium-lanthanide binary phase diagrams whose data are crucial for determining the temperature range and chemical composition of alloys that may lead to GICs.The immersion of pyrographite platelets in some europium-lithium alloys wisely chosen led to a binary EuC6 compound as well as a graphite-lithium-europium first stage ternary compound.Kinetics study of EuC6 compound was followed by ex situ X-ray diffraction in order to understand the different reaction steps and identify intermediate phases leading to the thermodynamically stable final compound. This mechanism revealed a reaction process more "cooperative" than that leading to CaC6 binary compound and was described by a succession of steps that contribute to the bulk insertion of europium.The elementary composition of the ternary compound was determined by ions beam analysis allowing the simultaneous quantification of the three elements lithium, carbon and europium. The refinement of these analyses led to the chemical formula Li0,25Eu1,95C6 for the ternary compound. EuC6 has also been studied by nuclear microprobe analysis, and especially the C/Eu atomic ratio equal to 6 has been confirmed.Structural studies have been undertaken for binary and ternary compounds. On one hand, it was possible to fully resolve the three-dimensional structure of the binary EuC6, which crystallizes in a hexagonal unit cell with P63/mmc space group. On the other hand, the c axis stacking sequence of the poly-layered intercalated sheet of the ternary compound was modeled by combining structural data with information from the ions beam analysis. The graphite intercalation compounds are low-dimensional solids that are ideal for the study of structure-properties relations. Thus in graphite-lithium-calcium system, superconducting character has been studied for CaC6 and Li3Ca2C6 compounds by muons spin spectroscopy ([mu]SR). For the graphite-lithium-europium system, previous magnetic measurements have been continued and supplemented by [mu]SR analysis (for Li0,25Eu1,95C6 and EuC6) and by low temperature 151Eu Mössbauer spectroscopy (for Li0,25Eu1,95C6)
Szathmary, Laszlo. "Méthodes symboliques de fouille de données avec la plate-forme Coron". Phd thesis, Université Henri Poincaré - Nancy I, 2006. http://tel.archives-ouvertes.fr/tel-00336374.
Texto completoLes contributions principales de cette thèse sont : (1) nous avons développé et adapté des algorithmes pour trouver les règles d'association minimales non-redondantes ; (2) nous avons défini une nouvelle base pour les règles d'associations appelée “règles fermées” ; (3) nous avons étudié un champ de l'ECBD important mais relativement peu étudié, à savoir l'extraction des motifs rares et des règles d'association rares ; (4) nous avons regroupé nos algorithmes et une collection d'autres algorithmes ainsi que d'autres opérations auxiliaires d'ECBD dans une boîte à outils logicielle appelée Coron.
Brard, Caroline. "Approche Bayésienne de la survie dans les essais cliniques pour les cancers rares". Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLS474/document.
Texto completoBayesian approach augments the information provided by the trial itself by incorporating external information into the trial analysis. In addition, this approach allows the results to be expressed in terms of probability of some treatment effect, which is more informative and interpretable than a p-value and a confidence interval. In addition, the frequent reduction of an analysis to a binary interpretation of the results (significant versus non-significant) is particularly harmful in rare diseases.In this context, the objective of my work was to explore the feasibility, constraints and contribution of the Bayesian approach in clinical trials in rare cancers with a primary censored endpoint. A review of the literature confirmed that the implementation of Bayesian methods is still limited in the analysis of clinical trials with a censored endpoint.In the second part of our work, we developed a Bayesian design, integrating historical data in the setting of a real clinical trial with a survival endpoint in a rare disease (osteosarcoma). The prior incorporated individual historical data on the control arm and aggregate historical data on the relative treatment effect. Through a large simulation study, we evaluated the operating characteristics of the proposed design and calibrated the model while exploring the issue of commensurability between historical and current data. Finally, the re-analysis of three clinical trials allowed us to illustrate the contribution of Bayesian approach to the expression of the results, and how this approach enriches the frequentist analysis of a trial
Nambot, Sophie. "Exploration pangénomique des anomalies du développement de causes rares". Thesis, Bourgogne Franche-Comté, 2019. http://www.theses.fr/2019UBFCI012.
