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      BioTCM-SE: A Semantic Search Engine for the Information Retrieval of Modern Biology and Traditional Chinese Medicine

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          Abstract

          Understanding the functional mechanisms of the complex biological system as a whole is drawing more and more attention in global health care management. Traditional Chinese Medicine (TCM), essentially different from Western Medicine (WM), is gaining increasing attention due to its emphasis on individual wellness and natural herbal medicine, which satisfies the goal of integrative medicine. However, with the explosive growth of biomedical data on the Web, biomedical researchers are now confronted with the problem of large-scale data analysis and data query. Besides that, biomedical data also has a wide coverage which usually comes from multiple heterogeneous data sources and has different taxonomies, making it hard to integrate and query the big biomedical data. Embedded with domain knowledge from different disciplines all regarding human biological systems, the heterogeneous data repositories are implicitly connected by human expert knowledge. Traditional search engines cannot provide accurate and comprehensive search results for the semantically associated knowledge since they only support keywords-based searches. In this paper, we present BioTCM-SE, a semantic search engine for the information retrieval of modern biology and TCM, which provides biologists with a comprehensive and accurate associated knowledge query platform to greatly facilitate the implicit knowledge discovery between WM and TCM.

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            Bio2RDF: towards a mashup to build bioinformatics knowledge systems.

            Presently, there are numerous bioinformatics databases available on different websites. Although RDF was proposed as a standard format for the web, these databases are still available in various formats. With the increasing popularity of the semantic web technologies and the ever growing number of databases in bioinformatics, there is a pressing need to develop mashup systems to help the process of bioinformatics knowledge integration. Bio2RDF is such a system, built from rdfizer programs written in JSP, the Sesame open source triplestore technology and an OWL ontology. With Bio2RDF, documents from public bioinformatics databases such as Kegg, PDB, MGI, HGNC and several of NCBI's databases can now be made available in RDF format through a unique URL in the form of http://bio2rdf.org/namespace:id. The Bio2RDF project has successfully applied the semantic web technology to publicly available databases by creating a knowledge space of RDF documents linked together with normalized URIs and sharing a common ontology. Bio2RDF is based on a three-step approach to build mashups of bioinformatics data. The present article details this new approach and illustrates the building of a mashup used to explore the implication of four transcription factor genes in Parkinson's disease. The Bio2RDF repository can be queried at http://bio2rdf.org.
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              Significance of interleukin-6 (IL-6) in breast cancer (review).

              Cytokines are factors that are known to have both tumor-promoting and inhibitory effects on breast cancer growth depending presumably on their relative concentrations and the presence of other modulating factors. Different cytokines play an important role in controlling the immune system. Interleukin-6 (IL-6) is a pleiotropic cytokine with obviously tumor-promoting and tumor-inhibitory effects. Here, we review the role of IL-6 in in vitro experiments of breast tumor cells, in breast tumor tissues (BTs) and assess its potential as a prognostic indicator in breast cancer patients. A literature search was conducted using PubMed, restricted to articles published in English language. In summary, results regarding the effect of IL-6 on breast tumor cells and on BTs are not unique indicating both tumor-promoting and inhibitory effects of IL-6. Concerning patients' serum IL-6 levels, data are surprisingly unique showing IL-6 to be a negative prognosticator in breast tumor patients.
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                Author and article information

                Journal
                Comput Math Methods Med
                Comput Math Methods Med
                CMMM
                Computational and Mathematical Methods in Medicine
                Hindawi Publishing Corporation
                1748-670X
                1748-6718
                2014
                12 March 2014
                : 2014
                : 957231
                Affiliations
                College of Computer Science, Zhejiang University, Hangzhou 310027, China
                Author notes

                Academic Editor: Dejing Dou

                Article
                10.1155/2014/957231
                3989774
                24772189
                7ee28bea-5c9d-4701-a152-1126db654de7
                Copyright © 2014 Xi Chen et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 23 August 2013
                : 25 November 2013
                Categories
                Research Article

                Applied mathematics
                Applied mathematics

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