This project describes DRG (Dynamic Report Generator). This program can be used on the internet to summarize the content of a database based on user criteria. DRG allows the user to choose a database, input the data, and generate a report based on user input, and print out the results in a new format. This paper describes the design and analysis of the DRG program.

The purpose of this project is to provide faculty and students a secure access to graduate student resources and it will also cover database design, web development, security, migration, and deployment of the new system.

Whenever one designs a new database system, an Entity-Relationship Diagram (ER diagram) is always needed to present the structure of this database. Using the graphically well-arranged ER Diagram helps you to easily understand the entities, attributes, domains, primary keys, foreign keys, constraints, and relationships inside a database. This data-modeling tool is an ideal choice for companies and developers.

This document describes the design and implementation of a tool which allows for evaluation and visualisation of statistical data gathered from users of the AVG Admin Console application. The document describes collected statistical data including their localization and storing all the data in the database is discussed. The application was tested on real statistical data and possible improvements based on the results are proposed.

In modern IT landscapes, databases are subject to a major role change. Especially in Service-Oriented Architectures, databases are more and more frequently dedicated to a single application. Therefore, it is even more important to reflect the application requirements in their design. Software developers and application experts formulate application requirements in software models. Hence, we obviously need to bridge the gap to the software world and directly derive a database design from the software models used in application development and maintenance. We introduce this concept as model-driven database design. In this paper, we present the architecture principles of a model-driven database design tool and details on the enumeration and evaluation of logical database designs.

No description available.

Entity Relationship (ER) diagrams are among the most popular formalisms for the support of database design [7, 12, 17, 6]. Their classical use in the (usually computer aided) database design process can roughly be described as follows: after evaluating the requirements of the application, the database designer constructs an ER schema, which represents the conceptual model of the new database. CASE tools can be used to automatically transform the ER schema into a relational database schema, which is then manually fine-tuned. During the last years, the initially rather simple ER formalisms has been extended by various means of expressivity to account for new, more complex application areas such as schema integration for data warehouses [12, 3, 13]. Designing a conceptual model with such enriched ER diagrams is a nontrivial task: there exist complex interactions between the various means of expressivity, which quite often result in unnoticed inconsistencies in the ER schemas and in implicit ramifications of the modeling that have not been intended by the designer. To address this problem, Description Logics (DLs) have been proposed and succesfully used as a tool for reasoning about ER diagrams and thereby detecting the aforementioned anomalies [5, 6, 8].

Mycoplasma pneumoniae, einer der kleinsten lebenden Organismen, ist ein erfolgversprechender Modellorganismus der Systembiologie um eine komplette lebende Zelle zu verstehen. Wichtig dahingehend ist die Konstruktion mathematischer Modelle, die zelluläre Prozesse beschreiben, indem sie beteiligte Komponenten vernetzen und zugrundeliegende Mechanismen entschlüsseln. Für Mycoplasma pneumoniae wurden genomweite Datensätze für Genomics, Transcriptomics, Proteomics und Metabolomics produziert. Allerdings fehlten ein effizientes Informationsaustauschsystem und mathematische Modelle zur Datenintegration. Zudem waren verschiedene Beobachtungen im metabolischen Verhalten ungeklärt. Diese Dissertation präsentiert einen kombinatorischen Ansatz zur Entwicklung eines metabolischen Modells für Mycoplasma pneumoniae. Zuerst haben wir eine Datenbank, MyMpn, entwickelt, um Zugang zu strukturierten, organisierten Daten zu schaffen. Danach haben wir ein genomweites, Constraint-basiertes metabolisches Modell mit Vorhersagekapazitäten konstruiert und parallel dazu das Metabolome experimentell charakterisiert. Wir haben die Biomasse einer Mycoplasma pneumoniae Zelle definiert, das Netzwerk korrigiert, gezeigt, dass ein Grossteil der produzierten Energie auf zelluläre Homeostase verwendet wird, und das Verhalten unter verschiedenen Wachstumsbedingungen analysiert. Schließlich haben wir manuell das Genom reannotiert. Die Datenbank, obwohl noch nicht öffentlich zugänglich, wird bereits intern für die Analyse experimenteller Daten und die Modellierung genutzt. Die Entdeckung von Kontrollprinzipien des Energiemetabolismus und der Anpassungsfähigkeiten bei Genausfall heben den Einfluss der reduktiven Genomevolution hervor und erleichtert die Entwicklung von Manipulationstechniken und dynamischen Modellen. Überdies haben wir gezeigt, dass die Genomorganisation in Mycoplasma pneumoniae komplexer ist als bisher für möglich gehalten, und 32 neue, noch nicht annotierte Gene entdeckt. / Mycoplasma pneumoniae, one of the smallest known self-replicating organisms, is a promising model organism in systems biology when aiming to assess understanding of an entire living cell. One key step towards this goal is the design of mathematical models that describe cellular processes by connecting the involved components to unravel underlying mechanisms. For Mycoplasma pneumoniae, a wealth of genome-wide datasets on genomics, transcriptomics, proteomics, and metabolism had been produced. However, a proper system facilitating information exchange and mathematical models to integrate the different datasets were lacking. Also, different in vivo observations of metabolic behavior remained unexplained. This thesis presents a combinatorial approach to design a metabolic model for Mycoplasma pneumoniae. First, we developed a database, MyMpn, in order to provide access to structured and organized data. Second, we built a predictive, genome-scale, constraint-based metabolic model and, in parallel, we explored the metabolome in vivo. We defined the biomass composition of a Mycoplasma pneumoniae cell, corrected the wiring diagram, showed that a large proportion of energy is dedicated to cellular homeostasis, and analyzed the metabolic behavior under different growth conditions. Finally, we manually re-annotated the genome of Mycoplasma pneumoniae. The database, despite not yet being released to the public, is internally already used for data analysis, and for mathematical modeling. Unraveling the principles governing energy metabolism and adaptive capabilities upon gene deletion highlight the impact of the reductive genome evolution and facilitates the development of engineering tools and dynamic models for metabolic sub-systems. Furthermore, we revealed that the degree of complexity in which the genome of Mycoplasma pneumoniae is organized far exceeds what has been considered possible so far and we identified 32 new, previously not annotated genes.