Texto completoTitle : Genome-wide exploration of congenital anomalies of rare causesKey words : congenital anomalies, exome sequencing, data-sharing, reverse phenotypingCongenital anomalies are a group of diseases that are both clinically and molecularly heterogeneous. They include more than 3,000 monogenic diseases, but only a third of them have a known molecular cause. Although advances in sequencing techniques have identified hundreds of new genes in recent years, many patients remain undiagnosed. The vast genetic heterogeneity of these conditions challenges the conventional diagnostic approach that typically includes clinical expertise, a pan-genomic microarray study and/or targeted analysis of known genes and, recently, exome sequencing targeting the genes already associated with human disease. Until genome sequencing becomes more affordable and the interpretation of its data for diagnostic use is better perceived, we have chosen to explore new strategies to optimize the identification of new molecular bases through exome sequencing.The first article aimed to demonstrate the feasibility and effectiveness of annual reanalysis of negative exome sequencing data in a diagnostic setting. Patients eligible for the study had developmental anomalies, but no molecular cause was established after a standard diagnostic procedure including DNA chromosome analysis and diagnostic exome analysis. This first study yielded a significant number of additional diagnoses, but also identified candidate variants for which we used international data-sharing and reverse phenotyping to establish cohorts of genotypic and/or phenotypic replication and genotype-phenotype correlations. These strategies allowed us to meet the ACMG criteria necessary to establish the pathogenicity of these variants.With this experience, and because we wished to go further in identifying new molecular bases for our patients, we continued the reanalysis project within a research framework. This was the focus of the second article of this thesis. The reanalysis project led to the identification of 17 new genes associated with congenital anomalies. Data-sharing has led to the development of numerous international collaborations and functional studies carried out by specialized teams.The third article illustrated the application of these tools in a syndromic form of ultra-rare intellectual disability. Following a considerable collaborative effort, we were able to accurately describe the phenotype of 25 unreported patients in the literature with pathogenic variants in the TBR1 gene, a candidate gene in autism spectrum disorders associated to intellectual disability.These various studies demonstrate how innovative strategies can be effective for identifying new molecular bases in patients with congenital anomalies. These strategies include exome data reanalysis, reverse phenotyping, and international data-sharing. For patients and their families, knowing the molecular basis of the disease makes it possible to understand the origin of the condition and to put an end to diagnostic wandering. In addition, they are able to learn more about the prognosis and developmental progression, and they can obtain appropriate care management. This information is also essential for reliable genetic counseling, and may offer the possibility of prenatal or even pre-implantation diagnosis. These new diagnoses also give geneticists a chance to understand new physiopathological processes, to develop new diagnostic tests and even to discover new therapeutic targets
Pellier, Karine. "La dynamique structurelle et spatiale des systèmes de brevets". Thesis, Montpellier 1, 2010. http://www.theses.fr/2010MON10025.
Texto completoAt the behest of Schumpeter's seminal works, innovation is now positioned at the heart of economic analysis. However, since these pioneering works, not enough innovation studies have been devoted to the uses of patent over time. Starting from this assertion, the present thesis aims first and foremost at providing - in addition to good quality empirical information and new statistical series - a new interpretation of patents in their structural and spatial dimensions, based on a cliometric approach. Our first contribution is to present the organisation of a new database on the evolution over a long period of time of patents in 40 countries from the XVIIth century up to 1945 and in over 150 countries from 1945 to the present time. We show in a second step that rare but nevertheless significant events conditioned the heartbeat of the economic history of patents. Wars, the promulgation of laws, the opening or closing of offices, but also purely statistical effects standardized over the long term the existence of patent systems through the application and granting of the series under study. Furthermore we determine the periodicity of our patent series using a spectral and co-spectral analysis. Finally we propose a more contemporary insight - in terms of convergence - into structural and more specifically spatial dynamics at work in the European countries patent systems
Rafaranalisoa, Esther. "Donnees nouvelles sur la hibonite (ca a112 o19) de madagascar". Paris 6, 1988. http://www.theses.fr/1988PA066502.
