Common Ontology Research Articles

Abstract 2214: An integrative approach to reveal driver gene fusions from paired end sequencing data in cancer

Abstract With a flood of cancer genome sequences expected soon, distinguishing ‘driver’ from ‘passenger’ mutations will be an important task. To discover the key characteristics of driver gene fusions in cancer, we performed a systematic analysis of known fusion genes using a compendium of ‘molecular concepts', inclusive of functional domains, pathways, gene ontologies and molecular interactions. Although analysis of domain architectures and shared pathways was less informative, we found that cancer-related fusion genes tend to share common gene ontologies or engage distinct interaction networks. We hypothesized that such ‘signatures’ of molecular concepts may be used to distinguish biologically meaningful gene fusions underlying cancer, similar to signature genes defining certain phenotypes. We therefore designed an algorithm, called concept signature score (ConSig score), to quantitatively rank human genes underlying cancer by the strength of their association with the molecular concepts characteristics of cancer genes. To integrate the use of high-throughput genomic data, we characterized the chromosomal imbalances associated with gene fusions, finding that recurrent gene fusions exhibit distinctive patterns of copy number alteration corresponding to differential portions of fusion partners. We named this pattern as the fusion breakpoint principle, and confirmed this principle by large-scale meta-analysis of recurrent gene fusions using high-resolution array CGH/SNP datasets. Next, we applied the ConSig technology to paired-end transcriptome sequencing data to benchmark fusion candidates, which were then assessed for chromosomal aberrations complying with the fusion breakpoint principle by integrating high-quality copy number data. We found that the ConSig score was able to identify the known EML4-ALK fusion as the top-ranked candidate in the H2228 lung cancer cell line, and, in addition, we found further evidence of a R3HDM2-NFE2 fusion in H1792 cell line. We show that the R3HDM2-NFE2 fusion, which results in overexpression of wild-type NFE2, promotes cell proliferation and invasion. Moreover, through analysis of SNP arrays and lung TMAs, we find that chromosomal rearrangements at the NFE2 locus are recurrent in a small subset of patient tumors, suggesting that NFE2 may contribute to a new class of lung cancer molecular biology. Together, the ConSig technology suggests the functional importance of putative fusions in cancer, whereas the breakpoint principle helps interpret large-scale cancer genomic data sets to explore potential recurrence. Thus the methodology described here can filter the large number of fusion candidates generated by paired-end sequencing data and preferentially identify driver gene fusions in cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2214.

The Teleost Anatomy Ontology: Anatomical Representation for the Genomics Age

The rich knowledge of morphological variation among organisms reported in the systematic literature has remained in free-text format, impractical for use in large-scale synthetic phylogenetic work. This noncomputable format has also precluded linkage to the large knowledgebase of genomic, genetic, developmental, and phenotype data in model organism databases. We have undertaken an effort to prototype a curated, ontology-based evolutionary morphology database that maps to these genetic databases (http://kb.phenoscape.org) to facilitate investigation into the mechanistic basis and evolution of phenotypic diversity. Among the first requirements in establishing this database was the development of a multispecies anatomy ontology with the goal of capturing anatomical data in a systematic and computable manner. An ontology is a formal representation of a set of concepts with defined relationships between those concepts. Multispecies anatomy ontologies in particular are an efficient way to represent the diversity of morphological structures in a clade of organisms, but they present challenges in their development relative to single-species anatomy ontologies. Here, we describe the Teleost Anatomy Ontology (TAO), a multispecies anatomy ontology for teleost fishes derived from the Zebrafish Anatomical Ontology (ZFA) for the purpose of annotating varying morphological features across species. To facilitate interoperability with other anatomy ontologies, TAO uses the Common Anatomy Reference Ontology as a template for its upper level nodes, and TAO and ZFA are synchronized, with zebrafish terms specified as subtypes of teleost terms. We found that the details of ontology architecture have ramifications for querying, and we present general challenges in developing a multispecies anatomy ontology, including refinement of definitions, taxon-specific relationships among terms, and representation of taxonomically variable developmental pathways.

