Biomedical subjects

C A Goble

Publications and source records attributed to C A Goble.

12 recordsLinked to original sources

PubMed2003

Investigating semantic similarity measures across the Gene Ontology: the relationship between sequence and annotation.

MOTIVATION: Many bioinformatics data resources not only hold data in the form of sequences, but also as annotation. In the majority of cases, annotation is written as scientific natural language: this is suitable for humans, but not particularly useful for machine processing. Ontologies offer a mechanism by which knowledge can be represented in a form capable of such processing. In this paper we investigate the use of ontological annotation to measure the similarities in knowledge content or 'semantic similarity' between entries in a data resource. These allow a bioinformatician to perform a similarity measure over annotation in an analogous manner to those performed over sequences. A measure of semantic similarity for the knowledge component of bioinformatics resources should afford a biologist a new tool in their repertoire of analyses. RESULTS: We present the results from experiments that investigate the validity of using semantic similarity by comparison with sequence similarity. We show a simple extension that enables a semantic search of the knowledge held within sequence databases. AVAILABILITY: Software available from http://www.russet.org.uk.

Artificial Intelligence↗

PubMed2003

Semantic similarity measures as tools for exploring the gene ontology.

Many bioinformatics resources hold data in the form of sequences. Often this sequence data is associated with a large amount of annotation. In many cases this data has been hard to model, and has been represented as scientific natural language, which is not readily computationally amenable. The development of the Gene Ontology provides us with a more accessible representation of some of this data. However it is not clear how this data can best be searched, or queried. Recently we have adapted information content based measures for use with the Gene Ontology (GO). In this paper we present detailed investigation of the properties of these measures, and examine various properties of GO, which may have implications for its future design.

Classification↗

PubMed2003

A methodology to migrate the gene ontology to a description logic environment using DAML+OIL.

The Gene Ontology Next Generation Project (GONG) is developing a staged methodology to evolve the current representation of the Gene Ontology into DAML+OIL in order to take advantage of the richer formal expressiveness and the reasoning capabilities of the underlying description logic. Each stage provides a step level increase in formal explicit semantic content with a view to supporting validation, extension and multiple classification of the Gene Ontology. The paper introduces DAML+OIL and demonstrates the activity within each stage of the methodology and the functionality gained.

Classification↗

PubMed2000

Ontology-based knowledge representation for bioinformatics.

Much of biology works by applying prior knowledge ('what is known') to an unknown entity, rather than the application of a set of axioms that will elicit knowledge. In addition, the complex biological data stored in bioinformatics databases often require the addition of knowledge to specify and constrain the values held in that database. One way of capturing knowledge within bioinformatics applications and databases is the use of ontologies. An ontology is the concrete form of a conceptualisation of a community's knowledge of a domain. This paper aims to introduce the reader to the use of ontologies within bioinformatics. A description of the type of knowledge held in an ontology will be given.The paper will be illustrated throughout with examples taken from bioinformatics and molecular biology, and a survey of current biological ontologies will be presented. From this it will be seen that the use to which the ontology is put largely determines the content of the ontology. Finally, the paper will describe the process of building an ontology, introducing the reader to the techniques and methods currently in use and the open research questions in ontology development.

Artificial Intelligence↗

PubMed2000

TAMBIS: transparent access to multiple bioinformatics information sources.

UNLABELLED: TAMBIS (Transparent Access to Multiple Bioinformatics Information Sources) is an application that allows biologists to ask rich and complex questions over a range of bioinformatics resources. It is based on a model of the knowledge of the concepts and their relationships in molecular biology and bioinformatics. AVAILABILITY: TAMBIS is available as an applet from http://img.cs.man.ac.uk/tambis SUPPLEMENTARY: A full manual, tutorial and videos can be found at http://img.cs.man.ac.uk/tambis. CONTACT: tambis@cs.man.ac.uk

Computational Biology↗

PubMed2000

Conceptual modelling of genomic information.