Texto completoBayar, Mohamed Amine. "Randomized Clinical Trials in Oncology with Rare Diseases or Rare Biomarker-based Subtypes". Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLS441.
Texto completoLarge sample sizes are required in randomized trials designed to meet typical one-sided α-level of 0.025 and at least 80% power. This may be unachievable in a reasonable time frame even with international collaborations. It is either because the medical condition is rare, or because the trial focuses on an uncommon subset of patients with a rare molecular subtype where the treatment tested is deemed relevant. We simulated a series of two-arm superiority trials over a long research horizon (15 years). Within the series of trials, the treatment selected after each trial becomes the control treatment of the next one. Different disease severities, accrual rates, and hypotheses of how treatments improve over time were considered. We showed that compared with two larger trials with the typical one-sided α-level of 0.025, performing a series of small trials with relaxed α-levels leads on average to larger survival benefits over a long research horizon, but also to higher risk of selecting a worse treatment at the end of the research period. We then extended this framework with more 'flexible' designs including interim analyses for futility and/or efficacy, and three-arm adaptive designs with treatment selection at interim. We showed that including an interim analysis with a futility rule is associated with an additional survival gain and a better risk control as compared to series with no interim analysis. Including an interim analysis for efficacy yields almost no additional gain. Series based on three-arm trials are associated with a systematic improvement of the survival gain and the risk control as compared to series of two-arm trials. In the third part of the thesis, we examined the issue of randomized trials evaluating a treatment algorithm instead of a single drugs' efficacy. The treatment in the experimental group depends on the mutation, unlike the control group. We evaluated two methods based on the Cox frailty model to estimate the treatment effect in each mutation: Maximum Integrated Partial Likellihood (MIPL) using package coxme and Maximum H-Likelihood (MHL) using package frailtyHL. MIPL method performs slightly better. In presence of a heterogeneous treatment effect, the two methods underestimate the treatment effect in mutations where the treatment effect is large, and overestimates the treatment effect in mutations where the treatment effect is small
Scélo, Ghislaine. "Facteurs de risque de trois cancers rares : le cancer de l'intestin grêle, le mélanome oculaire, et le carcinome nasopharyngé. Utilisation de données existantes recueillies en routine". Paris 11, 2006. http://www.theses.fr/2006PA11T027.
Texto completoMoreau, Juliette. "Propriétés thermodynamiques, données structurales et mécanismes de formation des complexes de l'acide 1,4,7,10-tétraazacyclododécane - 1,4,7,10-tétraacétique et de son dérivé tétracarboxyethyl avec Eu3+, Gd3+ et Tb3+". Reims, 2003. http://www.theses.fr/2003REIMS017.
Texto completoThe thermodynamic stability of lanthanide ions (Eu3+, Gd3+ et Tb3+) complexes with two tetraazacyclododecane polycarboxylic ligands (DOTA and tetracarboxyethylDOTA) was studied by potentimetry. This study confirmed the important stability of this compounds and showed that the kinetic of thier formation was very slow. Several reorganisation steps involving intermediates species are necesseray to obtain the thermodynamic stable compounds. In order to characterize these complexes, luminescence and EXAFS spectroscopy studies were carried out, leading to the determination of the mean number of water molecules coordinated to the lanthanide cations. This last method, applied to complexesallowed us to precise the nature of the donor atoms that surround the metal and the corresponding binding lengths. This results have allowed us to propose a reactional mechanism for each ligand, starting from the hydrated lanthanide ion and leading in three steps to the final stable complexes
Bouzouita-Bayoudh, Inès. "Etude et extraction des règles associatives de classification en classification supervisée". Thesis, Montpellier 2, 2012. http://www.theses.fr/2012MON20217.
