Open semantic annotation of scientific publications using DOMEO

<p>Abstract</p> <p>Background</p> <p>Our group has developed a useful shared software framework for performing, versioning, sharing and viewing Web annotations of a number of kinds, using an open representation model.</p> <p>Methods</p> <p>The Domeo Annotation Tool was developed in tandem with this open model, the Annotation Ontology (AO). Development of both the Annotation Framework and the open model was driven by requirements of several different types of alpha users, including bench scientists and biomedical curators from university research labs, online scientific communities, publishing and pharmaceutical companies.</p> <p>Several use cases were incrementally implemented by the toolkit. These use cases in biomedical communications include personal note-taking, group document annotation, semantic tagging, claim-evidence-context extraction, reagent tagging, and curation of textmining results from entity extraction algorithms.</p> <p>Results</p> <p>We report on the Domeo user interface here. Domeo has been deployed in beta release as part of the NIH Neuroscience Information Framework (NIF, <url>http://www.neuinfo.org</url><it/>) and is scheduled for production deployment in the NIF’s next full release.</p> <p>Future papers will describe other aspects of this work in detail, including Annotation Framework Services and components for integrating with external textmining services, such as the NCBO Annotator web service, and with other textmining applications using the Apache UIMA framework.</p

An open annotation ontology for science on web 3.0

Background: There is currently a gap between the rich and expressive collection of published biomedical ontologies, and the natural language expression of biomedical papers consumed on a daily basis by scientific researchers. The purpose of this paper is to provide an open, shareable structure for dynamic integration of biomedical domain ontologies with the scientific document, in the form of an Annotation Ontology (AO), thus closing this gap and enabling application of formal biomedical ontologies directly to the literature as it emerges. Methods: Initial requirements for AO were elicited by analysis of integration needs between biomedical web communities, and of needs for representing and integrating results of biomedical text mining. Analysis of strengths and weaknesses of previous efforts in this area was also performed. A series of increasingly refined annotation tools were then developed along with a metadata model in OWL, and deployed for feedback and additional requirements the ontology to users at a major pharmaceutical company and a major academic center. Further requirements and critiques of the model were also elicited through discussions with many colleagues and incorporated into the work. Results: This paper presents Annotation Ontology (AO), an open ontology in OWL-DL for annotating scientific documents on the web. AO supports both human and algorithmic content annotation. It enables "stand-off" or independent metadata anchored to specific positions in a web document by any one of several methods. In AO, the document may be annotated but is not required to be under update control of the annotator. AO contains a provenance model to support versioning, and a set model for specifying groups and containers of annotation. AO is freely available under open source license at http://purl.org/ao/, and extensive documentation including screencasts is available on AO's Google Code page: http://code.google.com/p/annotation-ontology/. Conclusions: The Annotation Ontology meets critical requirements for an open, freely shareable model in OWL, of annotation metadata created against scientific documents on the Web. We believe AO can become a very useful common model for annotation metadata on Web documents, and will enable biomedical domain ontologies to be used quite widely to annotate the scientific literature. Potential collaborators and those with new relevant use cases are invited to contact the authors

Integrative genomic analysis by interoperation of bioinformatics tools in GenomeSpace

Integrative analysis of multiple data types to address complex biomedical questions requires the use of multiple software tools in concert and remains an enormous challenge for most of the biomedical research community. Here we introduce GenomeSpace (http://www.genomespace.org), a cloud-based, cooperative community resource. Seeded as a collaboration of six of the most popular genomics analysis tools, GenomeSpace now supports the streamlined interaction of 20 bioinformatics tools and data resources. To facilitate the ability of non-programming users’ to leverage GenomeSpace in integrative analysis, it offers a growing set of ‘recipes’, short workflows involving a few tools and steps to guide investigators through high utility analysis tasks

Simulação e análise econômica da produção de epicloridrina a partir do glicerol oriundo da produção de biodiesel

A produção de biodiesel no Brasil vem crescendo continuamente desde meados dos anos 2000, a partir do estabelecimento de um percentual mínimo de adição de biodiesel ao óleo diesel. Uma consequência do crescimento da produção de biodiesel é o aumento da oferta do glicerol, o seu principal subproduto. A quantidade de glicerol excede em muito a demanda proveniente de suas aplicações tradicionais. Logo, a conversão em produtos de maior valor agregado se apresenta como grande potencial para o glicerol. Um dos possíveis produtos que se pode obter a partir do glicerol e, assim agregar valor à cadeia produtiva do biodiesel, é a epicloridrina, que é muito utilizada como matéria-prima na produção de resinas epóxi. Dessa forma, o objetivo deste trabalho é realizar uma avaliação técnico-econômica do processo de produção de epicloridrina, tendo o glicerol, oriundo da produção de biodiesel, como principal matéria-prima. O software Aspen HYSYS® v12 foi utilizado para simular o processo e os resultados obtidos foram usados, juntamente com informações da literatura, para estimar os custos de produção e avaliar a viabilidade econômica do processo. Concluiu-se que o processo de produção de epicloridrina é economicamente viável no cenário base, devido à alta efetividade e boa recuperação do catalisador no processo, pouco impacto do hidróxido de sódio no custo em matéria-prima e formação considerável de epicloridrina mesmo podendo ocorrer uma eventual degradação por hidrólise. Entretanto, apesar da viabilidade econômica, o alto consumo de água e a grande quantidade de rejeitos a serem tratados no processo requerem a busca por soluções que amenizem esses impactos ambientais resultantes do processo de produção de epicloridrinaThe production of biodiesel in Brazil has been growing continuously since the mid-2000s, from the establishment of a minimum percentage of biodiesel addition to diesel oil. A consequence of the growth in biodiesel production is the increase in the supply of glycerol, its main by-product. The amount of glycerol far exceeds the demand from its traditional applications. Therefore, the conversion into products with higher added value presents a great potential for glycerol. One of the possible products that can be obtained from glycerol and, thus add value to biodiesel production chain, is epichlorohydrin, which is widely used as a raw material in the production of epoxy resins. Thus, the objective of this work is to carry out a technical-economic evaluation of the epichlorohydrin production process, having glycerol, derived from biodiesel production, as main raw material. The Aspen HYSYS® v12 software was used to simulate the process and the results obtained were used, together with information from the literature, to estimate production costs and evaluate the economic viability of the process. It was concluded that the epichlorohydrin production process is economically viable in the base scenario, due to the high effectiveness and good recovery of the catalyst in the process, little impact of sodium hydroxide on the cost of raw materials and considerable formation of epichlorohydrin even though an eventual degradation by hydrolysis may occur. However, despite the economic viability, the high consumption of water and the high amount of waste to be treated in the process require the search for solutions that mitigate these environmental impacts resulting from the epichlorohydrin production process92 f

The SWAN biomedical discourse ontology

SWAN (Semantic Web Application in Neuromedicine) is a project to construct a semantically-organized, community-curated, distributed knowledge base of Theory, Evidence, and Discussion in biomedicine. Unlike Wikipedia and similar approaches, SWAN’s ontology is designed to represent and foreground both harmonizing and contradictory assertions within the total community discourse. Releases of the software, content and ontology will be initially by and for the Alzheimer Disease (AD) research community, with the obvious potential for extension into other disease research areas. The Alzheimer Research Forum, a 4,000-member web community for AD researchers, will host SWAN’s initial public release, currently scheduled for late 2007. This paper presents the current version of SWAN’s ontology of scientific discourse and presents our current thinking about its evolution including extensions and alignment with related communities, projects and ontologies