The Unified Enterprise Modelling Language—Overview and further work

The Unified Enterprise Modelling Language (UEML) aims at supporting integrated use of enterprise and IS models expressed using different languages. To achieve this aim, UEML offers a hub through which modelling languages can be connected, thereby paving the way for also connecting the models expressed in those languages. This paper motivates and presents the most central parts of the UEML approach: a structured path to describing enterprise and IS modelling constructs; a common ontology to interrelate construct descriptions at the semantic level; a correspondence analysis approach to estimate semantic construct similarity; a quality framework to aid selection of languages; a meta-meta model to integrate the different parts of the approach; and a set of tools to aid its use and evolution. The paper also discusses the benefits of UEML and points to paths for further work.

MINER: exploratory analysis of gene interaction networks by machine learning from expression data

BackgroundThe reconstruction of gene regulatory networks from high-throughput "omics" data has become a major goal in the modelling of living systems. Numerous approaches have been proposed, most of which attempt only "one-shot" reconstruction of the whole network with no intervention from the user, or offer only simple correlation analysis to infer gene dependencies.ResultsWe have developed MINER (Microarray Interactive Network Exploration and Representation), an application that combines multivariate non-linear tree learning of individual gene regulatory dependencies, visualisation of these dependencies as both trees and networks, and representation of known biological relationships based on common Gene Ontology annotations. MINER allows biologists to explore the dependencies influencing the expression of individual genes in a gene expression data set in the form of decision, model or regression trees, using their domain knowledge to guide the exploration and formulate hypotheses. Multiple trees can then be summarised in the form of a gene network diagram. MINER is being adopted by several of our collaborators and has already led to the discovery of a new significant regulatory relationship with subsequent experimental validation.ConclusionUnlike most gene regulatory network inference methods, MINER allows the user to start from genes of interest and build the network gene-by-gene, incorporating domain expertise in the process. This approach has been used successfully with RNA microarray data but is applicable to other quantitative data produced by high-throughput technologies such as proteomics and "next generation" DNA sequencing.

The materialization of religious structures in the time of stonehenge

ABSTRACTBoth ritual and religion share a common ontology, in that they are materialized through practice—they are technologies of the body and material world as much as of the mind and immaterial. Acknowledging such offers considerable prospect for archaeology, inasmuch as it implies that the generation, reproduction, and transformation of religion will be worked through and given dimension by material forms that are recoverable. The latter might include the construction of shrines, temples, and other architectural foci for veneration and spirit communication, attendant practices of deposition, and ceremony itself as embodied within architectural forms. Working through details of architectural form, cosmology, materiality, and the sequence of monument construction in the Stonehenge region of Wiltshire, this paper provides an interpretation of the history of religious practice during the later Neolithic (c.3000–2300 bc) of central southern England.

Analogical model formulation for transfer learning in AP Physics

Transfer learning is the ability to apply previously learned knowledge to new problems or domains. In qualitative reasoning, model formulation is the process of moving from the unruly, broad set of concepts used in everyday life to a concise, formal vocabulary of abstractions, assumptions, causal relationships, and models that support problem-solving. Approaching transfer learning from a model formulation perspective, we found that analogy with examples can be used to learn how to solve AP Physics style problems. We call this process analogical model formulation and implement it in the Companion cognitive architecture. A Companion begins with some basic mathematical skills, a broad common sense ontology, and some qualitative mechanics, but no equations. The Companion uses worked solutions, explanations of example problems at the level of detail appearing in textbooks, to learn what equations are relevant, how to use them, and the assumptions necessary to solve physics problems. We present an experiment, conducted by the Educational Testing Service, demonstrating that analogical model formulation enables a Companion to learn to solve AP Physics style problems. Across six different variations of relationships between base and target problems, or transfer levels, a Companion exhibited a 63% improvement in initial performance. While already a significant result, we describe an in-depth analysis of this experiment to pinpoint the causes of failures. Interestingly, the sources of failures were primarily due to errors in the externally generated problem and worked solution representations as well as some domain-specific problem-solving strategies, not analogical model formulation. To verify this, we describe a second experiment which was performed after fixing these problems. In this second experiment, a Companion achieved a 95.8% improvement in initial performance due to transfer, which is nearly perfect. We know of no other problem-solving experiments which demonstrate performance of analogical learning over systematic variations of relationships between problems at this scale.