Texto completoWithin the framework of this thesis, our interest is focused on classification accuracy and the optimalité of the traversal of the search. we introduced a new direct associative classification method called IGARC that extracts directly a classifier formed by generic associative classification rules from a training set in order to reduce the number of associative classification rules without jeopardizing the classification accuracy. Carried out experiments outlined that IGARC is highly competitive in comparison with popular classification methods.We also introduced a new classification approach called AFORTIORI. We address the problem of generating relevant frequent and rare classification rules. Our work is motivated by the long-standing open question of devising an efficient algorithm for finding rules with low support. A particularly relevant field for rare item sets and rare associative classification rules is medical diagnosis. The proposed approach is based on the cover set classical algorithm. It allows obtaining frequent and rare rules while exploring the search space in a depth first manner. To this end, AFORTIORI adopts the covering set algorithm and uses the cover measure in order to guide the traversal of the search space and to generate the most interesting rules for the classification framework even rare ones. We describe our method and provide comparisons with common methods of associative classification on standard benchmark data set
Turati, Pietro. "Méthodes de simulation adaptative pour l’évaluation des risques de système complexes". Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLC032/document.
Texto completoRisk assessment is conditioned on the knowledge and information available at the moment of the analysis. Modeling and simulation are ways to explore and understand system behavior, for identifying critical scenarios and avoiding surprises. A number of simulations of the model are run with different initial and operational conditions to identify scenarios leading to critical consequences and to estimate their probabilities of occurrence. For complex systems, the simulation models can be: i) high-dimensional; ii) black-box; iii) dynamic; and iv) computationally expensive to run, preventing the analyst from running the simulations for the multiple conditions that need to be considered.The present thesis presents advanced frameworks of simulation-based risk assessment. The methods developed within the frameworks are attentive to limit the computational cost required by the analysis, in order to keep them scalable to complex systems. In particular, all methods proposed share the powerful idea of automatically focusing and adaptively driving the simulations towards those conditions that are of interest for the analysis, i.e., for risk-oriented information.The advantages of the proposed methods have been shown with respect to different applications including, among others, a gas transmission subnetwork, a power network and the Advanced Lead Fast Reactor European Demonstrator (ALFRED)
Hassan, Mohsen. "Knowledge Discovery Considering Domain Literature and Ontologies : Application to Rare Diseases". Electronic Thesis or Diss., Université de Lorraine, 2017. http://www.theses.fr/2017LORR0092.
Texto completoEven if they are uncommon, Rare Diseases (RDs) are numerous and generally sever, what makes their study important from a health-care point of view. Few databases provide information about RDs, such as Orphanet and Orphadata. Despite their laudable effort, they are incomplete and usually not up-to-date in comparison with what exists in the literature. Indeed, there are millions of scientific publications about these diseases, and the number of these publications is increasing in a continuous manner. This makes the manual extraction of this information painful and time consuming and thus motivates the development of semi-automatic approaches to extract information from texts and represent it in a format suitable for further applications. This thesis aims at extracting information from texts and using the result of the extraction to enrich existing ontologies of the considered domain. We studied three research directions (1) extracting relationships from text, i.e., extracting Disease-Phenotype (D-P) relationships; (2) identifying new complex entities, i.e., identifying phenotypes of a RD and (3) enriching an existing ontology on the basis of the relationship previously extracted, i.e., enriching a RD ontology. First, we mined a collection of abstracts of scientific articles that are represented as a collection of graphs for discovering relevant pieces of biomedical knowledge. We focused on the completion of RD description, by extracting D-P relationships. This could find