Database technologies for l-system simulations in virtual plant applications on bioinformatics

One of the most important advantages of database systems is that the underlying mathematics is rich enough to specify very complex operations with a small number of statements in the database language. This research covers an aspect of biological informatics that is the marriage of information technology and biology, involving the study of real-world phenomena using virtual plants derived from L-systems simulation. L-systems were introduced by Aristid Lindenmayer as a mathematical model of multicellular organisms. Not much consideration has been given to the problem of persistent storage for these simulations. Current procedures for querying data generated by L-systems for scientific experiments, simulations and measurements are also inadequate. To address these problems the research in this paper presents a generic process for data-modeling tools (L-DBM) between L-systems and database systems. This paper shows how L-system productions can be generically and automatically represented in database schemas and how a database can be populated from the L-system strings. This paper further describes the idea of pre-computing recursive structures in the data into derived attributes using compiler generation. A method to allow a correspondence between biologists' terms and compiler-generated terms in a biologist computing environment is supplied. Once the L-DBM gets any specific L-systems productions and its declarations, it can generate the specific schema for both simple correspondence terminology and also complex recursive structure data attributes and relationships.

Approaches and Strategy for Cancer Research and Surveillance Data: Integration, Information Pipeline, Data Models, and Informatics Opportunities

Thesis (Ph.D.)--University of Washington, 2016-04

Cross-species and cross-platform gene expression studies with the Bioconductor-compliant R package 'annotationTools'.

Background: The variety of DNA microarray formats and datasets presently available offers an unprecedented opportunity to perform insightful comparisons of heterogeneous data. Cross-species studies, in particular, have the power of identifying conserved, functionally important molecular processes. Validation of discoveries can now often be performed in readily available public data which frequently requires cross-platform studies.Cross-platform and cross-species analyses require matching probes on different microarray formats. This can be achieved using the information in microarray annotations and additional molecular biology databases, such as orthology databases. Although annotations and other biological information are stored using modern database models ( e. g. relational), they are very often distributed and shared as tables in text files, i.e. flat file databases. This common flat database format thus provides a simple and robust solution to flexibly integrate various sources of information and a basis for the combined analysis of heterogeneous gene expression profiles.Results: We provide annotationTools, a Bioconductor-compliant R package to annotate microarray experiments and integrate heterogeneous gene expression profiles using annotation and other molecular biology information available as flat file databases. First, annotationTools contains a specialized set of functions for mining this widely used database format in a systematic manner. It thus offers a straightforward solution for annotating microarray experiments. Second, building on these basic functions and relying on the combination of information from several databases, it provides tools to easily perform cross-species analyses of gene expression data.Here, we present two example applications of annotationTools that are of direct relevance for the analysis of heterogeneous gene expression profiles, namely a cross-platform mapping of probes and a cross-species mapping of orthologous probes using different orthology databases. We also show how to perform an explorative comparison of disease-related transcriptional changes in human patients and in a genetic mouse model.Conclusion: The R package annotationTools provides a simple solution to handle microarray annotation and orthology tables, as well as other flat molecular biology databases. Thereby, it allows easy integration and analysis of heterogeneous microarray experiments across different technological platforms or species.

Multimodal Investment Analysis Methodology, Phase One: The Conceptual Model, 1998

The purpose of this project is to develop an investment analysis model that integrates the capabilities of four types of analysis for use in evaluating interurban transportation system improvements. The project will also explore the use of new data warehousing and mining techniques to design the types of databases required for supporting such a comprehensive transportation model. The project consists of four phases. The first phase, which is documented in this report, involves development of the conceptual foundation for the model. Prior research is reviewed in Chapter 1, which is composed of three major sections providing demand modeling background information for passenger transportation, transportation of freight (manufactured products and supplies), and transportation of natural resources and agricultural commodities. Material from the literature on geographic information systems makes up Chapter 2. Database models for the national and regional economies and for the transportation and logistics network are conceptualized in Chapter 3. Demand forecasting of transportation service requirements is introduced in Chapter 4, with separate sections for passenger transportation, freight transportation, and transportation of natural resources and commodities. Characteristics and capacities of the different modes, modal choices, and route assignments are discussed in Chapter 5. Chapter 6 concludes with a general discussion of the economic impacts and feedback of multimodal transportation activities and facilities.

