GO faster ChEBI with Reasonable Biochemistry

Chemical Entities of Biological Interest (ChEBI) is a database and ontology that represents biochemical knowledge about small molecules. Recent changes to the ontology have created new opportunities for automated reasoning with description logic, that have not previously been fully exploited in Chemistry. These changes open up the possibility of building an improved chemical semantic web, by making more use of necessary and sufficient conditions, allowing reasoning about chemical structure, highlighting ambiguous inconsistencies and improving alignment with the Gene Ontology (GO). This paper briefly discusses some of the problems with reasoning over the current version of ChEBI, to tackle these issues, and their potential solutions

Semantic Web Representation for Phytochemical Ontology Model

Nowadays people are more health conscious; they monitor the ingredients and nutrients of what they eat. Fruits and vegetables, which are rich of phytochemicals, are always chosen as a good diet. Phytochemicals are rich of nutrients and can give health benefits to the takers. Previous research has modelled the phytochemicals into its chemical structure and colours according to group of fruits and vegetables ontologically. However, there is no semantic web representation of that ontology model that makes the information more sharable among users. Therefore, in this paper, we develop a semantic web for phytochemical ontology model by linking the user interface to ontology model using JENA framework. The data from the ontology is read by using SPARQL query to display information to the front-end user. By having this semantic web representation, it is hoped that the knowledge is more accessible and shareable among intended users

Prototype semantic infrastructure for automated small molecule classification and annotation in lipidomics

<p>Abstract</p> <p>Background</p> <p>The development of high-throughput experimentation has led to astronomical growth in biologically relevant lipids and lipid derivatives identified, screened, and deposited in numerous online databases. Unfortunately, efforts to annotate, classify, and analyze these chemical entities have largely remained in the hands of human curators using manual or semi-automated protocols, leaving many novel entities unclassified. Since chemical function is often closely linked to structure, accurate structure-based classification and annotation of chemical entities is imperative to understanding their functionality.</p> <p>Results</p> <p>As part of an exploratory study, we have investigated the utility of semantic web technologies in automated chemical classification and annotation of lipids. Our prototype framework consists of two components: an ontology and a set of federated web services that operate upon it. The formal lipid ontology we use here extends a part of the LiPrO ontology and draws on the lipid hierarchy in the LIPID MAPS database, as well as literature-derived knowledge. The federated semantic web services that operate upon this ontology are deployed within the Semantic Annotation, Discovery, and Integration (SADI) framework. Structure-based lipid classification is enacted by two core services. Firstly, a structural annotation service detects and enumerates relevant functional groups for a specified chemical structure. A second service reasons over lipid ontology class descriptions using the attributes obtained from the annotation service and identifies the appropriate lipid classification. We extend the utility of these core services by combining them with additional SADI services that retrieve associations between lipids and proteins and identify publications related to specified lipid types. We analyze the performance of SADI-enabled eicosanoid classification relative to the LIPID MAPS classification and reflect on the contribution of our integrative methodology in the context of high-throughput lipidomics.</p> <p>Conclusions</p> <p>Our prototype framework is capable of accurate automated classification of lipids and facile integration of lipid class information with additional data obtained with SADI web services. The potential of programming-free integration of external web services through the SADI framework offers an opportunity for development of powerful novel applications in lipidomics. We conclude that semantic web technologies can provide an accurate and versatile means of classification and annotation of lipids.</p

Use of Semantic Technologies - Semantic Chemistry

Our Chemical e-Science Information Cloud (ChemCloud) &#x2013; a Semantic Web based eScience infrastructure &#x2013; integrates and automates a multitude of databases, tools and services in the domain of chemistry, pharmacy and bio-chemistry available at the Fachinformationszentrum Chemie (FIZ Chemie), at the Freie Universitaet Berlin (FUB), and on the public Web. Based on the approach of the W3C Linked Open Data initiative and the W3C Semantic Web technologies for ontologies and rules it semantically links and integrates knowledge from our W3C HCLS knowledge base hosted at the FUB, our multi-domain knowledge base DBpedia (Deutschland) implemented at FUB, which is extracted from Wikipedia (De) providing a public semantic resource for chemistry, and our well-established databases at FIZ Chemie such as ChemInform for organic reaction data, InfoTherm the leading source for thermophysical data, Chemisches Zentralblatt, the complete chemistry knowledge from 1830 to 1969, and ChemgaPedia the largest and most frequented e-Learning platform for Chemistry and related sciences in German language

