46 research outputs found

    Computational analysis of a candidate region for psychosis

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    Genetic analysis of a candidate region for psychiatric illness on chromosone 4p

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    Psychiatric illnesses are debilitating conditions for those affected and place a significant burden on the National Health Service, the social services and the family. Here I describe genetic analysis, physical mapping and transcript mapping of a region of chromosome 4p that is linked to psychiatric illness, including bipolar and unipolar affective disorders and schizophrenia.I have studied four families that show linkage of psychiatric illness to chromosome 4p. Linkage was first observed in a large family, F22, segregating bipolar affective disorder (BPAD) and recurrent major depression (RMD). Subsequently, a smaller family, F59, segregating affective disorders (Blackwood et al, 1996a), and two families (F50 & F48) segregating schizophrenia (SCZ), schizoaffective disorder and BPAD confirmed this linkage.Previously, comparison of the haplotypes inherited with illness in each family allowed prioritisation of two sub-regions for detailed study. Minimal Region One (MR1) is defined by overlap of the disease chromosomes from three Celtic families (F22, F59 & F50). Minimal Region Two (MR2) is defined by the two largest families F22 and F48, as well as F50. The sequence available from the human genome sequencing project for these two regions is largely complete. Here, I describe an extension to the BAC map in the repetitive telomeric end of MR1. The telomeric end of MR1 is defined by a recombination event in an individual from F50. I mapped clones, designed markers and refined the position of the recombination breakpoint. I also refined the position of the recombination breakpoint at the centromeric end of MR1, as defined by a member of F59.I describe construction of a transcript map of MR land 2 using bioinformatics methods, RT-PCR and cDNA library screening. I then selected two candidate genes from this region: orphan g-protein-coupled receptor 78 (GPR78) and superoxide dismutase 3 (SOD3), for further study. Firstly, I identified SNPs in the genes from the linked families, and then carried out a preliminary association study on 95 SCZ in patients, 93 BPAD patients 95 controls. The linkage disequilibrium (LD) between the markers was measured and, using a low stringency significant p-value cut off, revealed a positive association in GPR78. SNPs were then tested on a larger population for association. This work adds to the case for studying the role of chromosome 4 in the genetic susceptibility to affective disorder

    BIRCH: A user-oriented, locally-customizable, bioinformatics system

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    BACKGROUND: Molecular biologists need sophisticated analytical tools which often demand extensive computational resources. While finding, installing, and using these tools can be challenging, pipelining data from one program to the next is particularly awkward, especially when using web-based programs. At the same time, system administrators tasked with maintaining these tools do not always appreciate the needs of research biologists. RESULTS: BIRCH (Biological Research Computing Hierarchy) is an organizational framework for delivering bioinformatics resources to a user group, scaling from a single lab to a large institution. The BIRCH core distribution includes many popular bioinformatics programs, unified within the GDE (Genetic Data Environment) graphic interface. Of equal importance, BIRCH provides the system administrator with tools that simplify the job of managing a multiuser bioinformatics system across different platforms and operating systems. These include tools for integrating locally-installed programs and databases into BIRCH, and for customizing the local BIRCH system to meet the needs of the user base. BIRCH can also act as a front end to provide a unified view of already-existing collections of bioinformatics software. Documentation for the BIRCH and locally-added programs is merged in a hierarchical set of web pages. In addition to manual pages for individual programs, BIRCH tutorials employ step by step examples, with screen shots and sample files, to illustrate both the important theoretical and practical considerations behind complex analytical tasks. CONCLUSION: BIRCH provides a versatile organizational framework for managing software and databases, and making these accessible to a user base. Because of its network-centric design, BIRCH makes it possible for any user to do any task from anywhere

    Genome visualisation and user studies in biologist-computer interaction

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    We surveyed a number of genome visualisation tools used in biomedical research. We recognised that none of the tools shows all the relevant data geneticists who look for candidate disease genes would like to see. The biological researchers we collaborate with would like to view integrated data from a variety of sources and be able to see both data overviews and details. In response to this need, we developed a new visualisation tool, VisGenome, which allows the users to add their own data or data downloaded from other sources, such as Ensembl. VisGenome visualises single and comparative representations of the rat, the mouse, and the human chromosomes, and can easily be used for other genomes. In the context of VisGenome development we made the following research contributions. We developed a new algorithm (CartoonPlus) which allows the users to see different kinds of data in cartoon scaling depending on a selected basis. Also, two user studies were conducted: an initial quantitative user study and a mixed paradigm user study. The first study showed that neither Ensembl nor VisGenome fulfil all user requirements and can be regarded as user-friendly, as the users make a significant number of mistakes during data navigation. To help users navigate their data easily, we improved existing visualisation techniques in VisGenome and added a new technique CartoonPlus. To verify if this solution was useful, we conducted a second user study. We saw that the users became more familiar with the tool, and found new ways to use the application on its own and in connection with other tools. They frequently used CartoonPlus, which allowed them to see small regions of their data in a way that was not possible before

    SEMEDA (Semantic Meta-Database) : ontology based semantic integration of biological databases