MOTIVATION: Genome sequencing projects are making available complete records of the genetic make-up of organisms. These core data sets are themselves complex, and present challenges to those who seek to store, analyse and present the information. However, in addition to the sequence data, high throughput experiments are making available distinctive new data sets on protein interactions, the phenotypic consequences of gene deletions, and on the transcriptome, proteome, and metabolome. The effective description and management of such data is of considerable importance to bioinformatics in the post-genomic era. The provision of clear and intuitive models of complex information is surprisingly challenging, and this paper presents conceptual models for a range of important emerging information resources in bioinformatics. It is hoped that these can be of benefit to bioinformaticians as they attempt to integrate genetic and phenotypic data with that from genomic sequences, in order to both assign gene functions and elucidate the different pathways of gene action and interaction. RESULTS: This paper presents a collection of conceptual (i.e. implementation-independent) data models for genomic data. These conceptual models are amenable to (more or less direct) implementation on different computing platforms.

Computational Biology↗

PubMed1999

An ontology for bioinformatics applications.

MOTIVATION: An ontology of biological terminology provides a model of biological concepts that can be used to form a semantic framework for many data storage, retrieval and analysis tasks. Such a semantic framework could be used to underpin a range of important bioinformatics tasks, such as the querying of heterogeneous bioinformatics sources or the systematic annotation of experimental results. RESULTS: This paper provides an overview of an ontology [the Transparent Access to Multiple Biological Information Sources (TAMBIS) ontology or TaO] that describes a wide range of bioinformatics concepts. The present paper describes the mechanisms used for delivering the ontology and discusses the ontology's design and organization, which are crucial for maintaining the coherence of a large collection of concepts and their relationships. AVAILABILITY: The TAMBIS system, which uses a subset of the TaO described here, is accessible over the Web via http://img.cs.man.ac.uk/tambis (although in the first instance, we will use a password mechanism to limit the load on our server). The complete model is also available on the Web at the above URL.

Animals↗

PubMed1997

The GRAIL concept modelling language for medical terminology.

The GALEN representation and integration language (GRAIL) has been developed to support effective clinical user interfaces and extensible re-usable models of medical terminology. It has been used successfully to develop the prototype GALEN common reference (CORE) model for medical terminology and for a series of projects in clinical user interfaces within the GALEN and PEN&PAD projects. GRAIL is a description logic or frame language with novel features to support part-whole and other transitive relations and to support the GALEN modelling style aimed at re-use and application independence. GRAIL began as an experimental language. However, it has clarified many requirements for an effective knowledge representation language for clinical concepts. It still has numerous limitations despite its practical successes. The GRAIL experience is expected to form the basis for future languages which meet the same requirements but have greater expressiveness and more soundly based semantics. This paper provides a description and motivation for the GRAIL language and gives examples of the modelling paradigm which it supports.

Artificial Intelligence↗

PubMed1994

Expression of human amyloid precursor proteins in cultured neuronal cells through the use of HSV-1 defective vectors.

Postmortem investigations of Alzheimer's patients reveal senile plaques that contain, among other molecules, deposits of beta-amyloid protein. The role of the beta-amyloid deposits remains unclear but identification of mutations in the amyloid precursor protein (APP) gene within the beta-amyloid portion in hereditary forms of the disease provide evidence that these deposits are involved in the pathological state. To more fully investigate this hypothesis attempts have been made to create transgenic mice to overexpress the beta-amyloid protein but these models have not been successful in modeling the disease. We have chosen to utilize the HSV-1 defective vector system which allows the expression of experimental genes in neuronal cells to overexpress APPC100. We have cloned the rat tyrosine hydroxylase (TH) promoter into a defective HSV plasmid. Cloning the firefly luciferase gene under the control of the TH promoter (demonstrates that the promoter is active after infection of human SY5Y cells or rat PC12 cells. A synthetic APP cDNA which represents the last 100 amino acids of the carboxy terminus of APP including the beta-amyloid protein was synthesized and inserted under the control of the TH promoter. Infection and subsequent nuclease protection assays demonstrate expression of the synthetic gene in the infected cells. Current research focuses on detection of the expressed protein within the infected cells and determination of the time period for continued expression.

