Дисертації з теми "Integration of peptidomic data"
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Suwareh, Ousmane. "Modélisation de la pepsinolyse in vitro en conditions gastriques et inférence de réseaux de filiation de peptides à partir de données de peptidomique." Electronic Thesis or Diss., Rennes, Agrocampus Ouest, 2022. https://tel.archives-ouvertes.fr/tel-04059711.
Повний текст джерелаAddressing the current demographic challenges, “civilization diseases” and the possible depletion of food resources, require optimization of food utilization and adapting their conception to the specific needs of each target population. This requires a better understanding of the different stages of the digestion process. In particular, how proteins are hydrolyzed is a major issue, due to their crucial role in human nutrition. However, the probabilistic laws governing the action of pepsin, the first protease to act in the gastrointestinal tract, are still unclear.In a first approach based on peptidomic data, we demonstrate that the hydrolysis by pepsin of a peptidebond depends on the nature of the amino acid residues in its large neighborhood, but also on physicochemical and structural variables describing its environment. In a second step, and considering the physicochemical environment at the peptide level, we propose a nonparametric model of the hydrolysis by pepsin of these peptides, and an Expectation-Maximization type estimation algorithm, offering novel perspectives for the valorization of peptidomic data. In this dynamic approach, we integrate the peptide kinship network into the estimation procedure, which leads to a more parsimonious model that is also more relevant regarding biological interpretations
Nadal, Francesch Sergi. "Metadata-driven data integration." Doctoral thesis, Universitat Politècnica de Catalunya, 2019. http://hdl.handle.net/10803/666947.
Повний текст джерелаLes dades tenen un impacte indubtable en la societat. La capacitat d’emmagatzemar i processar grans quantitats de dades disponibles és avui en dia un dels factors claus per l’èxit d’una organització. No obstant, avui en dia estem presenciant un canvi representat per grans volums de dades heterogenis. En efecte, el 90% de les dades mundials han sigut generades en els últims dos anys. Per tal de dur a terme aquestes tasques d’explotació de dades, les organitzacions primer han de realitzar una integració de les dades, combinantles a partir de diferents fonts amb l’objectiu de tenir-ne una vista unificada d’elles. Per això, aquest fet requereix reconsiderar les assumpcions tradicionals en integració amb l’objectiu de lidiar amb els requisits imposats per aquests sistemes de tractament massiu de dades. Aquesta tesi doctoral té com a objectiu proporcional un nou marc de treball per a la integració de dades en el context de sistemes de tractament massiu de dades, el qual implica lidiar amb una gran quantitat de dades heterogènies, provinents de múltiples fonts i en el seu format original. Per això, proposem un procés d’integració compost d’una seqüència d’activitats governades per una capa semàntica, la qual és implementada a partir d’un repositori de metadades compartides. Des d’una perspectiva d’administració, aquestes activitats són el desplegament d’una arquitectura d’integració de dades, seguit per la inserció d’aquestes metadades compartides. Des d’una perspectiva de consum de dades, les activitats són la integració virtual i materialització de les dades, la primera sent una tasca exploratòria i la segona una de consolidació. Seguint el marc de treball proposat, ens centrem en proporcionar contribucions a cada una de les quatre activitats. La tesi inicia proposant una arquitectura de referència de software per a sistemes de tractament massiu de dades amb coneixement semàntic. Aquesta arquitectura serveix com a planell per a desplegar un conjunt de sistemes, sent el repositori de metadades al seu nucli. Posteriorment, proposem un model basat en grafs per a la gestió de metadades. Concretament, ens centrem en donar suport a l’evolució d’esquemes i fonts de dades, un dels factors predominants en les fonts de dades heterogènies considerades. Per a l’integració virtual, proposem algorismes de rescriptura de consultes que usen el model de metadades previament proposat. Com a afegitó, considerem heterogeneïtat semàntica en les fonts de dades, les quals els algorismes de rescriptura poden resoldre automàticament. Finalment, la tesi es centra en l’activitat d’integració materialitzada. Per això proposa un mètode per a seleccionar els resultats intermedis a materialitzar un fluxes de tractament intensiu de dades. En general, els resultats d’aquesta tesi serveixen com a contribució al camp d’integració de dades en els ecosistemes de tractament massiu de dades contemporanis
Les données ont un impact indéniable sur la société. Le stockage et le traitement de grandes quantités de données disponibles constituent actuellement l’un des facteurs clés de succès d’une entreprise. Néanmoins, nous assistons récemment à un changement représenté par des quantités de données massives et hétérogènes. En effet, 90% des données dans le monde ont été générées au cours des deux dernières années. Ainsi, pour mener à bien ces tâches d’exploitation des données, les organisations doivent d’abord réaliser une intégration des données en combinant des données provenant de sources multiples pour obtenir une vue unifiée de ces dernières. Cependant, l’intégration de quantités de données massives et hétérogènes nécessite de revoir les hypothèses d’intégration traditionnelles afin de faire face aux nouvelles exigences posées par les systèmes de gestion de données massives. Cette thèse de doctorat a pour objectif de fournir un nouveau cadre pour l’intégration de données dans le contexte d’écosystèmes à forte intensité de données, ce qui implique de traiter de grandes quantités de données hétérogènes, provenant de sources multiples et dans leur format d’origine. À cette fin, nous préconisons un processus d’intégration constitué d’activités séquentielles régies par une couche sémantique, mise en oeuvre via un dépôt partagé de métadonnées. Du point de vue de la gestion, ces activités consistent à déployer une architecture d’intégration de données, suivies de la population de métadonnées partagées. Du point de vue de la consommation de données, les activités sont l’intégration de données virtuelle et matérialisée, la première étant une tâche exploratoire et la seconde, une tâche de consolidation. Conformément au cadre proposé, nous nous attachons à fournir des contributions à chacune des quatre activités. Nous commençons par proposer une architecture logicielle de référence pour les systèmes de gestion de données massives et à connaissance sémantique. Une telle architecture consiste en un schéma directeur pour le déploiement d’une pile de systèmes, le dépôt de métadonnées étant son composant principal. Ensuite, nous proposons un modèle de métadonnées basé sur des graphes comme formalisme pour la gestion des métadonnées. Nous mettons l’accent sur la prise en charge de l’évolution des schémas et des sources de données, facteur prédominant des sources hétérogènes sous-jacentes. Pour l’intégration virtuelle, nous proposons des algorithmes de réécriture de requêtes qui s’appuient sur le modèle de métadonnées proposé précédemment. Nous considérons en outre les hétérogénéités sémantiques dans les sources de données, que les algorithmes proposés sont capables de résoudre automatiquement. Enfin, la thèse se concentre sur l’activité d’intégration matérialisée et propose à cette fin une méthode de sélection de résultats intermédiaires à matérialiser dans des flux des données massives. Dans l’ensemble, les résultats de cette thèse constituent une contribution au domaine de l’intégration des données dans les écosystèmes contemporains de gestion de données massives
Jakonienė, Vaida. "Integration of biological data /." Linköping : Linköpings universitet, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-7484.
