Towards Semantic e-Science for Traditional Chinese Medicine

<p>Abstract</p> <p>Background</p> <p>Recent advances in Web and information technologies with the increasing decentralization of organizational structures have resulted in massive amounts of information resources and domain-specific services in Traditional Chinese Medicine. The massive volume and diversity of information and services available have made it difficult to achieve seamless and interoperable e-Science for knowledge-intensive disciplines like TCM. Therefore, information integration and service coordination are two major challenges in e-Science for TCM. We still lack sophisticated approaches to integrate scientific data and services for TCM e-Science.</p> <p>Results</p> <p>We present a comprehensive approach to build dynamic and extendable e-Science applications for knowledge-intensive disciplines like TCM based on semantic and knowledge-based techniques. The semantic e-Science infrastructure for TCM supports large-scale database integration and service coordination in a virtual organization. We use domain ontologies to integrate TCM database resources and services in a semantic cyberspace and deliver a semantically superior experience including browsing, searching, querying and knowledge discovering to users. We have developed a collection of semantic-based toolkits to facilitate TCM scientists and researchers in information sharing and collaborative research.</p> <p>Conclusion</p> <p>Semantic and knowledge-based techniques are suitable to knowledge-intensive disciplines like TCM. It's possible to build on-demand e-Science system for TCM based on existing semantic and knowledge-based techniques. The presented approach in the paper integrates heterogeneous distributed TCM databases and services, and provides scientists with semantically superior experience to support collaborative research in TCM discipline.</p

Integrating findings of traditional medicine with modern pharmaceutical research: the potential role of linked open data

One of the biggest obstacles to progress in modern pharmaceutical research is the difficulty of integrating all available research findings into effective therapies for humans. Studies of traditionally used pharmacologically active plants and other substances in traditional medicines may be valuable sources of previously unknown compounds with therapeutic actions. However, the integration of findings from traditional medicines can be fraught with difficulties and misunderstandings. This article proposes an approach to use linked open data and Semantic Web technologies to address the heterogeneous data integration problem. The approach is based on our initial experiences with implementing an integrated web of data for a selected use-case, i.e., the identification of plant species used in Chinese medicine that indicate potential antidepressant activities

A PRACTICAL APPLICATION OF AN ONTOLOGY-BASED DIAGNOSTIC AND THERAPEUTIC SYSTEM FOR YORUBA TRADITIONAL MEDICINE.

Traditional Medicine (TM) has an important place in health care delivery among developed and developin g nations of the world. It is a first point of call before western m edicine and a last resort when all orthodox efforts fail. The objective of this study was to provide a way to share knowledge of Yo ruba Traditional Medicine (YTM) in a machine-readab le form and to use this method to build a treatment system base on Traditional Medicine. The treatment system constru cted in this study is an ontology-based application that can be used for treatment. Description Logics formalism is used to model YTM knowledge with visual reasoning capabilities and pr ocesses. Ontological approach is used to express fo rmal specification of YTM domain knowledge and this is implemented using Web Protégé application. In order to ensure the kno wledge model and ontology view is well defined, a prototype of k nowledge based system is developed based on the ont ology classes or concepts and relationships defined which require co nversion of OWL ontology into the relational datab ase system at first hand