GLOBAL CONSERVATION OF STRAWBERRIES: A STRATEGY IS FORMED

Strawberry was listed in the International Treaty on Plant Genetic Resources, Annex 1, as a crop of global horticultural significance. The Global Crop Diversity Trust and Bioversity International requested that a global conservation strategy be developed for strawberry. A coordinator was appointed and an international expert committee meeting was held July 5 to 8, 2006, at the US Department of Agriculture, Agricultural Research Service, National Clonal Germplasm Repository, Corvallis, Oregon. A questionnaire about strawberry holdings was sent to 537 international strawberry contacts. Responses were received from 37 locations in 27 countries. More than 12,000 accessions of species and cultivated strawberries are maintained at respondent locations. Roughly half of the accessions represent advanced breeding lines of the cultivated hybrid strawberry, F. ×ananassa. Six major genebanks (US, Canada, Russian Federation, Chile, Germany, and Spain) of the 20 genebanks respondents had collections of 500 accessions or more. Private corporations maintain >15,000 proprietary strawberries for internal use that are unavailable for distribution. Primary collections at national genebanks consist of living plants protected in containers in greenhouses, screenhouses, tube structures, or planted in fields. Secondary backup collections are maintained in vitro under refrigeration. Long-term backup collections of meristems are placed in cryogenic storage at remote locations to provide decades of security. Species diversity is represented by seedlots stored in -18°C or backed-up in cryogenics. The committee recommended that the capacity building of two genebanks be supported in Asia and South America. Limited resources are constraining genebanks from sufficient personnel, pathogen-free plants, secure backup, adequate facilities, and equipment. The committee also recommended that a granting system to improve facilities for and health of accessible genebank strawberries, funding for training of genebank staff in standard protocols, and coordination of characterization data using a common ontology and a web-accessible inventory should also be supported.

BFO/DOLCE Primitive Relation Comparison

AbstractThis paper examines the primitive relations (dependence, quality, and constitution) of the BFO and DOLCE upper ontologies, employed in developing domain ontologies of the biomedical sciences. The strengths in both upper ontologies are examined, which sets a framework for developing a common upper ontology that utilizes the assets of both.

BFO/DOLCE Primitive Relation Comparison

This paper examines the primitive relations (dependence, quality, and constitution) of the BFO and DOLCE upper ontologies, employed in developing domain ontologies of the biomedical sciences. The strengths in both upper ontologies are examined, which sets a framework for developing a common upper ontology that utilizes the assets of both.

Defining assessment projects and scenarios for policy support: Use of ontology in Integrated Assessment and Modelling

Integrated Assessment and Modelling (IAM) provides an interdisciplinary approach to support ex-ante decision-making by combining quantitative models representing different systems and scales into a framework for integrated assessment. Scenarios in IAM are developed in the interaction between scientists and stakeholders to explore possible pathways of future development. As IAM typically combines models from different disciplines, there is a clear need for a consistent definition and implementation of scenarios across models, policy problems and scales. This paper presents such a unified conceptualization for scenario and assessment projects. We demonstrate the use of common ontologies in building this unified conceptualization, e.g. a common ontology on assessment projects and scenarios. The common ontology and the process of ontology engineering are used in a case study, which refers to the development of SEAMLESS-IF, an integrated modelling framework to assess agricultural and environmental policy options as to their contribution to sustainable development. The presented common ontology on assessment projects and scenarios can be reused by IAM consortia and if required, adapted by using the process of ontology engineering as proposed in this paper.

3.1.1 Defining an Integration Readiness Level for Defense Acquisition

AbstractThere is a tremendous need to analyze system interoperability within Defense for both government and industry. Part of this challenge is the need for a metric that can be used as a common ontology and assess the state of interoperability in system's development and acquisition. Previous research developments have created an Integration Readiness Level (IRL) that complements the well‐established Technology Readiness Level (TRL) of the Department of Defense. This paper expands upon this work with the objective of presenting a verified and validated IRL and supporting guide of critical maturation criteria. We will review the foundations of this IRL, describe our development of a “guide” to support the IRLs, present the results of a survey to assess the criticality of decision criteria in the “guide,” and conclude with a discussion of the results and their implications to defense acquisition.