Повний текст джерелаAkeel, Fatmah Y. "Secure data integration systems." Thesis, University of Southampton, 2017. https://eprints.soton.ac.uk/415716/.
Повний текст джерелаEberius, Julian. "Query-Time Data Integration." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-191560.
Повний текст джерелаJakonienė, Vaida. "Integration of Biological Data." Doctoral thesis, Linköpings universitet, IISLAB - Laboratoriet för intelligenta informationssystem, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-7484.
Повний текст джерелаPeralta, Veronika. "Data Quality Evaluation in Data Integration Systems." Phd thesis, Université de Versailles-Saint Quentin en Yvelines, 2006. http://tel.archives-ouvertes.fr/tel-00325139.
Повний текст джерелаPeralta, Costabel Veronika del Carmen. "Data quality evaluation in data integration systems." Versailles-St Quentin en Yvelines, 2006. http://www.theses.fr/2006VERS0020.
Повний текст джерелаCette thèse porte sur la qualité des données dans les Systèmes d’Intégration de Données (SID). Nous nous intéressons, plus précisément, aux problèmes de l’évaluation de la qualité des données délivrées aux utilisateurs en réponse à leurs requêtes et de la satisfaction des exigences des utilisateurs en terme de qualité. Nous analysons également l’utilisation de mesures de qualité pour l’amélioration de la conception du SID et la conséquente amélioration de la qualité des données. Notre approche consiste à étudier un facteur de qualité à la fois, en analysant sa relation avec le SID, en proposant des techniques pour son évaluation et en proposant des actions pour son amélioration. Parmi les facteurs de qualité qui ont été proposés, cette thèse analyse deux facteurs de qualité : la fraîcheur et l’exactitude des données
Neumaier, Sebastian, Axel Polleres, Simon Steyskal, and Jürgen Umbrich. "Data Integration for Open Data on the Web." Springer International Publishing AG, 2017. http://dx.doi.org/10.1007/978-3-319-61033-7_1.
Повний текст джерелаCheng, Hui. "Data integration and visualization for systems biology data." Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/77250.
Повний текст джерелаPh. D.
Hackl, Peter, and Michaela Denk. "Data Integration: Techniques and Evaluation." Austrian Statistical Society, 2004. http://epub.wu.ac.at/5631/1/435%2D1317%2D1%2DSM.pdf.
Повний текст джерелаKerr, W. Scott. "Data integration using virtual repositories." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0005/MQ45950.pdf.
Повний текст джерелаBauckmann, Jana. "Dependency discovery for data integration." Phd thesis, Universität Potsdam, 2013. http://opus.kobv.de/ubp/volltexte/2013/6664/.
Повний текст джерелаDatenintegration hat das Ziel, Daten aus unterschiedlichen Quellen zu kombinieren und Nutzern eine einheitliche Sicht auf diese Daten zur Verfügung zu stellen. Diese Aufgabe ist gleichermaßen anspruchsvoll wie wertvoll. In dieser Dissertation werden Algorithmen zum Erkennen von Datenabhängigkeiten vorgestellt, die notwendige Informationen zur Datenintegration liefern. Der Schwerpunkt dieser Arbeit liegt auf Inklusionsabhängigkeiten (inclusion dependency, IND) im Allgemeinen und auf der speziellen Form der Bedingten Inklusionsabhängigkeiten (conditional inclusion dependency, CIND): (i) INDs ermöglichen das Finden von Strukturen in einem gegebenen Schema. (ii) INDs und CINDs unterstützen das Finden von Referenzen zwischen Datenquellen. Eine IND „A in B“ besagt, dass alle Werte des Attributs A in der Menge der Werte des Attributs B enthalten sind. Diese Arbeit liefert einen Algorithmus, der alle INDs in einer relationalen Datenquelle erkennt. Die Herausforderung dieser Aufgabe liegt in der Komplexität alle Attributpaare zu testen und dabei alle Werte dieser Attributpaare zu vergleichen. Die Komplexität bestehender Ansätze ist abhängig von der Anzahl der Attributpaare während der hier vorgestellte Ansatz lediglich von der Anzahl der Attribute abhängt. Damit ermöglicht der vorgestellte Algorithmus unbekannte Datenquellen mit großen Schemata zu untersuchen. Darüber hinaus wird der Algorithmus erweitert, um drei spezielle Formen von INDs zu finden, und ein Ansatz vorgestellt, der Fremdschlüssel aus den erkannten INDs filtert. Bedingte Inklusionsabhängigkeiten (CINDs) sind Inklusionsabhängigkeiten deren Geltungsbereich durch Bedingungen über bestimmten Attributen beschränkt ist. Nur der zutreffende Teil der Instanz muss der Inklusionsabhängigkeit genügen. Die Definition für CINDs wird in der vorliegenden Arbeit generalisiert durch die Unterscheidung von überdeckenden und vollständigen Bedingungen. Ferner werden Qualitätsmaße für Bedingungen definiert. Es werden effiziente Algorithmen vorgestellt, die überdeckende und vollständige Bedingungen mit gegebenen Qualitätsmaßen auffinden. Dabei erfolgt die Auswahl der verwendeten Attribute und Attributkombinationen sowie der Attributwerte automatisch. Bestehende Ansätze beruhen auf einer Vorauswahl von Attributen für die Bedingungen oder erkennen nur Bedingungen mit Schwellwerten von 100% für die Qualitätsmaße. Die Ansätze der vorliegenden Arbeit wurden durch zwei Anwendungsbereiche motiviert: Datenintegration in den Life Sciences und das Erkennen von Links in Linked Open Data. Die Effizienz und der Nutzen der vorgestellten Ansätze werden anhand von Anwendungsfällen in diesen Bereichen aufgezeigt.