applications in automating the update process of RD databases such as Orphanet. Accordingly, we developed an automatic approach named SPARE*, for extracting D-P relationships from PubMed abstracts, where phenotypes and RDs are annotated by a Named Entity Recognizer. SPARE* is a hybrid approach that combines a pattern-based method, called SPARE, and a machine learning method (SVM). It benefited both from the relatively good precision of SPARE and from the good recall of the SVM. Second, SPARE* has been used for identifying phenotype candidates from texts. We selected high-quality syntactic patterns that are specific for extracting D-P relationships only. Then, these patterns are relaxed on the phenotype constraint to enable extracting phenotype candidates that are not referenced in databases or ontologies. These candidates are verified and validated by the comparison with phenotype classes in a well-known phenotypic ontology (e.g., HPO). This comparison relies on a compositional semantic model and a set of manually-defined mapping rules for mapping an extracted phenotype candidate to a phenotype term in the ontology. This shows the ability of SPARE* to identify existing and potentially new RD phenotypes. We applied SPARE* on PubMed abstracts to extract RD phenotypes that we either map to the content of Orphanet encyclopedia and Orphadata; or suggest as novel to experts for completing these two resources. Finally, we applied pattern structures for classifying RDs and enriching an existing ontology. First, we used SPARE* to compute the phenotype description of RDs available in Orphadata. We propose comparing and grouping RDs in regard to their phenotypic descriptions, and this by using pattern structures. The pattern structures enable considering both domain knowledge, consisting in a RD ontology and a phenotype ontology, and D-P relationships from various origins. The lattice generated from this pattern structures suggests a new classification of RDs, which in turn suggests new RD classes that do not exist in the original RD ontology. As their number is large, we proposed different selection methods to select a reduced set of interesting RD classes that we suggest for experts for further analysis
Basile, Deana. "Speechio delle rare e virtuose donne, the role of the female interlocutor in the sixteenth-century dialogues on love". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape9/PQDD_0010/NQ59103.pdf.
Texto completoModeley, Derek. "Etude des états doublement excités de H- et des processus de seuil dans les collisions H-/gaz rare par spectroscopie électronique à zéro degré". Paris 6, 2003. http://www.theses.fr/2003PA066458.
Texto completoBajja, Ali. "Nouvelles données pétrographiques et géochimiques sur les formations volcaniques précambriennes du Djebel Saghro (anti-atlas marocain), basaltes en coussins du P II et volcanites de la série de Ouarzazate (P III)". Nancy 1, 1987. http://www.theses.fr/1987NAN10130.
Texto completoHassan, Mohsen. "Knowledge Discovery Considering Domain Literature and Ontologies : Application to Rare Diseases". Thesis, Université de Lorraine, 2017. http://www.theses.fr/2017LORR0092/document.
Texto completoEven if they are uncommon, Rare Diseases (RDs) are numerous and generally sever, what makes their study important from a health-care point of view. Few databases provide information about RDs, such as Orphanet and Orphadata. Despite their laudable effort, they are incomplete and usually not up-to-date in comparison with what exists in the literature. Indeed, there are millions of scientific publications about these diseases, and the number of these publications is increasing in a continuous manner. This makes the manual extraction of this information painful and time consuming and thus motivates the development of semi-automatic approaches to extract information from texts and represent it in a format suitable for further applications. This thesis aims at extracting information from texts and using the result of the extraction to enrich existing ontologies of the considered domain. We studied three research directions (1) extracting relationships from text, i.e., extracting Disease-Phenotype (D-P) relationships; (2) identifying new complex entities, i.e., identifying phenotypes of a RD and (3) enriching an existing ontology on the basis of the relationship previously extracted, i.e., enriching a RD ontology. First, we mined a collection of abstracts of scientific articles that are represented as a collection of graphs for discovering relevant pieces of biomedical knowledge. We focused on the completion of RD description, by extracting D-P relationships. This could find applications in automating the update process of RD databases such as Orphanet. Accordingly, we developed