Chemical information matters: an e-Research perspective on information and data sharing in the chemical sciences

Recently, a number of organisations have called for open access to scientific information and especially to the data obtained from publicly funded research, among which the Royal Society report and the European Commission press release are particularly notable. It has long been accepted that building research on the foundations laid by other scientists is both effective and efficient. Regrettably, some disciplines, chemistry being one, have been slow to recognise the value of sharing and have thus been reluctant to curate their data and information in preparation for exchanging it. The very significant increases in both the volume and the complexity of the datasets produced has encouraged the expansion of e-Research, and stimulated the development of methodologies for managing, organising, and analysing "big data". We review the evolution of cheminformatics, the amalgam of chemistry, computer science, and information technology, and assess the wider e-Science and e-Research perspective. Chemical information does matter, as do matters of communicating data and collaborating with data. For chemistry, unique identifiers, structure representations, and property descriptors are essential to the activities of sharing and exchange. Open science entails the sharing of more than mere facts: for example, the publication of negative outcomes can facilitate better understanding of which synthetic routes to choose, an aspiration of the Dial-a-Molecule Grand Challenge. The protagonists of open notebook science go even further and exchange their thoughts and plans. We consider the concepts of preservation, curation, provenance, discovery, and access in the context of the research lifecycle, and then focus on the role of metadata, particularly the ontologies on which the emerging chemical Semantic Web will depend. Among our conclusions, we present our choice of the "grand challenges" for the preservation and sharing of chemical information

Representation and use of chemistry in the global electronic age.

We present an overview of the current state of public semantic chemistry and propose new approaches at a strategic and a detailed level. We show by example how a model for a Chemical Semantic Web can be constructed using machine-processed data and information from journal articles.This manuscript addresses questions of robotic access to data and its automatic re-use, including the role of Open Access archival of data. This is a pre-refereed preprint allowed by the publisher's (Royal Soc. Chemistry) Green policy. The author's preferred manuscript is an HTML hyperdocument with ca. 20 links to images, some of which are JPEgs and some of which are SVG (scalable vector graphics) including animations. There are also links to molecules in CML, for which the Jmol viewer is recommended. We susgeest that readers who wish to see the full glory of the manuscript, download the Zipped version and unpack on their machine. We also supply a PDF and DOC (Word) version which obviously cannot show the animations, but which may be the best palce to start, particularly for those more interested in the text

A community based approach for managing ontology alignments

The Semantic Web is rapidly becoming a defacto distributed repository for semantically represented data, thus leveraging on the added on value of the network effect. Various ontology mapping techniques and tools have been devised to facilitate the bridging and integration of distributed data repositories. Nevertheless, ontology mapping can benefitfrom human supervision to increase accuracy of results. The spread of Web 2.0 approaches demonstrate the possibility of using collaborative techniques for reaching consensus. While a number of prototypes for collaborative ontology construction are being developed, collaborative ontology mapping is not yet well investigated. In this paper, we describe a prototype that combines off-the-shelf ontology mapping tools with social software techniques to enable users to collaborate on mapping ontologies

Visions of a Semantic Molecular Future

Booklet handout distributed at the VSMF Symposium held at the Unilever Centre on 2011-01-17The event looks forward. Scholarship (universities, research, teaching, publishing) has been slow to take up the opportunities of this digital century. This is an opportunity to identify and build the future.EPSRC (Pathways to Impact Award). Unilever plc (Unilever Centre for Molecular Science Informatics