Krisnadhi, Adila Alfa. "Ontology Pattern-Based Data Integration." Wright State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=wright1453177798.
Повний текст джерелаBraunschweig, Katrin, Julian Eberius, Maik Thiele, and Wolfgang Lehner. "Frontiers in Crowdsourced Data Integration." De Gruyter, 2012. https://tud.qucosa.de/id/qucosa%3A72850.
Повний текст джерелаDie stetig wachsende Zahl offen verfügbarer Webdaten findet momentan viel zu wenig oder gar keine Berücksichtigung in Entscheidungsprozessen. Der Grund hierfür ist insbesondere in der mangelnden Unterstützung durch anwenderfreundliche Werkzeuge zu finden, die diese Daten nutzbar machen und Wissen daraus genieren können. Zu diesem Zweck schlagen wir ein schemaoptionales Datenrepositorium vor, welches ermöglicht, heterogene Webdaten zu speichern sowie kontinuierlich zu integrieren und mit Schemainformation anzureichern. Auf Grund der dabei inhärent auftretenden Mehrdeutigkeiten, soll dieser Prozess zusätzlich um eine Crowd-basierende Verifikationskomponente unterstützt werden.
Nagyová, Barbora. "Data integration in large enterprises." Master's thesis, Vysoká škola ekonomická v Praze, 2015. http://www.nusl.cz/ntk/nusl-203918.
Повний текст джерелаTallur, Gayatri. "Uncertain data integration with probabilities." Thesis, The University of North Carolina at Greensboro, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=1551297.
Повний текст джерелаReal world applications that deal with information extraction, such as business intelligence software or sensor data management, must often process data provided with varying degrees of uncertainty. Uncertainty can result from multiple or inconsistent sources, as well as approximate schema mappings. Modeling, managing and integrating uncertain data from multiple sources has been an active area of research in recent years. In particular, data integration systems free the user from the tedious tasks of finding relevant data sources, interacting with each source in isolation using its corresponding interface and combining data from multiple sources by providing a uniform query interface to gain access to the integrated information.
Previous work has integrated uncertain data using representation models such as the possible worlds and probabilistic relations. We extend this work by determining the probabilities of possible worlds of an extended probabilistic relation. We also present an algorithm to determine when a given extended probabilistic relation can be obtained by the integration of two probabilistic relations and give the decomposed pairs of probabilistic relations.
CALABRIA, ANDREA. "Data integration for clinical genomics." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2011. http://hdl.handle.net/10281/19219.
Повний текст джерелаAl-Mutairy, Badr. "Data mining and integration of heterogeneous bioinformatics data sources." Thesis, Cardiff University, 2008. http://orca.cf.ac.uk/54178/.
Повний текст джерелаFan, Hao. "Investigating a heterogeneous data integration approach for data warehousing." Thesis, Birkbeck (University of London), 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.424299.
Повний текст джерелаSerra, Angela. "Multi-view learning and data integration for omics data." Doctoral thesis, Universita degli studi di Salerno, 2017. http://hdl.handle.net/10556/2580.
Повний текст джерелаIn recent years, the advancement of high-throughput technologies, combined with the constant decrease of the data-storage costs, has led to the production of large amounts of data from different experiments that characterise the same entities of interest. This information may relate to specific aspects of a phenotypic entity (e.g. Gene expression), or can include the comprehensive and parallel measurement of multiple molecular events (e.g., DNA modifications, RNA transcription and protein translation) in the same samples. Exploiting such complex and rich data is needed in the frame of systems biology for building global models able to explain complex phenotypes. For example, theuseofgenome-widedataincancerresearch, fortheidentificationof groups of patients with similar molecular characteristics, has become a standard approach for applications in therapy-response, prognosis-prediction, and drugdevelopment.ÂăMoreover, the integration of gene expression data regarding cell treatment by drugs, and information regarding chemical structure of the drugs allowed scientist to perform more accurate drug repositioning tasks. Unfortunately, there is a big gap between the amount of information and the knowledge in which it is translated. Moreover, there is a huge need of computational methods able to integrate and analyse data to fill this gap. Current researches in this area are following two different integrative methods: one uses the complementary information of different measurements for the 7 i i “Template” — 2017/6/9 — 16:42 — page 8 — #8 i i i i i i study of complex phenotypes on the same samples (multi-view learning); the other tends to infer knowledge about the phenotype of interest by integrating and comparing the experiments relating to it with respect to those of different phenotypes already known through comparative methods (meta-analysis). Meta-analysis can be thought as an integrative study of previous results, usually performed aggregating the summary statistics from different studies. Due to its nature, meta-analysis usually involves homogeneous data. On the other hand, multi-view learning is a more flexible approach that considers the fusion of different data sources to get more stable and reliable estimates. Based on the type of data and the stage of integration, new methodologies have been developed spanning a landscape of techniques comprising graph theory, machine learning and statistics. Depending on the nature of the data and on the statistical problem to address, the integration of heterogeneous data can be performed at different levels: early, intermediate and late. Early integration consists in concatenating data from different views in a single feature space. Intermediate integration consists in transforming all the data sources in a common feature space before combining them. In the late integration methodologies, each view is analysed separately and the results are then combined. The purpose of this thesis is twofold: the former objective is the definition of a data integration methodology for patient sub-typing (MVDA) and the latter is the development of a tool for phenotypic characterisation of nanomaterials (INSIdEnano). In this PhD thesis, I present the methodologies and the results of my research. MVDA is a multi-view methodology that aims to discover new statistically relevant patient sub-classes. Identify patient subtypes of a specific diseases is a challenging task especially in the early diagnosis. This is a crucial point for the treatment, because not allthe patients affected bythe same diseasewill have the same prognosis or need the same drug treatment. This problem is usually solved by using transcriptomic data to identify groups of patients that share the same gene patterns. The main idea underlying this research work is that to combine more omics data for the same patients