Oliorelaatiotietokannan käyttö energianhallintajärjestelmässä

Empower Oy on energia-alan palveluja tarjoava yritys. Energianhallintajärjestelmää käytetään energiatietojen hallintaan ja ylläpitoon sekä tietojen esittämiseen loppukäyttäjille. Palvelun näytöt ja raportit on toteutettu web-pohjaisen käyttöliittymän kautta. Yhtiössä käynnistyi suurprojekti vanhan energianhallintajärjestelmän korvaamiseksi. Vanha järjestelmä otettiin käyttöön vuonna 1995 ja EMS-projekti käynnistettiin vuonna 2001. Diplomityö tehtiin osana EMS-projektia ja työn tavoitteina oli selvittää perusjärjestelmän käyttämän tietokantaratkaisun toimivuutta ja soveltuvuutta tehtävään sekä tutkailla eri tietokantamalleja teoreettisesti. Lisäksi työhön kuului erillisten haku- ja muutoskomponenttien ja rajapintojen toteuttaminen. Näiden avulla voidaan hakea ja muuttaa tietoa perusjärjestelmän pohjalla toimivasta oliorelaatiotietokannasta. Perusjärjestelmän DOR-tietokannaksi (Domain Object Repository) kutsuttu kokonaisuus on olioläheinen tietovarasto, josta tietoa haetaan ilmoittamalla haettavan olion tyyppi ja siihen liitoksissa olevat tyypit. Hakutulokseen mukaan haluttavat ominaisuudet ilmoitetaan kultakin tyypiltä erikseen. Haettaessa ja muutettaessa oliopohjaista DOR-tietoa, tulee noudattaa järjestelmän käyttämiä tietomalleja. Haku- ja muutoskomponentit toteutettiin Microsoftin kehittämällä .NET-teknologialla. Tietokantamallien teoreettinen tarkastelu auttoi ymmärtämään järjestelmän pohjalla toimivaa tietokantaratkaisua. Työssä selvisi, että perusjärjestelmän hyödyntämä oliorelaatiotietokanta soveltuu varsin hyvin tarkoitukseensa. Haku- ja muutoskomponenttien toteutus onnistui ja ne toimivat helppokäyttöisenä rajapintana energianhallintajärjestelmän tietokantaan.

A semantic paradigm for intelligent data access

An implementation of Sem-ODB—a database management system based on the Semantic Binary Model is presented. A metaschema of Sem-ODB database as well as the top-level architecture of the database engine is defined. A new benchmarking technique is proposed which allows databases built on different database models to compete fairly. This technique is applied to show that Sem-ODB has excellent efficiency comparing to a relational database on a certain class of database applications. A new semantic benchmark is designed which allows evaluation of the performance of the features characteristic of semantic database applications. An application used in the benchmark represents a class of problems requiring databases with sparse data, complex inheritances and many-to-many relations. Such databases can be naturally accommodated by semantic model. A fixed predefined implementation is not enforced allowing the database designer to choose the most efficient structures available in the DBMS tested. The results of the benchmark are analyzed. ^ A new high-level querying model for semantic databases is defined. It is proven adequate to serve as an efficient native semantic database interface, and has several advantages over the existing interfaces. It is optimizable and parallelizable, supports the definition of semantic userviews and the interoperability of semantic databases with other data sources such as World Wide Web, relational, and object-oriented databases. The query is structured as a semantic database schema graph with interlinking conditionals. The query result is a mini-database, accessible in the same way as the original database. The paradigm supports and utilizes the rich semantics and inherent ergonomics of semantic databases. ^ The analysis and high-level design of a system that exploits the superiority of the Semantic Database Model to other data models in expressive power and ease of use to allow uniform access to heterogeneous data sources such as semantic databases, relational databases, web sites, ASCII files, and others via a common query interface is presented. The Sem-ODB engine is used to control all the data sources combined under a unified semantic schema. A particular application of the system to provide an ODBC interface to the WWW as a data source is discussed. ^