Mechanisms for assessing and enhancing organisations’ readiness for collaboration in collaborative networks

Collaborative networks are an increasing trend in highly competitive globalised economies, where collaboration is essential to succeed. Some specific challenges in collaborative networks, either for a virtual breeding environment (VBE) or a virtual organisation (VO), are in the first instance, to support the VBE members’ integration process to the source network in order to establish: cooperation agreements, common operation principles, common interoperable infrastructures, common ontologies, and mutual trust towards guaranteeing that potential VO partners within the VBE are ready in advance to participate in dynamic coalitions and collaborative endeavours. In the second instance, the VO partners’ selection process faces the challenge of matching a particular collaboration opportunity with specific competency requirements available in a set of potential VO partners. This paper presents a readiness for collaboration assessment and enhancing approach aiming at identifying critical evaluation elements referred to as readiness for collaboration assessments in order to determine if a potential VBE member has the needed elements to collaborate and participate in a collaborative network such as a VBE or a VO. In case it lacks these elements, the approach will provide enhancing mechanisms to improve its readiness level for collaboration towards increasing both its chances and preparedness towards collaboration in potential VOs.

FuGEFlow: data model and markup language for flow cytometry

BackgroundFlow cytometry technology is widely used in both health care and research. The rapid expansion of flow cytometry applications has outpaced the development of data storage and analysis tools. Collaborative efforts being taken to eliminate this gap include building common vocabularies and ontologies, designing generic data models, and defining data exchange formats. The Minimum Information about a Flow Cytometry Experiment (MIFlowCyt) standard was recently adopted by the International Society for Advancement of Cytometry. This standard guides researchers on the information that should be included in peer reviewed publications, but it is insufficient for data exchange and integration between computational systems. The Functional Genomics Experiment (FuGE) formalizes common aspects of comprehensive and high throughput experiments across different biological technologies. We have extended FuGE object model to accommodate flow cytometry data and metadata.MethodsWe used the MagicDraw modelling tool to design a UML model (Flow-OM) according to the FuGE extension guidelines and the AndroMDA toolkit to transform the model to a markup language (Flow-ML). We mapped each MIFlowCyt term to either an existing FuGE class or to a new FuGEFlow class. The development environment was validated by comparing the official FuGE XSD to the schema we generated from the FuGE object model using our configuration. After the Flow-OM model was completed, the final version of the Flow-ML was generated and validated against an example MIFlowCyt compliant experiment description.ResultsThe extension of FuGE for flow cytometry has resulted in a generic FuGE-compliant data model (FuGEFlow), which accommodates and links together all information required by MIFlowCyt. The FuGEFlow model can be used to build software and databases using FuGE software toolkits to facilitate automated exchange and manipulation of potentially large flow cytometry experimental data sets. Additional project documentation, including reusable design patterns and a guide for setting up a development environment, was contributed back to the FuGE project.ConclusionWe have shown that an extension of FuGE can be used to transform minimum information requirements in natural language to markup language in XML. Extending FuGE required significant effort, but in our experiences the benefits outweighed the costs. The FuGEFlow is expected to play a central role in describing flow cytometry experiments and ultimately facilitating data exchange including public flow cytometry repositories currently under development.

EuroPhysiome, the Virtual Physiological Human toolkit, VPH Exemplar Projects, and the Renal Physiome

European Physiome activity is currently funded under the 7th Framework Program VPH call (Virtual Physiological Human), which supports more than a dozen targeted projects and also one Network of Excellence (NoE), whose mission is to coordinate these efforts, explore training possibilities, disseminate information about VPH resources and projects, and furnish a VPH ToolKit. I briefly summarize this activity and then focus on progress in the Renal Physiome, which is linked to the VPH NoE through the SAPHIR Exemplar Project treating blood pressure regulation in a Guyton‐inspired modular modeling environment. The Renal Physiome includes: (1) the Quantitative Kidney DataBase (QKDB) of experimental measurements and anatomical details, (2) links to other disciplines (incl. high‐throughput data) through common ontologies (e.g., FMA, GO...), (3) a library for models of channels and transporters expressed along the nephron, and (4) a repository of legacy models of kidney physiology at various scales (tubule transport, tubuloglomerular feedback, medullary models addressing the problem of urine concentration, etc.), with internet access through a KidneyGrid Portal (in collaboration with Univ. Melbourne).

V-Vagueness, Realism, Language and Thought

The problem of vagueness and the sorites paradox arise because we try to treat natural language as if it were a unitary formal system. In fact, natural language contains a large variety of representational ontologies that serve different purposes and which cannot be united formally, but which can intuitively be taken as ways of seeing a common basic ontology. Using this framework, we can save classical logic from vagueness and avoid the sorites.