to obtain a better characterisation of their disease profile. The proposed methodology is a late integration approach i i “Template” — 2017/6/9 — 16:42 — page 9 — #9 i i i i i i based on clustering. It works by evaluating the patient clusters in each single view and then combining the clustering results of all the views by factorising the membership matrices in a late integration manner. The effectiveness and the performance of our method was evaluated on six multi-view cancer datasets related to breast cancer, glioblastoma, prostate and ovarian cancer. The omics data used for the experiment are gene and miRNA expression, RNASeq and miRNASeq, Protein Expression and Copy Number Variation. In all the cases, patient sub-classes with statistical significance were found, identifying novel sub-groups previously not emphasised in literature. The experiments were also conducted by using prior information, as a new view in the integration process, to obtain higher accuracy in patients’ classification. The method outperformed the single view clustering on all the datasets; moreover, it performs better when compared with other multi-view clustering algorithms and, unlike other existing methods, it can quantify the contribution of single views in the results. The method has also shown to be stable when perturbation is applied to the datasets by removing one patient at a time and evaluating the normalized mutual information between all the resulting clusterings. These observations suggest that integration of prior information with genomic features in sub-typing analysis is an effective strategy in identifying disease subgroups. INSIdE nano (Integrated Network of Systems bIology Effects of nanomaterials) is a novel tool for the systematic contextualisation of the effects of engineered nanomaterials (ENMs) in the biomedical context. In the recent years, omics technologies have been increasingly used to thoroughly characterise the ENMs molecular mode of action. It is possible to contextualise the molecular effects of different types of perturbations by comparing their patterns of alterations. While this approach has been successfully used for drug repositioning, it is still missing to date a comprehensive contextualisation of the ENM mode of action. The idea behind the tool is to use analytical strategies to contextualise or position the ENM with the respect to relevant phenotypes that have been studied in literature, (such as diseases, drug treatments, and other chemical exposures) by comparing their patterns of molecular alteration. This could greatly increase the knowledge on the ENM molecular effects and in turn i i “Template” — 2017/6/9 — 16:42 — page 10 — #10 i i i i i i contribute to the definition of relevant pathways of toxicity as well as help in predicting the potential involvement of ENM in pathogenetic events or in novel therapeutic strategies. The main hypothesis is that suggestive patterns of similarity between sets of phenotypes could be an indication of a biological association to be further tested in toxicological or therapeutic frames. Based on the expression signature, associated to each phenotype, the strength of similarity between each pair of perturbations has been evaluated and used to build a large network of phenotypes. To ensure the usability of INSIdE nano, a robust and scalable computational infrastructure has been developed, to scan this large phenotypic network and a web-based effective graphic user interface has been built. Particularly, INSIdE nano was scanned to search for clique sub-networks, quadruplet structures of heterogeneous nodes (a disease, a drug, a chemical and a nanomaterial) completely interconnected by strong patterns of similarity (or anti-similarity). The predictions have been evaluated for a set of known associations between diseases and drugs, based on drug indications in clinical practice, and between diseases and chemical, based on literature-based causal exposure evidence, and focused on the possible involvement of nanomaterials in the most robust cliques. The evaluation of INSIdE nano confirmed that it highlights known disease-drug and disease-chemical connections. Moreover, disease similarities agree with the information based on their clinical features, as well as drugs and chemicals, mirroring their resemblance based on the chemical structure. Altogether, the results suggest that INSIdE nano can also be successfully used to contextualise the molecular effects of ENMs and infer their connections to other better studied phenotypes, speeding up their safety assessment as well as opening new perspectives concerning their usefulness in biomedicine. [edited by author]
L’avanzamento tecnologico delle tecnologie high-throughput, combinato con il costante decremento dei costi di memorizzazione, ha portato alla produzione di grandi quantit`a di dati provenienti da diversi esperimenti che caratterizzano le stesse entit`a di interesse. Queste informazioni possono essere relative a specifici aspetti fenotipici (per esempio l’espressione genica), o possono includere misure globali e parallele di diversi aspetti molecolari (per esempio modifiche del DNA, trascrizione dell’RNA e traduzione delle proteine) negli stessi campioni. Analizzare tali dati complessi `e utile nel campo della systems biology per costruire modelli capaci di spiegare fenotipi complessi. Ad esempio, l’uso di dati genome-wide nella ricerca legata al cancro, per l’identificazione di gruppi di pazienti con caratteristiche molecolari simili, `e diventato un approccio standard per una prognosi precoce piu` accurata e per l’identificazione di terapie specifiche. Inoltre, l’integrazione di dati di espressione genica riguardanti il trattamento di cellule tramite farmaci ha permesso agli scienziati di ottenere accuratezze elevate per il drug repositioning. Purtroppo, esiste un grosso divario tra i dati prodotti, in seguito ai numerosi esperimenti, e l’informazione in cui essi sono tradotti. Quindi la comunit`a scientifica ha una forte necessit`a di metodi computazionali per poter integrare e analizzate tali dati per riempire questo divario. La ricerca nel campo delle analisi multi-view, segue due diversi metodi di analisi integrative: uno usa le informazioni complementari di diverse misure per studiare fenotipi complessi su diversi campioni (multi-view learning); l’altro tende ad inferire conoscenza sul fenotipo di interesse di una entit`a confrontando gli esperimenti ad essi relativi con quelli di altre entit`a fenotipiche gi`a note in letteratura (meta-analisi). La meta-analisi pu`o essere pensata come uno studio comparativo dei risultati identificati in un particolare esperimento, rispetto a quelli di studi precedenti. A causa della sua natura, la meta-analisi solitamente coinvolge dati omogenei. D’altra parte, il multi-view learning `e un approccio piu` flessibile che considera la fusione di diverse sorgenti di dati per ottenere stime piu` stabili e affidabili. In base al tipo di dati e al livello di integrazione, nuove metodologie sono state sviluppate a partire da tecniche basate sulla teoria dei grafi, machine learning e statistica. In base alla natura dei dati e al problema statistico da