Partial automation of database processing of simulation outputs from L-systems models of plant morphogenesis

Models of plant architecture allow us to explore how genotype environment interactions effect the development of plant phenotypes. Such models generate masses of data organised in complex hierarchies. This paper presents a generic system for creating and automatically populating a relational database from data generated by the widely used L-system approach to modelling plant morphogenesis. Techniques from compiler technology are applied to generate attributes (new fields) in the database, to simplify query development for the recursively-structured branching relationship. Use of biological terminology in an interactive query builder contributes towards making the system biologist-friendly. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.

PK/DB: database for pharmacokinetic properties and predictive in silico ADME models

The study of pharmacokinetic properties (PK) is of great importance in drug discovery and development. In the present work, PK/DB (a new freely available database for PK) was designed with the aim of creating robust databases for pharmacokinetic studies and in silico absorption, distribution, metabolism and excretion (ADME) prediction. Comprehensive, web-based and easy to access, PK/DB manages 1203 compounds which represent 2973 pharmacokinetic measurements, including five models for in silico ADME prediction (human intestinal absorption, human oral bioavailability, plasma protein binding, bloodbrain barrier and water solubility).

Web-based access to mouse models of human cancers: the Mouse Tumor Biology (MTB) Database

The Mouse Tumor Biology (MTB) Database serves as a curated, integrated resource for information about tumor genetics and pathology in genetically defined strains of mice (i.e., inbred, transgenic and targeted mutation strains). Sources of information for the database include the published scientific literature and direct data submissions by the scientific community. Researchers access MTB using Web-based query forms and can use the database to answer such questions as ‘What tumors have been reported in transgenic mice created on a C57BL/6J background?’, ‘What tumors in mice are associated with mutations in the Trp53 gene?’ and ‘What pathology images are available for tumors of the mammary gland regardless of genetic background?’. MTB has been available on the Web since 1998 from the Mouse Genome Informatics web site (http://www.informatics.jax.org). We have recently implemented a number of enhancements to MTB including new query options, redesigned query forms and results pages for pathology and genetic data, and the addition of an electronic data submission and annotation tool for pathology data.

AgroDB - integration of database management systems with crop models.

2016

Virtual models of the HLA class I antigen processing pathway

Antigen recognition by cytotoxic CD8 T cells is dependent upon a number of critical steps in MHC class I antigen processing including proteosomal cleavage, TAP transport into the endoplasmic reticulum, and MHC class 1 binding. Based on extensive experimental data relating to each of these steps there is now the capacity to model individual antigen processing steps with a high degree of accuracy. This paper demonstrates the potential to bring together models of individual antigen processing steps, for example proteosome cleavage, TAP transport, and MHC binding, to build highly informative models of functional pathways. In particular, we demonstrate how an artificial neural network model of TAP transport was used to mine a HLA-binding database so as to identify H LA-binding peptides transported by TAP. This integrated model of antigen processing provided the unique insight that HLA class I alleles apparently constitute two separate classes: those that are TAP-efficient for peptide loading (HLA-B27, -A3, and -A24) and those that are TAP-inefficient (HLA-A2, -B7, and -B8). Hence, using this integrated model we were able to generate novel hypotheses regarding antigen processing, and these hypotheses are now capable of being tested experimentally. This model confirms the feasibility of constructing a virtual immune system, whereby each additional step in antigen processing is incorporated into a single modular model. Accurate models of antigen processing have implications for the study of basic immunology as well as for the design of peptide-based vaccines and other immunotherapies. (C) 2004 Elsevier Inc. All rights reserved.