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    Köhler J. SEMEDA (Semantic Meta-Database) : ontology based semantic integration of biological databases. Bielefeld (Germany): Bielefeld University; 2003.The work presented in this thesis is outlined in the following. The state of the art in the relevant disciplines is introduced and reviewed in chapter 2. This includes on the one hand the current state of molecular biological databases, their heterogeneity and the integration of molecular biological databases. On the other hand the current usage of ontologies in general and with special regard to database integration is described. The principles of semantic database integration as introduced in this thesis are new and suitable to be used also in other database integration systems, which have to deal with a high number of semantically heterogeneous databases. Therefore in Chapter 3 the newly introduced principles for ontology based semantic database integration are presented independent of their implementation. Chapter 4 introduces the requirements for the implementation of a semantic database integration system (SEMEDA). Several general requirements for the integration of molecular biological systems from the scientific literature are discussed with regard to the feasibility of their implementation in general and in SEMEDA. In addition, the requirements specific to semantic database integration are introduced. In addition how the BioDataServer is used to overcome "technical" heterogeneity, so that SEMEDA only has to deal with semantic heterogeneity is analysed. In chapter 5, an appropriate data structure for storing ontologies, database metadata and the semantic definitions as described in Chapter 3 is developed. Subsequently, it is discussed how this data structure can be edited and queried. In Chapter 6, SEMEDAs software design, implementation and system architecture is given. Chapter 7 describes the use of SEMEDA and its interfaces. The user interface SEMEDA-edit is used to collaboratively edit ontologies and to semantically define databases using ontologies. SEMEDA-query is the query interface that provides uniform access to heterogeneous databases. In addition, a set of procedures exists which can be used by external applications. In order to use SEMEDA to semantically define databases, an appropriate ontology is needed. Although SEMEDA allows building ontologies from the scratch, due to the fact that generating ontologies is a labour intensive time-consuming task, it would be preferable to use an existing ontology. Therefore, in chapter 8 several ontologies were evaluated for their usability in SEMEDA. The intention was to find out if a suitable ontology can be found and imported or whether it is more appropriate to build a custom ontology for SEMEDA. It turned out that the existing ontologies were not well suited for semantic database integration. In chapter 9 general and SEMEDA specific ontology design principles are introduced which were then followed to build a custom ontology for database integration. The structure of this custom ontology and some issues concerning its use for semantic database integration are explained. In chapter 10, the practical use of SEMEDA is described by two examples. The first section of this chapter shows how SEMEDA supports the building of user schemata for the BioDataServer. The second section describes how the clone database of the RZPD Berlin (Deutsches Ressourcenzentrum fĂŒr Genomforschung GmbH) is connected to SEMEDA and thus linked to the other databases. In the discussion (chapter 11) SEMEDA is compared to existing database integration systems, especially other ontology based integration systems. It is further discussed how principles for semantic database integration apply to other database integration systems and how they might be implemented there. A database mirror is proposed to improve the overall performance of SEMEDA and the BioDataServer

    A cooperative framework for molecular biology database integration using image object selection

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    The theme and the concept of 'Molecular Biology Database Integration' and the problems associated with this concept initiated the idea for this Ph.D research. The available technologies facilitate to analyse the data independently and discretely but it fails to integrate the data resources for more meaningful information. This along with the integration issues created the scope for this Ph.D research. The research has reviewed the 'database interoperability' problems and it has suggested a framework for integrating the molecular biology databases. The framework has proposed to develop a cooperative environment to share information on the basis of common purpose for the molecular biology databases. The research has also reviewed other implementation and interoperability issues for laboratory based, dedicated and target specific database. The research has addressed the following issues: diversity of molecular biology databases schemas, schema constructs and schema implementation multi-database query using image object keying, database integration technologies using context graph, automated navigation among these databases. This thesis has introduced a new approach for database implementation. It has introduced an interoperable component database concept to initiate multidatabase query on gene mutation data. A number of data models have been proposed for gene mutation data which is the basis for integrating the target specific component database to be integrated with the federated information system. The proposed data models are: data models for genetic trait analysis, classification of gene mutation data, pathological lesion data and laboratory data. The main feature of this component database is non-overlapping attributes and it will follow non-redundant integration approach as explained in the thesis. This will be achieved by storing attributes which will not have the union or intersection of any attributes that exist in public domain molecular biology databases. Unlike data warehousing technique, this feature is quite unique and novel. The component database will be integrated with other biological data sources for sharing information in a cooperative environment. This involves developing new tools. The thesis explains the role of these new tools which are: meta data extractor, mapping linker, query generator and result interpreter. These tools are used for a transparent integration without creating any global schema of the participating databases. The thesis has also established the concept of image object keying for multidatabase query and it has proposed a relevant algorithm for matching protein spot in gel electrophoresis image. An object spot in gel electrophoresis image will initiate the query when it is selected by the user. It matches the selected spot with other similar spots in other resource databases. This image object keying method is an alternative to conventional multidatabase query which requires writing complex SQL scripts. This method also resolve the semantic conflicts that exist among molecular biology databases. The research has proposed a new framework based on the context of the web data for interactions with different biological data resources. A formal description of the resource context is described in the thesis. The implementation of the context into Resource Document Framework (RDF) will be able to increase the interoperability by providing the description of the resources and the navigation plan for accessing the web based databases. A higher level construct is developed (has, provide and access) to implement the context into RDF for web interactions. The interactions within the resources are achieved by utilising an integration domain to extract the required information with a single instance and without writing any query scripts. The integration domain allows to navigate and to execute the query plan within the resource databases. An extractor module collects elements from different target webs and unify them as a whole object in a single page. The proposed framework is tested to find specific information e.g., information on Alzheimer's disease, from public domain biology resources, such as, Protein Data Bank, Genome Data Bank, Online Mendalian Inheritance in Man and local database. Finally, the thesis proposes further propositions and plans for future work
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