risolvere, l’integrazione di dati eterogenei pu`o essere effettuata a diversi livelli: early, intermediate e late integration. Le tecniche di early integration consistono nella concatenazione dei dati delle diverse viste in un unico spazio delle feature. Le tecniche di intermediate integration consistono nella trasformazione di tutte le sorgenti dati in un unico spazio comune prima di combinarle. Nelle tecniche di late integration, ogni vista `e analizzata separatamente e i risultati sono poi combinati. Lo scopo di questa tesi `e duplice: il primo obbiettivo `e la definizione di una metodologia di integrazione dati per la sotto-tipizzazione dei pazienti (MVDA) e il secondo `e lo sviluppo di un tool per la caratterizzazione fenotipica dei nanomateriali (INSIdEnano). In questa tesi di dottorato presento le metodologie e i risultati della mia ricerca. MVDA `e una tecnica multi-view con lo scopo di scoprire nuove sotto tipologie di pazienti statisticamente rilevanti. Identificare sottotipi di pazienti per una malattia specifica `e un obbiettivo con alto rilievo nella pratica clinica, soprattutto per la diagnosi precoce delle malattie. Questo problema `e generalmente risolto usando dati di trascrittomica per identificare i gruppi di pazienti che condividono gli stessi pattern di alterazione genica. L’idea principale alla base di questo lavoro di ricerca `e quello di combinare piu` tipologie di dati omici per gli stessi pazienti per ottenere una migliore caratterizzazione del loro profilo. La metodologia proposta `e un approccio di tipo late integration basato sul clustering. Per ogni vista viene effettuato il clustering dei pazienti rappresentato sotto forma di matrici di membership. I risultati di tutte le viste vengono poi combinati tramite una tecnica di fattorizzazione di matrici per ottenere i metacluster finali multi-view. La fattibilit`a e le performance del nostro metodo sono stati valutati su sei dataset multi-view relativi al tumore al seno, glioblastoma, cancro alla prostata e alle ovarie. I dati omici usati per gli esperimenti sono relativi alla espressione dei geni, espressione dei mirna, RNASeq, miRNASeq, espressione delle proteine e della Copy Number Variation. In tutti i dataset sono state identificate sotto-tipologie di pazienti con rilevanza statistica, identificando nuovi sottogruppi precedentemente non noti in letteratura. Ulteriori esperimenti sono stati condotti utilizzando la conoscenza a priori relativa alle macro classi dei pazienti. Tale informazione `e stata considerata come una ulteriore vista nel processo di integrazione per ottenere una accuratezza piu` elevata nella classificazione dei pazienti. Il metodo proposto ha performance migliori degli algoritmi di clustering clussici su tutti i dataset. MVDA ha ottenuto risultati migliori in confronto a altri algoritmi di integrazione di tipo ealry e intermediate integration. Inoltre il metodo `e in grado di calcolare il contributo di ogni singola vista al risultato finale. I risultati mostrano, anche, che il metodo `e stabile in caso di perturbazioni del dataset effettuate rimuovendo un paziente alla volta (leave-one-out). Queste osservazioni suggeriscono che l’integrazione di informazioni a priori e feature genomiche, da utilizzare congiuntamente durante l’analisi, `e una strategia vincente nell’identificazione di sotto-tipologie di malattie. INSIdE nano (Integrated Network of Systems bIology Effects of nanomaterials) `e un tool innovativo per la contestualizzazione sistematica degli effetti delle nanoparticelle (ENMs) in contesti biomedici. Negli ultimi anni, le tecnologie omiche sono state ampiamente applicate per caratterizzare i nanomateriali a livello molecolare. E’ possibile contestualizzare l’effetto a livello molecolare di diversi tipi di perturbazioni confrontando i loro pattern di alterazione genica. Mentre tale approccio `e stato applicato con successo nel campo del drug repositioning, una contestualizzazione estensiva dell’effetto dei nanomateriali sulle cellule `e attualmente mancante. L’idea alla base del tool `e quello di usare strategie comparative di analisi per contestualizzare o posizionare i nanomateriali in confronto a fenotipi rilevanti che sono stati studiati in letteratura (come ad esempio malattie dell’uomo, trattamenti farmacologici o esposizioni a sostanze chimiche) confrontando i loro pattern di alterazione molecolare. Questo potrebbe incrementare la conoscenza dell’effetto molecolare dei nanomateriali e contribuire alla definizione di nuovi pathway tossicologici oppure identificare eventuali coinvolgimenti dei nanomateriali in eventi patologici o in nuove strategie terapeutiche. L’ipotesi alla base `e che l’identificazione di pattern di similarit`a tra insiemi di fenotipi potrebbe essere una indicazione di una associazione biologica che deve essere successivamente testata in ambito tossicologico o terapeutico. Basandosi sulla firma di espressione genica, associata ad ogni fenotipo, la similarit`a tra ogni coppia di perturbazioni `e stata valuta e usata per costruire una grande network di interazione tra fenotipi. Per assicurare l’utilizzo di INSIdE nano, `e stata sviluppata una infrastruttura computazionale robusta e scalabile, allo scopo di analizzare tale network. Inoltre `e stato realizzato un sito web che permettesse agli utenti di interrogare e visualizzare la network in modo semplice ed efficiente. In particolare, INSIdE nano `e stato analizzato cercando tutte le possibili clique di quattro elementi eterogenei (un nanomateriale, un farmaco, una malattia e una sostanza chimica). Una clique `e una sotto network completamente connessa, dove ogni elemento `e collegato con tutti gli altri. Di tutte le clique, sono state considerate come significative solo quelle per le quali le associazioni tra farmaco e malattia e farmaco e sostanze chimiche sono note. Le connessioni note tra farmaci e malattie si basano sul fatto che il farmaco `e prescritto per curare tale malattia. Le connessioni note tra malattia e sostanze chimiche si basano su evidenze presenti in letteratura del fatto che tali sostanze causano la malattia. Il focus `e stato posto sul possibile coinvolgimento dei nanomateriali con le malattie presenti in tali clique. La valutazione di INSIdE nano ha confermato che esso mette in evidenza connessioni note tra malattie e farmaci e tra malattie e sostanze chimiche. Inoltre la similarit`a tra le malattie calcolata in base ai geni `e conforme alle informazioni basate sulle loro informazioni cliniche. Allo stesso modo le similarit`a tra farmaci e sostanze chimiche rispecchiano le loro similarit`a basate sulla struttura chimica. Nell’insieme, i risultati suggeriscono che INSIdE nano pu`o essere usato per contestualizzare l’effetto molecolare dei nanomateriali e inferirne le connessioni rispetto a fenotipi precedentemente studiati in letteratura. Questo metodo permette di velocizzare il processo di valutazione della loro tossicit`a e apre nuove prospettive per il loro utilizzo nella biomedicina. [a cura dell'autore]
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Sutiwaraphun, Janjao. "Knowledge integration in distributed data mining." Thesis, Imperial College London, 2001. http://hdl.handle.net/10044/1/8924.