Ontologies and Computational Methods for Traditional Chinese Medicine

Perinteinen kiinalainen lääketiede (PKL) on tuhansia vuosia vanha hoitomuoto, jonka tarkoituksena on terveyden ylläpito, tautien ennaltaehkäisemisen ja terveydellisten ongelmien hoito. Useat vuosittain julkaistavat tutkimukset tukevat hoitojen tehokkuutta ja PKL onkin jatkuvasti kasvattamassa suosiotaan maailmanlaajuisesti. Kiinassa PKL ollut suosittu hoitomuoto jo pitkään ja nykyään sitä harjoitetaan rinnakkain länsimaisen lääketieteen kanssa. Viime vuosikymmeninä tapahtuneen tietotekniikan kehityksen ja yleistymisen myötä myös PKL:n menetelmät ovat muuttuneet ja tietotekniikkaa on alettu hyödyntämään PKL:n tutkimuksessa. PKL:n tietoa on tallennettu digitaaliseen muotoon, minkä seurauksena on syntynyt suuri määrä erilaisia tietokantoja. Tieto on jakautunut eri tietokantoihin, joiden terminologia ei ole yhtenevää. Tämä aiheuttaa ongelmia tiedon löytämisessä ja tietoa hyödyntävien sovellusten kehittämisessä. Tässä työssä selvitetään, mitä PKL on, ja mikä sen asema on nykyään Kiinassa ja muualla maailmalla. Työn tarkoituksena on tutkia PKL:n tietoteknisten sovelluksen kehittämistä ja siihen liittyviä haasteita. Työssä perehdytään PKL:n ontologioiden ja semanttisten työkalujen toimintaan, sekä PKL:n laskennallisiin menetelmiin ja niiden tarjoamiin mahdollisuuksiin. Lisäksi kerrotaan uusimmista kansainvälisesti merkittävistä projekteista ja pohditaan tulevaisuuden näkymiä. Jo kehitetyt PKL:n tietotekniset sovellukset tarjoavat uusia mahdollisuuksia tiedon etsimiseen ja parantavat tutkijoiden mahdollisuutta jakaa tietoa ja tehdä yhteistyötä. Tietokoneavusteiset diagnoosityökalut ja asiantuntijajärjestelmät tarjoavat mahdollisuuksia lääkärin tekemän diagnoosin varmistamiseen. Tulevaisuudessa laskennallisia menetelmiä hyödyntäen voitaisiin tarjota terveyttä ja hyvinvointia edistäviä palveluja verkossa.Traditional Chinese Medicine (TCM) has been used for thousands of years in China for the purposes of health maintenance, disease prevention and treatment of health problems. Several published studies support the effectiveness of TCM treatments and the global use of TCM is constantly increasing. In China, Western and Chinese medicine are practiced in parallel. During the past few decades, the use of information technology in medicine has increased rapidly. The development of information technology has opened up new possibilities for information storage and sharing, as well as communication and interaction between people. Along with the growing use of information technology, a wide variety of patient databases and other electronic sources of information have emerged. However, the information is fragmented and dispersed, and the terminology is ambiguous. The objective of the thesis is to examine the position of TCM today, and to find out what changes and new opportunities the modern information technology brings for different aspects of TCM. This study describes how ontologies and semantic tools can be utilized when collecting existing knowledge and combining different databases. Also different computational methods and TCM expert systems are introduced. Finally, the most recent projects in the field of TCM are discussed and the future challenges are reflected. The computational methods for TCM, such as diagnostic tools and expert systems, could be very useful in anticipating and preventing health problems. E-science and knowledge discovery offer new ways for knowledge sharing and cooperation. TCM expert systems can be used to generate diagnosis or automatic clinical alerts. In the future, a comprehensive and easily accessible online health service system could be developed and used to improve the health and well-being of people

Knowledge representation for data integration and exploration in translational medicine

Tese de doutoramento, Informática (Bioinformática), Universidade de Lisboa, Faculdade de Ciências, 2014Biomedical research has evolved into a data-intensive science, where prodigious amounts of data can be collected from disparate resources at any time. However, the value of data can only be leveraged through its analysis, which ultimately results in the acquisition of knowledge. In domains such as translational medicine, data integration and interoperability are key requirements for an efficient data analysis. The semantic web and its technologies have been proposed as a solution for the problems of data integration and interoperability. One of the tools of the semantic web is the representation of domain knowledge with ontologies, which provide a formal description of that knowledge in a structured manner. The thesis underlying this work is that the representation of domain knowledge in ontologies can be exploited to improve the current knowledge about a disease, as well as improve the diagnosis and prognosis processes. The following two objectives were defined to validate this thesis: 1) to create a semantic model that represents and integrates the heterogeneous sources of data necessary for the characterization of a disease and of its prognosis process, exploiting semantic web technologies and existing ontologies; 2) to develop a methodology that exploits the knowledge represented in existing ontologies to improve the results of knowledge exploration methods obtained with translational medicine datasets. The first objective was accomplished and resulting in the following contributions: the methodology for the creation of a semantic model in the OWL language; a semantic model of the disease hypertrophic cardiomyopathy; and a review on the exploitation of semantic web resources in translation medicine systems. In the case of the second objective, also accomplished, the contributions are the adaptation of a standard enrichment analysis to use data from patients; and the application of the adapted enrichment analysis to improve the predictions made with a translational medicine dataset.Fundação para a Ciência e a Tecnologia (FCT, SFRH/BD/65257/2009