an automatic approach named SPARE*, for extracting D-P relationships from PubMed abstracts, where phenotypes and RDs are annotated by a Named Entity Recognizer. SPARE* is a hybrid approach that combines a pattern-based method, called SPARE, and a machine learning method (SVM). It benefited both from the relatively good precision of SPARE and from the good recall of the SVM. Second, SPARE* has been used for identifying phenotype candidates from texts. We selected high-quality syntactic patterns that are specific for extracting D-P relationships only. Then, these patterns are relaxed on the phenotype constraint to enable extracting phenotype candidates that are not referenced in databases or ontologies. These candidates are verified and validated by the comparison with phenotype classes in a well-known phenotypic ontology (e.g., HPO). This comparison relies on a compositional semantic model and a set of manually-defined mapping rules for mapping an extracted phenotype candidate to a phenotype term in the ontology. This shows the ability of SPARE* to identify existing and potentially new RD phenotypes. We applied SPARE* on PubMed abstracts to extract RD phenotypes that we either map to the content of Orphanet encyclopedia and Orphadata; or suggest as novel to experts for completing these two resources. Finally, we applied pattern structures for classifying RDs and enriching an existing ontology. First, we used SPARE* to compute the phenotype description of RDs available in Orphadata. We propose comparing and grouping RDs in regard to their phenotypic descriptions, and this by using pattern structures. The pattern structures enable considering both domain knowledge, consisting in a RD ontology and a phenotype ontology, and D-P relationships from various origins. The lattice generated from this pattern structures suggests a new classification of RDs, which in turn suggests new RD classes that do not exist in the original RD ontology. As their number is large, we proposed different selection methods to select a reduced set of interesting RD classes that we suggest for experts for further analysis
Chabiron, Aliouka. "Les gisements d'uranium de la caldeira de Streltsovka (Transbaikalie, Russie)". Nancy 1, 1999. http://www.theses.fr/1999NAN10069.
Texto completoVan, de Steen Cyril. "Modélisation des propriétés de transport des ions moléculaires de krypton et xénon pour l'optimisation des générateurs de plasma froids utilisant les gaz rares". Thesis, Toulouse 3, 2018. http://www.theses.fr/2018TOU30264/document.
Texto completoThe use of cold plasmas based on rare gases (Rg) in biomedical applications as well as in space propulsion is clearly evolving. To optimize these plasma reactors, a fine understanding of the processes taking place in these reactors is necessary. This thesis aims to provide the missing data in the literature (transport coefficients and reaction rates) through mesoscopic data (cross-sections) obtained from microscopic data (interaction potentials) for xenon and krypton in their parent gas. Only cold plasmas composed of a single type of atom are considered. As krypton and xenon are rare gases, and so have, in the neutral state little / no interaction between them. Therefore, only ion - atom collisions will be considered. Due to the low ion energies in the cold plasma, only the first 6 excited states of the Rg2+ pair will be taken into account. These 6 states will be classified in two groups, 2P1/2 and 2P3/2. In this work, two different interaction potentials available in the literature are used and compared for the Kr+/Kr and Xe+/Xe collision systems in the calculation of cross-sections. For collisions involving ionic dimers (Kr2+/Kr and Xe2+/Xe), the interaction potentials are calculated from the DIM model (Diatomics In Molecules) which is a combination of the atomic potentials of neutral - neutral and ionic - neutral interactions. The cross-sections required to obtain the missing mesoscopic data are calculated from three different methods. The first method is the quantum method which allows, by a resolution of the Schrödinger equation, to obtain exactly the cross-sections from the interaction potentials. This exact method, which consumes a lot of computation time, is used as a reference to validate the two other approximate methods. The second method, called semi-classical, is based on the same expression as the quantum cross section but uses an approximate phase shift (JWKB approximation), induced by the interaction potential, between the scattered wave and the incident wave. [...]
Seppecher, Manon. "Mining call detail records to reconstruct global urban mobility patterns for large scale emissions calculation". Electronic Thesis or Diss., Lyon, 2022. http://www.theses.fr/2022LYSET002.