Повний текст джерелаWilliams, Dean Ashley. "Combining data integration and information extraction." Thesis, Birkbeck (University of London), 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.499152.
Повний текст джерелаMorris, Christopher Robert. "Data integration in the rail domain." Thesis, University of Birmingham, 2018. http://etheses.bham.ac.uk//id/eprint/8204/.
Повний текст джерелаSilva, Luís António Bastião. "Federated architecture for biomedical data integration." Doctoral thesis, Universidade de Aveiro, 2015. http://hdl.handle.net/10773/15759.
Повний текст джерелаThe last decades have been characterized by a continuous adoption of IT solutions in the healthcare sector, which resulted in the proliferation of tremendous amounts of data over heterogeneous systems. Distinct data types are currently generated, manipulated, and stored, in the several institutions where patients are treated. The data sharing and an integrated access to this information will allow extracting relevant knowledge that can lead to better diagnostics and treatments. This thesis proposes new integration models for gathering information and extracting knowledge from multiple and heterogeneous biomedical sources. The scenario complexity led us to split the integration problem according to the data type and to the usage specificity. The first contribution is a cloud-based architecture for exchanging medical imaging services. It offers a simplified registration mechanism for providers and services, promotes remote data access, and facilitates the integration of distributed data sources. Moreover, it is compliant with international standards, ensuring the platform interoperability with current medical imaging devices. The second proposal is a sensor-based architecture for integration of electronic health records. It follows a federated integration model and aims to provide a scalable solution to search and retrieve data from multiple information systems. The last contribution is an open architecture for gathering patient-level data from disperse and heterogeneous databases. All the proposed solutions were deployed and validated in real world use cases.
A adoção sucessiva das tecnologias de comunicação e de informação na área da saúde tem permitido um aumento na diversidade e na qualidade dos serviços prestados, mas, ao mesmo tempo, tem gerado uma enorme quantidade de dados, cujo valor científico está ainda por explorar. A partilha e o acesso integrado a esta informação poderá permitir a identificação de novas descobertas que possam conduzir a melhores diagnósticos e a melhores tratamentos clínicos. Esta tese propõe novos modelos de integração e de exploração de dados com vista à extração de conhecimento biomédico a partir de múltiplas fontes de dados. A primeira contribuição é uma arquitetura baseada em nuvem para partilha de serviços de imagem médica. Esta solução oferece um mecanismo de registo simplificado para fornecedores e serviços, permitindo o acesso remoto e facilitando a integração de diferentes fontes de dados. A segunda proposta é uma arquitetura baseada em sensores para integração de registos electrónicos de pacientes. Esta estratégia segue um modelo de integração federado e tem como objetivo fornecer uma solução escalável que permita a pesquisa em múltiplos sistemas de informação. Finalmente, o terceiro contributo é um sistema aberto para disponibilizar dados de pacientes num contexto europeu. Todas as soluções foram implementadas e validadas em cenários reais.
Sernadela, Pedro Miguel Lopes. "Data integration services for biomedical applications." Doctoral thesis, Universidade de Aveiro, 2018. http://hdl.handle.net/10773/23511.
Повний текст джерелаIn the last decades, the field of biomedical science has fostered unprecedented scientific advances. Research is stimulated by the constant evolution of information technology, delivering novel and diverse bioinformatics tools. Nevertheless, the proliferation of new and disconnected solutions has resulted in massive amounts of resources spread over heterogeneous and distributed platforms. Distinct data types and formats are generated and stored in miscellaneous repositories posing data interoperability challenges and delays in discoveries. Data sharing and integrated access to these resources are key features for successful knowledge extraction. In this context, this thesis makes contributions towards accelerating the semantic integration, linkage and reuse of biomedical resources. The first contribution addresses the connection of distributed and heterogeneous registries. The proposed methodology creates a holistic view over the different registries, supporting semantic data representation, integrated access and querying. The second contribution addresses the integration of heterogeneous information across scientific research, aiming to enable adequate data-sharing services. The third contribution presents a modular architecture to support the extraction and integration of textual information, enabling the full exploitation of curated data. The last contribution lies in providing a platform to accelerate the deployment of enhanced semantic information systems. All the proposed solutions were deployed and validated in the scope of rare diseases.
Nas últimas décadas, o campo das ciências biomédicas proporcionou grandes avanços científicos estimulados pela constante evolução das tecnologias de informação. A criação de diversas ferramentas na área da bioinformática e a falta de integração entre novas soluções resultou em enormes quantidades de dados distribuídos por diferentes plataformas. Dados de diferentes tipos e formatos são gerados e armazenados em vários repositórios, o que origina problemas de interoperabilidade e atrasa a investigação. A partilha de informação e o acesso integrado a esses recursos são características fundamentais para a extração bem sucedida do conhecimento científico. Nesta medida, esta tese fornece contribuições para acelerar a integração, ligação e reutilização semântica de dados biomédicos. A primeira contribuição aborda a interconexão de registos distribuídos e heterogéneos. A metodologia proposta cria uma visão holística sobre os diferentes registos, suportando a representação semântica de dados e o acesso integrado. A segunda contribuição aborda a integração de diversos dados para investigações científicas, com o objetivo de suportar serviços interoperáveis para a partilha de informação. O terceiro contributo apresenta uma arquitetura modular que apoia a extração e integração de informações textuais, permitindo a exploração destes dados. A última contribuição consiste numa plataforma web para acelerar a criação de sistemas de informação semânticos. Todas as soluções propostas foram validadas no âmbito das doenças raras.
