125,867 research outputs found

    West-Life: A Virtual Research Environment for structural biology

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    The West-Life project (https://about.west-life.eu/)is a Horizon 2020 project funded by the European Commission to provide data processing and data management services for the international community of structural biologists, and in particular to support integrative experimental approaches within the field of structural biology. It has developed enhancements to existing web services for structure solution and analysis, created new pipelines to link these services into more complex higher-level workflows, and added new data management facilities. Through this work it has striven to make the benefits of European e-Infrastructures more accessible to life-science researchers in general and structural biologists in particular

    Envisioning the future of aquatic animal tracking: Technology, science, and application

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    Electronic tags are significantly improving our understanding of aquatic animal behavior and are emerging as key sources of information for conservation and management practices. Future aquatic integrative biology and ecology studies will increasingly rely on data from electronic tagging. Continued advances in tracking hardware and software are needed to provide the knowledge required by managers and policymakers to address the challenges posed by the world's changing aquatic ecosystems. We foresee multiplatform tracking systems for simultaneously monitoring the position, activity, and physiology of animals and the environment through which they are moving. Improved data collection will be accompanied by greater data accessibility and analytical tools for processing data, enabled by new infrastructure and cyberinfrastructure. To operationalize advances and facilitate integration into policy, there must be parallel developments in the accessibility of education and training, as well as solutions to key governance and legal issues

    Ontology-assisted database integration to support natural language processing and biomedical data-mining

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    Successful biomedical data mining and information extraction require a complete picture of biological phenomena such as genes, biological processes, and diseases; as these exist on different levels of granularity. To realize this goal, several freely available heterogeneous databases as well as proprietary structured datasets have to be integrated into a single global customizable scheme. We will present a tool to integrate different biological data sources by mapping them to a proprietary biomedical ontology that has been developed for the purposes of making computers understand medical natural language

    Systems biology in animal sciences

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    Systems biology is a rapidly expanding field of research and is applied in a number of biological disciplines. In animal sciences, omics approaches are increasingly used, yielding vast amounts of data, but systems biology approaches to extract understanding from these data of biological processes and animal traits are not yet frequently used. This paper aims to explain what systems biology is and which areas of animal sciences could benefit from systems biology approaches. Systems biology aims to understand whole biological systems working as a unit, rather than investigating their individual components. Therefore, systems biology can be considered a holistic approach, as opposed to reductionism. The recently developed ‘omics’ technologies enable biological sciences to characterize the molecular components of life with ever increasing speed, yielding vast amounts of data. However, biological functions do not follow from the simple addition of the properties of system components, but rather arise from the dynamic interactions of these components. Systems biology combines statistics, bioinformatics and mathematical modeling to integrate and analyze large amounts of data in order to extract a better understanding of the biology from these huge data sets and to predict the behavior of biological systems. A ‘system’ approach and mathematical modeling in biological sciences are not new in itself, as they were used in biochemistry, physiology and genetics long before the name systems biology was coined. However, the present combination of mass biological data and of computational and modeling tools is unprecedented and truly represents a major paradigm shift in biology. Significant advances have been made using systems biology approaches, especially in the field of bacterial and eukaryotic cells and in human medicine. Similarly, progress is being made with ‘system approaches’ in animal sciences, providing exciting opportunities to predict and modulate animal traits

    An integrated systems biology approach to the study of preterm birth using "-omic" technology - a guideline for research

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    Preterm birth is the leading cause of neonatal mortality and perinatal morbidity. The etiology of preterm is multi-factorial and still unclear. As evidence increases for a genetic contribution to PTB, so does the need to explore genomics, transcriptomics, proteomics and metabolomics in its study. This review suggests research guidelines for the conduct of high throughput systems biology investigations into preterm birth with the expectation that this will facilitate the sharing of samples and data internationally through consortia, generating the power needed to study preterm birth using integrated "-omics" technologies. The issues to be addressed include: (1) integrated "-omics" approaches, (2) phenotyping, (3) sample collection, (4) data management-integrative databases, (5) international consortia and (6) translational feasibility. This manuscript is the product of discussions initiated by the "-Omics" Working Group at the Preterm Birth International Collaborative Meeting held at the World Health Organization, Geneva, Switzerland in April 2009

    In Silico Approaches and the Role of Ontologies in Aging Research

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    The 2013 Rostock Symposium on Systems Biology and Bioinformatics in Aging Research was again dedicated to dissecting the aging process using in silico means. A particular focus was on ontologies, as these are a key technology to systematically integrate heterogeneous information about the aging process. Related topics were databases and data integration. Other talks tackled modeling issues and applications, the latter including talks focussed on marker development and cellular stress as well as on diseases, in particular on diseases of kidney and skin

    BacillOndex: An Integrated Data Resource for Systems and Synthetic Biology

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    BacillOndex is an extension of the Ondex data integration system, providing a semantically annotated, integrated knowledge base for the model Gram-positive bacterium Bacillus subtilis. This application allows a user to mine a variety of B. subtilis data sources, and analyse the resulting integrated dataset, which contains data about genes, gene products and their interactions. The data can be analysed either manually, by browsing using Ondex, or computationally via a Web services interface. We describe the process of creating a BacillOndex instance, and describe the use of the system for the analysis of single nucleotide polymorphisms in B. subtilis Marburg. The Marburg strain is the progenitor of the widely-used laboratory strain B. subtilis 168. We identified 27 SNPs with predictable phenotypic effects, including genetic traits for known phenotypes. We conclude that BacillOndex is a valuable tool for the systems-level investigation of, and hypothesis generation about, this important biotechnology workhorse. Such understanding contributes to our ability to construct synthetic genetic circuits in this organism
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