Semantic business process integration based on ontology alignment

Innovation and agility should be provided to businesses by efficient collaboration (i.e., communication and sharing) between them. However, semantic heterogeneity between business processes is a serious problem for automatically supporting cooperation processes (e.g., knowledge sharing and querying-based interactions) between businesses. In order to overcome this problem, we propose a novel framework based on aligning business ontologies for integrating heterogeneous business processes. We can consider two types of alignment processes; (i) manual alignment for building a whole business process ontology in a business process management (BPM) system and (ii) automated alignment between business processes of different BPM systems. Thereby, the optimal integration between two business processes has to be discovered to maximize the summation of a set of partial similarities between semantic components consisting of the business processes. In particular, the semantic component are extracted from semantic annotations of business processes. For evaluating the proposed system, we have conducted experimentations by using 22 business process management systems, which are organized as six business alliances. We have assumed that business processes in a same BPM system should be built with a common ontologies. The proposed alignment method has shown about 71.3% of precision (65.4% of recall). In addition, we found out that alignment results are dependent on some characteristics of ontologies (e.g., depth and number of classes).

SIMO: An adaptable simulation framework for multiscale forest resource data

Forest management planning is facing new objectives and diversified data sources. To succeed in the new context, a forest management planning framework should support integration of the new goals, knowledge, and technology as well as embrace multiple scales. The aim of the SIMO framework is to develop a hierarchical, extendable simulation and optimization framework for forest management planning. Current implementation includes a forest growth and yield simulator which is adaptable with respect to the components of a simulation; data, growth and operation models that modify the data, and the control structures between the data and the models. The simulation framework components implemented in XML include the hierarchical structures for data and simulation descriptions, and an extendable model base. To achieve flexibility and reusability, the components are connected through a common ontology, again defined in XML. The article includes two use cases demonstrating the adaptability of the simulation framework, which is available as open source software.

Ontology-driven codification for discrete and modular products

Efficient codification system for companies with wide assortments of products makes it possible for customers to easily navigate among the products and eventually ensures good corporate look for the company. The paper represents an approach to building such a codification system and its implementation. The codification system is based on a common ontology containing family-based product classification used in the company's Product Data Management (PDM) and Enterprise Resource Planning (ERP) systems. The codes are based on product families and additional product characteristics described via attributes in the ontology. This approach makes it possible to have similar codes for similar products and vice versa. Another important advantage of the approach is that the common ontology is easily expandable what is demonstrated in the 'Possible Future Work' section. Besides solving their primary tasks the extensions will be tightly connected to the codification system, and consequently, with the company's PDM and ERP systems.

ImmunoGrid, an integrative environment for large-scale simulation of the immune system for vaccine discovery, design and optimization

Vaccine research is a combinatorial science requiring computational analysis of vaccine components, formulations and optimization. We have developed a framework that combines computational tools for the study of immune function and vaccine development. This framework, named ImmunoGrid combines conceptual models of the immune system, models of antigen processing and presentation, system-level models of the immune system, Grid computing, and database technology to facilitate discovery, formulation and optimization of vaccines. ImmunoGrid modules share common conceptual models and ontologies. The ImmunoGrid portal offers access to educational simulators where previously defined cases can be displayed, and to research simulators that allow the development of new, or tuning of existing, computational models. The portal is accessible at <igrid-ext.cryst.bbk.ac.uk/immunogrid>.

FOAFing the music: Bridging the semantic gap in music recommendation

In this paper we give an overview of the Foafing the Music system. The system uses the Friend of a Friend (FOAF) and RDF Site Summary (RSS) vocabularies for recommending music to a user, depending on the user’s musical tastes and listening habits. Music information (new album releases and reviews, podcast sessions, audio from MP3 blogs, related artists’ news, and upcoming gigs) is gathered from thousands of RSS feeds. The presented system provides music discovery by means of: user profiling (defined in the user’s FOAF description), context-based information (extracted from music related RSS feeds) and content-based descriptions (extracted from the audio itself), based on a common ontology (OWL DL) that describes the music recommendation domain. The system is available at: http://foafing-the-music.iua.upf.edu.