Mishra, Alok. "Data integration for regulatory module discovery." Thesis, Imperial College London, 2012. http://hdl.handle.net/10044/1/10615.
Повний текст джерелаAdai, Alex Tamas. "Uncovering microRNA function through data integration." Diss., Search in ProQuest Dissertations & Theses. UC Only, 2008. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3311333.
Повний текст джерелаFriedman, Marc T. "Representation and optimization for data integration /." Thesis, Connect to this title online; UW restricted, 1999. http://hdl.handle.net/1773/6979.
Повний текст джерелаIves, Zachary G. "Efficient query processing for data integration /." Thesis, Connect to this title online; UW restricted, 2002. http://hdl.handle.net/1773/6864.
Повний текст джерелаAyyad, Majed. "Real-Time Event Centric Data Integration." Doctoral thesis, Università degli studi di Trento, 2014. https://hdl.handle.net/11572/367750.
Повний текст джерелаAyyad, Majed. "Real-Time Event Centric Data Integration." Doctoral thesis, University of Trento, 2014. http://eprints-phd.biblio.unitn.it/1353/1/REAL-TIME_EVENT_CENTRIC_DATA_INTEGRATION.pdf.
Повний текст джерелаTous, Ruben. "Data integration with XML and semantic web technologies novel approaches in the design of modern data integration systems." Saarbrücken VDM Verlag Dr. Müller, 2006. http://d-nb.info/991303105/04.
Повний текст джерелаSonmez, Sunercan Hatice Kevser. "Data Integration Over Horizontally Partitioned Databases In Service-oriented Data Grids." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612414/index.pdf.
Повний текст джерелаcoping with various forms of data distribution and maintenance policies, scalability, performance, security and trust, reliability and resilience, legal issues etc. It is obvious that each of these dimensions deserves a separate thread of research efforts. One particular challenge among the ones listed above that is more relevant to the work presented in this thesis is coping with various forms of data distribution and maintenance policies. This thesis aims to provide a service-oriented data integration solution over data Grids for cases where distributed data sources are partitioned with overlapping sections of various proportions. This is an interesting variation which combines both replicated and partitioned data within the same data management framework. Thus, the data management infrastructure has to deal with specific challenges regarding the identification, access and aggregation of partitioned data with varying proportions of overlapping sections. To provide a solution we have extended OGSA-DAI DQP, a well-known service-oriented data access and integration middleware with distributed query processing facilities, by incorporating UnionPartitions operator into its algebra in order to cope with various unusual forms of horizontally partitioned databases. As a result
our solution extends OGSA-DAI DQP, in two points
1 - A new operator type is added to the algebra to perform a specialized union of the partitions with different characteristics, 2 - OGSA-DAI DQP Federation Description is extended to include some more metadata to facilitate the successful execution of the newly introduced operator.
Wegener, Dennis [Verfasser]. "Integration of Data Mining into Scientific Data Analysis Processes / Dennis Wegener." Bonn : Universitäts- und Landesbibliothek Bonn, 2012. http://d-nb.info/1044867434/34.
Повний текст джерелаRepchevskiy, Dmitry. "Ontology based data integration in life sciences." Doctoral thesis, Universitat de Barcelona, 2016. http://hdl.handle.net/10803/386411.
Повний текст джерелаEl objetivo de la tesis es el desarrollo de una solución práctica y estándar para la integración semántica de los datos y servicios biológicos. La tesis estudia escenarios diferentes en los cuales las ontologías pueden beneficiar el desarrollo de los servicios web, su búsqueda y su visibilidad. A pesar de que las ontologías son ampliamente utilizadas en la biología, su uso habitualmente se limita a la definición de las jerarquías taxonómicas. La tesis examina la utilidad de las ontologías para la integración de los datos en el desarrollo de los servicios web semánticos. Las ontologías que definen los tipos de datos biológicos tienen un gran valor para la integración de los datos, especialmente ante un cambio continuo de los estándares. La tesis evalúa la ontología BioMoby para la generación de los servicios web conforme con las especificaciones WS-I y los servicios REST. Otro aspecto muy importante de la tesis es el uso de las ontologías para la descripción de los servicios web. La tesis evalúa la ontología WSDL promovida por el consorcio W3C para la descripción de los servicios y su búsqueda. Finalmente, se considera la integración con las plataformas modernas de la ejecución de los flujos de trabajo como Taverna y Galaxy. A pesar de la creciente popularidad del formato JSON, los servicios web dependen mucho del XML. La herramienta OWL2XS facilita el desarrollo de los servicios web semánticos generando un esquema XML a partir de una ontología OWL 2. La integración de los servicios web es difícil de conseguir sin una adaptación de los estándares. La aplicación BioNemus genera de manera automática servicios web estándar a partir de las ontologías BioMoby. La representación semántica de los servicios web simplifica su búsqueda y anotación. El Registro Semántico de Servicios Web (BioSWR) está basado en la ontología WSDL del W3C y proporciona una representación en distintos formatos: OWL 2, WSDL 1.1, WSDL 2.0 y WADL. Para demostrar los beneficios de la descripción semántica de los servicios web se ha desarrollado un plugin para Taverna. También se ha implementado una nueva librería experimental que ha sido usada en la aplicación Galaxy Gears, la cual permite la integración de los servicios web en Galaxy. La tesis explora el alcance de la aplicación de las ontologías para la integración de los datos y los servicios biológicos, proporcionando un amplio conjunto de nuevas aplicaciones.
Wang, Guilian. "Schema mapping for data transformation and integration." Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2006. http://wwwlib.umi.com/cr/ucsd/fullcit?p3211371.
Повний текст джерелаTitle from first page of PDF file (viewed June 7, 2006). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 135-142).
Schallehn, Eike. "Efficient similarity-based operations for data integration." [S.l. : s.n.], 2004. http://deposit.ddb.de/cgi-bin/dokserv?idn=971682631.
Повний текст джерелаWiesner, Christian. "Query evaluation techniques for data integration systems." [S.l.] : [s.n.], 2004. http://deposit.ddb.de/cgi-bin/dokserv?idn=971999139.
Повний текст джерелаZhang, Baoquan. "Integration and management of ophthalmological research data." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1996. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp04/MQ31665.pdf.