The purpose of this study is to design a database of resources for rational therapy. An investigation of the current health situation and reorientation towards primary health care (PHC) in South Africa evidenced the need for a database of resources which would meet the demand for rational therapy information made on the Helderberg College Library by various user groups as well as make a contribution to the national health information infrastructure. Rational therapy is viewed as an approach within PHC that is rational, common-sense, wholistic and credible, focusing on the prevention and maintenance of health. A model of the steps in database design was developed. A user study identified users' requirements for design and the conceptual schema was developed. The entities, attributes, relationships and policies were presented and graphically summarised in an Entity-Relationship (E-R) diagram. The conceptual schema is the blueprint for further design and implementation of the database. / Information Science / M.Inf.

<p>Stress responsive genes play a key role in shaping the manner in which plants process and respond to environmental stress. Their gene products are linked to DNA transcription and its consequent translation into a response product. However, whilst these genes play a significant role in manufacturing responses to stressful stimuli, transcription factors coordinate access to these genes, specifically by accessing a gene&rsquo / s promoter region which houses transcription factor binding sites. Here transcriptional elements play a key role in mediating responses to environmental stress where each transcription factor binding site may constitute a potential response to a stress signal. Arabidopsis thaliana, a model organism, can be used to identify the mechanism of how transcription factors shape a plant&rsquo / s survival in a stressful environment. Whilst there are numerous plant stress research groups, globally there is a shortage of publicly available stress responsive gene databases. In addition a number of previous databases such as the Generation Challenge Programme&rsquo / s comparative plant stressresponsive gene catalogue, Stresslink and DRASTIC have become defunct whilst others have stagnated. There is currently a single Arabidopsis thaliana stress response database called STIFDB which was launched in 2008 and only covers abiotic stresses as handled by major abiotic stress responsive transcription factor families. Its data was sourced from microarray expression databases, contains numerous omissions as well as numerous erroneous entries and has not been updated since its inception.The Dragon Arabidopsis Stress Transcription Factor database (DASTF) was developed in response to the current lack of stress response gene resources. A total of 2333 entries were downloaded from SWISSPROT, manually curated and imported into DASTF. The entries represent 424 transcription factor families. Each entry has a corresponding SWISSPROT, ENTREZ GENBANK and TAIR accession number. The 5&rsquo / untranslated regions (UTR) of 417 families were scanned against TRANSFAC&rsquo / s binding site catalogue to identify binding sites. The relational database consists of two tables, namely a transcription factor table and a transcription factor family table called DASTF_TF and TF_Family respectively. Using a two-tier client-server architecture, a webserver was built with PHP, APACHE and MYSQL and the data was loaded into these tables with a PYTHON script. The DASTF database contains 60 entries which correspond to biotic stress and 167 correspond to abiotic stress while 2106 respond to biotic and/or abiotic stress. Users can search the database using text, family, chromosome and stress type search options. Online tools have been integrated into the DASTF&nbsp / database, such as HMMER, CLUSTALW, BLAST and HYDROCALCULATOR. User&rsquo / s can upload sequences to identify which transcription factor family their sequences belong to by using HMMER. The website can be accessed at http://apps.sanbi.ac.za/dastf/ and two updates per year are envisaged.</p>