Amyloid↗

PubMed1993

Mechanism of glucocorticoid induction of the rat plasminogen activator inhibitor-1 gene in HTC rat hepatoma cells: identification of cis-acting regulatory elements.

Type 1 plasminogen activator inhibitor (PAI-1) is the major physiological inhibitor of plasminogen activation, inhibiting both tissue- and urokinase-type plasminogen activators. In HTC rat hepatoma cells, glucocorticoids increase PAI-1 activity, antigen and mRNA accumulation 3- to 5-fold; this increase is due solely to an increase in the rate of PAI-1 gene transcription. We have identified the cis-acting sequences in the 5'-flanking sequence of the HTC PAI-1 gene that mediate this induction. Analysis of a series of hybrid genes containing various portions of the PAI-1 5'-flanking region fused to the chloramphenicol acetyltransferase reporter gene transfected into HTC cells localized the region involved in the transcriptional regulation by glucocorticoids to between -1237 and -764. Electrophoretic mobility shift assays and DNase-I protection assays showed that a glucocorticoid response element (GRE) 15-mer located at -1212 bound the glucocorticoid receptor DNA-binding domain protein in a concentration-dependent manner. Mutations created within this GRE eliminated its ability both to confer a glucocorticoid response and to bind the glucocorticoid receptor. When placed upstream of a heterologous promoter in either orientation, this GRE conferred glucocorticoid inducibility. We, therefore, conclude that the sole cis-acting sequence required for the glucocorticoid response of the PAI-1 gene in rat HTC hepatoma cells is the GRE at -1212.

Animals↗

PubMed1993

A framework for modelling the electronic medical record.

This paper presents a model for an electronic medical record which satisfies the requirements for a faithful and structured record of patient care set out in a previous paper in this series. The model underlies the PEN & PAD clinical workstation, and it provides for a permanent, completely attributable record of patient care and the process of medical decision making. The model separates the record into two levels: direct observations of the patient and meta-statements about the use of observations in decision making and the clinical dialogue. The model is presented in terms of "descriptions" formulated in the Structured Meta Knowledge (SMK) formalism, but many of its features are more general than the specific implementation. The use of electronic medical records based on the model for decision support and the analysis of aggregated data are discussed along with potential use of the model in distributed information systems.

Computer Simulation↗

PubMed1989

Macromolecular organization of human centromeric regions reveals high-frequency, polymorphic macro DNA repeats.

To analyze the macromolecular organization of human centromeric regions, we used alpha-satellite, or alphoid, repetitive DNA sequences specific to the centromeres of human chromosomes 6 (D6Z1), X (XC), and Y (YC-2) and the technique of pulsed-field gel electrophoresis. Genomic DNA from 24 normal, unrelated individuals was digested and separated into fragments ranging from 23 kilobases (kb) to 2 megabases (Mb) in length. Digestion with 12 different restriction enzymes with 4- to 8-base-pair recognition sequences and hybridization with alphoid sequences revealed chromosome-specific hybridization patterns. Similarities in the organization of the centromeric regions of the three chromosomes included NotI, SfiI, and SalI fragments of greater than 2 Mb and Sau3A1 and Alu I fragments of less than 150 kb. Each restriction enzyme with a 6-base-pair recognition sequence (Ava II, BamHI, HindIII, Hpa I, Pst I, Sal I, Sst I, and Xba I) detected polymorphic DNA fragments of 50 kb to 2 Mb. Forty percent or more of the individuals screened revealed a unique hybridization pattern with these enzymes and at least one of the three chromosome-specific alphoid probes. Five individuals differed from one another in hybridization pattern for each of the three enzymes HindIII, HpaI, and SstI and for each of the three centromeric probes. All 24 individuals could be distinguished on the basis of unique hybridization patterns with only two enzymes and one chromosome-specific alphoid probe. Family studies showed that these polymorphisms are inherited. The high frequency of these macro restriction fragment length polymorphisms illustrates the high degree of variability of the centromeric region among normal individuals and demonstrates its usefulness for DNA fingerprinting and pericentromeric mapping by linkage analysis.

Centromere↗