Повний текст джерелаKeijzer, Ander de. "Management of uncertain data towards unattended integration /." Enschede : University of Twente [Host], 2008. http://doc.utwente.nl/58869.
Повний текст джерелаSu, Weifeng. "Domain-based data integration for Web databases /." View abstract or full-text, 2007. http://library.ust.hk/cgi/db/thesis.pl?CSED%202007%20SU.
Повний текст джерелаHaak, Liane. "Semantische Integration von Data Warehousing und Wissensmanagement /." Berlin : Dissertation.de - Verl. im Internet, 2008. http://d-nb.info/989917010/04.
Повний текст джерелаWang, Hongxia. "Data service framework for urban information integration." Thesis, University of Salford, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.490440.
Повний текст джерелаLo, Chi-lik Eric, and 盧至力. "Bridging data integration technology and e-commerce." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2003. http://hub.hku.hk/bib/B29360705.
Повний текст джерелаDIAS, SANDRA APARECIDA. "SEMANTIC DATA INTEGRATION WITH AN ONTOLOGY FEDERATION." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2006. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=9148@1.
Повний текст джерелаO advento da WEB propiciou a disseminação de bases de dados distribuídas e heterogêneas. Por vezes, a resposta a uma consulta demanda o uso de várias destas bases. É necessário, então, algum nível de integração destas. A publicação dessas bases nem sempre segue um padrão semântico. Em função disso parece ser essencial existir um meio de relacionar os diferentes dados para satisfazer tais consultas. Este processo é comumente denominado de integração de dados. A comunidade de Banco de Dados tem conhecimento de métodos para dar conta desta integração no contexto de federações de Bancos de Dados heterogêneos. No entanto, atualmente existem descrições mais ricas e com mais possibilidades de semântica, tais como aquelas induzidas pelo conceito de ontologia. A comunidade de Banco de Dados tem considerado ontologias na solução do problema da integração de Banco de Dados. O alinhamento ou merge de ontologias são algumas das propostas conhecidas da comunidade de WEB semântica. Este trabalho propõe o uso de métodos de merge de ontologias como solução ao problema da construção de uma federação de ontologias como método integrador de fontes de dados. O trabalho inclui a implementação de um estudo de caso na ferramenta Protegé. Este estudo de caso permite discutir aspectos de escalabilidade e de aplicabilidade da proposta como uma solução tecnologicamente viável.
The WEB has spread out the use of heterogeneous distributed databases. Sometimes, the answer to a query demands the use of more than one database. Some level of integration among these databases is desired. However, frequently, the bases were not designed according a unique semantic pattern. Thus, it seems essential to relate the different data, in the respective base, in order to provide an adequate answer to the query. The process of building this relationship is often called data integration. The Data Base community has acquired enough knowledge to deal with this in the context of Data Base Heterogeneous Federation. Nowadays, there are more expressive model descriptions, namely ontologies. The Data Base community has also considered ontologies as a tool to contribute as part of a solution to the data integration problem. The Semantic WEB community defined alignment or merge of ontologies as one of the possible solutions to the some of this integration problem. This work has the aim of using merge of ontologies methods as a mean to define the construction of a Federation of ontologies as a mean to integrate source of data. The dissertation includes a case study written in the Protegé tool. From this case study, a discussion follows on the scalability and applicability of the proposal as a feasible technological solution for data integration.
Шендрик, Віра Вікторівна, Вера Викторовна Шендрик, Vira Viktorivna Shendryk, A. Boiko, and Y. Mashyn. "Mechanisms of Data Integration in Information Systems." Thesis, Sumy State University, 2016. http://essuir.sumdu.edu.ua/handle/123456789/47066.
Повний текст джерелаSalazar, Gustavo A. "Integration and visualisation of data in bioinformatics." Doctoral thesis, University of Cape Town, 2015. http://hdl.handle.net/11427/16861.
Повний текст джерелаThe most recent advances in laboratory techniques aimed at observing and measuring biological processes are characterised by their ability to generate large amounts of data. The more data we gather, the greater the chance of finding clues to understand the systems of life. This, however, is only true if the methods that analyse the generated data are efficient, effective, and robust enough to overcome the challenges intrinsic to the management of big data. The computational tools designed to overcome these challenges should also take into account the requirements of current research. Science demands specialised knowledge for understanding the particularities of each study; in addition, it is seldom possible to describe a single observation without considering its relationship with other processes, entities or systems. This thesis explores two closely related fields: the integration and visualisation of biological data. We believe that these two branches of study are fundamental in the creation of scientific software tools that respond to the ever increasing needs of researchers. The distributed annotation system (DAS) is a community project that supports the integration of data from federated sources and its visualisation on web and stand-alone clients. We have extended the DAS protocol to improve its search capabilities and also to support feature annotation by the community. We have also collaborated on the implementation of MyDAS, a server to facilitate the publication of biological data following the DAS protocol, and contributed in the design of the protein DAS client called DASty. Furthermore, we have developed a tool called probeSearcher, which uses the DAS technology to facilitate the identification of microarray chips that include probes for regions on proteins of interest. Another community project in which we participated is BioJS, an open source library of visualisation components for biological data. This thesis includes a description of the project, our contributions to it and some developed components that are part of it. Finally, and most importantly, we combined several BioJS components over a modular architecture to create PINV, a web based visualiser of protein-protein interaction (PPI) networks, that takes advantage of the features of modern web technologies in order to explore PPI datasets on an almost ubiquitous platform (the web) and facilitates collaboration between scientific peers. This thesis includes a description of the design and development processes of PINV, as well as current use cases that have benefited from the tool and whose feedback has been the source of several improvements to PINV. Collectively, this thesis describes novel software tools that, by using modern web technologies, facilitates the integration, exploration and visualisation of biological data, which has the potential to contribute to our understanding of the systems of life.
Guan, Xiaowei. "Bioinformatics Approaches to Heterogeneous Omic Data Integration." Case Western Reserve University School of Graduate Studies / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=case1340302883.
Повний текст джерелаZHAN, YUNSONG. "XML-BASED DATA INTEGRATION FOR APPLICATION INTROPERABILITY." University of Cincinnati / OhioLINK, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1020432798.
Повний текст джерела