Texto completoRoad traffic contributes significantly to atmospheric emissions in urban areas, a major issue in the fight against climate change. Therefore, joint monitoring of road traffic and related emissions is essential for urban public decision-making. And beyond this kind of procedure, public authorities need methods for evaluating transport policies according to environmental criteria.Coupling traffic models with traffic-related emission models is a suitable response to this need. However, integrating this solution into decision support tools requires a refined and dynamic char-acterization of urban mobility. Cell phone data, particularly Call Detail Records, are an interesting alternative to traditional data to estimate this mobility. They are rich, massive, and available worldwide. However, their use in literature for systematic traffic characterization has remained limited. It is due to low spatial resolution and temporal sampling rates sensitive to communication behaviors.This Ph.D. thesis investigates the estimation of traffic variables necessary for calculating air emis-sions (total distances traveled and average traffic speeds) from such data, despite their biases. The first significant contribution is to articulate methods of classification of individuals with two distinct approaches of mobility reconstruction. A second contribution is developing a method for estimating traffic speeds based on the fusion of large amounts of travel data. Finally, we present a complete methodological process of modeling and data processing. It relates the methods proposed in this thesis coherently
Desmet, Alain. "Ophiolites et séries basaltiques crétacées des régions caraïbes et nordandines : bassins marginaux, dorsales ou plateaux océaniques ?" Nancy 1, 1994. http://www.theses.fr/1994NAN10313.
Texto completoEl, Korbi Amell. "Identification de caractéristiques communes et rares dans les ARN structurés dans la base de données Rfam". Thèse, 2015. http://hdl.handle.net/1866/13798.
Texto completoNoncoding RNAs (ncRNAs) are RNA transcripts that are not translated into proteins yet they play important functional roles in the cell including gene regulation, transcription and translation. Among the many categories of ncRNAs that were discovered, we find the well-known ribosomal RNA (rRNA), transfer RNA (tRNA), snoRNA and microRNAs (miRNA). The functions of ncRNAs are tightly linked to their structural features. Thus, understanding and predicting RNA structure as well as developing methods to search for new ncRNAs help to gain insight into these molecules. Technological advances have made available abundant sequence information accessible in databases such as Rfam, which provides alignments and structural information of many ncRNA families. In this research project, we retrieved the information from the Rfam database about the sequences of all secondary structures such as hairpin loops, internal loops, bulges, etc. in all RNA families. A local database, RNAstem, was created to facilitate the use and manipulation of information about secondary structure motifs. We analyzed hairpin loops, bulges and internal loops using the compiled data about the frequencies of occurrence of each loop or bulge and calculated a frequency score. The frequency score is aimed to be an indicator for the abundance of a specific secondary structure motif. While minimizing the bias caused by the high redundancy of some RNA classes as ribosomal RNAs, the frequency score allowed us to identify the rare motifs in each category as well as the common ones. Our findings about the abundant motifs confirm what is already known from previous studies (ex. abundant GNRA or UNCG tetraloops). We found very large gaps between the most abundant and rare RNA structural features. Moreover, we discovered that "A" and "U" dominate single stranded RNA regions, whether they are bulges or loops. We further explored the possibility of using this data to improve current prediction tools for ncRNAs by applying a filter to new candidates. We developed a score system, RNAscore, that evaluates RNAs depending on their motif contents and we tested the program with many different controls.
Bendakir, Narimel. "RARE : un système de recommandation de cours basé sur les régles d'association". Thèse, 2006. http://hdl.handle.net/1866/16732.
Texto completoCatto, Lionel. "La réduction des impacts environnementaux des technologies de l’information par le droit". Thèse, 2016. http://hdl.handle.net/1866/18628.
Texto completoInformation and communication technologies (ICT) are far from being intangible goods and do have an environmental impact during their entire life cycle. Green IT stands at the crossroads of sustainable development and ICT. Green IT law consists of a set of rules governing the relations between information technologies and environment. The purpose of this thesis is to investigate the European and North American legal standards regulating the environment impacts of ICT throughout the three phases of their life cycle. In the first part, the design phase of ICT is examined. At this stage, existing regulations on eco-design, the use of rare earth elements, and the interdiction of planned obsolescence are of particular relevance. The thesis then studies how companies are trying to reduce the use-phase energy consumption of ICT, notably through the Corporate Social Responsability. The issue of the multiplication of data centres, due to an ever-growing demand, is also discussed. In the end, the thesis considers the end-of-life phase of ICT and the directives created by the European Union that affect recycling and waste reduction management at an international level.