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Linking the Resource Description Framework to cheminformatics and proteochemometrics.

ABSTRACT: BACKGROUND: Semantic web technologies are finding their way into the life sciences. Ontologies and semantic markup have already been used for more than a decade in molecular sciences, but have not found widespread use yet. The semantic web technology Resource Description Framework (RDF) and related methods show to be sufficiently versatile to change that situation. RESULTS: The work presented here focuses on linking RDF approaches to existing molecular chemometrics fields, including cheminformatics, QSAR modeling and proteochemometrics. Applications are presented that link RDF technologies to methods from statistics and cheminformatics, including data aggregation, visualization, chemical identification, and property prediction. They demonstrate how this can be done using various existing RDF standards and cheminformatics libraries. For example, we show how IC50 and Ki values are modeled for a number of biological targets using data from the ChEMBL database. CONCLUSIONS: We have shown that existing RDF standards can suitably be integrated into existing molecular chemometrics methods. Platforms that unite these technologies, like Bioclipse, makes this even simpler and more transparent. Being able to create and share workflows that integrate data aggregation and analysis (visual and statistical) is beneficial to interoperability and reproducibility. The current work shows that RDF approaches are sufficiently powerful to support molecular chemometrics workflows.

SUBMITTER: Willighagen EL

PROVIDER: S-EPMC3105498 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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Linking the Resource Description Framework to cheminformatics and proteochemometrics.

Willighagen Egon L EL Alvarsson Jonathan J Andersson Annsofie A Eklund Martin M Lampa Samuel S Lapins Maris M Spjuth Ola O Wikberg Jarl Es JE

Journal of biomedical semantics 20110307

<h4>Background</h4>Semantic web technologies are finding their way into the life sciences. Ontologies and semantic markup have already been used for more than a decade in molecular sciences, but have not found widespread use yet. The semantic web technology Resource Description Framework (RDF) and related methods show to be sufficiently versatile to change that situation.<h4>Results</h4>The work presented here focuses on linking RDF approaches to existing molecular chemometrics fields, including ...[more]

PMID: 21388575

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Project description:PurposeWhile many examples have shown unsustainable use of freshwater resources, existing LCIA methods for water use do not comprehensively address impacts to natural resources for future generations. This framework aims to (1) define freshwater resource as an item to protect within the Area of Protection (AoP) natural resources, (2) identify relevant impact pathways affecting freshwater resources, and (3) outline methodological choices for impact characterization model development.MethodConsidering the current scope of the AoP natural resources, the complex nature of freshwater resources and its important dimensions to safeguard safe future supply, a definition of freshwater resource is proposed, including water quality aspects. In order to clearly define what is to be protected, the freshwater resource is put in perspective through the lens of the three main safeguard subjects defined by Dewulf et al. (2015). In addition, an extensive literature review identifies a wide range of possible impact pathways to freshwater resources, establishing the link between different inventory elementary flows (water consumption, emissions and land use) and their potential to cause long-term freshwater depletion or degradation.Results and discussionFreshwater as a resource has a particular status in LCA resource assessment. First, it exists in the form of three types of resources: flow, fund, or stock. Then, in addition to being a resource for human economic activities (e.g. hydropower), it is above all a non-substitutable support for life that can be affected by both consumption (source function) and pollution (sink function). Therefore, both types of elementary flows (water consumption and emissions) should be linked to a damage indicator for freshwater as a resource. Land use is also identified as a potential stressor to freshwater resources by altering runoff, infiltration and erosion processes as well as evapotranspiration. It is suggested to use the concept of recovery period to operationalize this framework: when the recovery period lasts longer than a given period of time, impacts are considered to be irreversible and fall into the concern of freshwater resources protection (i.e. affecting future generations), while short-term impacts effect the AoP ecosystem quality and human health directly. It is shown that it is relevant to include this concept in the impact assessment stage in order to discriminate the long-term from the short-term impacts, as some dynamic fate models already do.ConclusionThis framework provides a solid basis for the consistent development of future LCIA methods for freshwater resources, thereby capturing the potential long-term impacts that could warn decision makers about potential safe water supply issues in the future.

Project description:BackgroundA plethora of publicly available biomedical resources do currently exist and are constantly increasing at a fast rate. In parallel, specialized repositories are been developed, indexing numerous clinical and biomedical tools. The main drawback of such repositories is the difficulty in locating appropriate resources for a clinical or biomedical decision task, especially for non-Information Technology expert users. In parallel, although NLP research in the clinical domain has been active since the 1960s, progress in the development of NLP applications has been slow and lags behind progress in the general NLP domain. The aim of the present study is to investigate the use of semantics for biomedical resources annotation with domain specific ontologies and exploit Natural Language Processing methods in empowering the non-Information Technology expert users to efficiently search for biomedical resources using natural language.MethodsA Natural Language Processing engine which can "translate" free text into targeted queries, automatically transforming a clinical research question into a request description that contains only terms of ontologies, has been implemented. The implementation is based on information extraction techniques for text in natural language, guided by integrated ontologies. Furthermore, knowledge from robust text mining methods has been incorporated to map descriptions into suitable domain ontologies in order to ensure that the biomedical resources descriptions are domain oriented and enhance the accuracy of services discovery. The framework is freely available as a web application at ( http://calchas.ics.forth.gr/ ).ResultsFor our experiments, a range of clinical questions were established based on descriptions of clinical trials from the ClinicalTrials.gov registry as well as recommendations from clinicians. Domain experts manually identified the available tools in a tools repository which are suitable for addressing the clinical questions at hand, either individually or as a set of tools forming a computational pipeline. The results were compared with those obtained from an automated discovery of candidate biomedical tools. For the evaluation of the results, precision and recall measurements were used. Our results indicate that the proposed framework has a high precision and low recall, implying that the system returns essentially more relevant results than irrelevant.ConclusionsThere are adequate biomedical ontologies already available, sufficiency of existing NLP tools and quality of biomedical annotation systems for the implementation of a biomedical resources discovery framework, based on the semantic annotation of resources and the use on NLP techniques. The results of the present study demonstrate the clinical utility of the application of the proposed framework which aims to bridge the gap between clinical question in natural language and efficient dynamic biomedical resources discovery.

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Linking the Resource Description Framework to cheminformatics and proteochemometrics.

Publications

Linking the Resource Description Framework to cheminformatics and proteochemometrics.

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