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Development of Haplotype Reconstruction System Using Public Resources (공개용 리소스를 활용한 Haplotype 재조합 시스템 개발)

  • Kim, Ki-Bong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.2
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    • pp.720-726
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    • 2010
  • Haplotype-based research has become increasingly important in the field of personalized medicine since the haplotype reflects a set of SNPs (Single Nucleotide Polymorphisms) that are genetically associated and inherited together. Currently, the most widely used application softwares available for haplotype reconstruction, based on in silico method, include PL-EM, Haplotyper, PHASE and HAP. PL-EM, Haplotyper and PHASE are command-line application running on LINUX or Unix system and HAP is a web-based client-server application. This paper deals with an integrated haplotype reconstruction system that have been developed with PL-EM and Haplotyper selected from the accuracy test with experimentally verified data on public application softwares. This integrated system is a kind of client-sever one with user friendly web interface and can provide end-users with a high quality of haplotype analysis. SNPs genotype data with a length of 5 derived from 5 people and SNPs genotype data with a length of 13 derived from 15 people were used to test the analysis results of Haplotyper and PL-EM respectively. As a result, this system has been confirmed to provide the systematic and easy-to-understand analysis results that consist of two main parts, i.e. individual haplotype information and haplotype pool information. In this respect, the integration system will be utilized as a useful tool for the discovery of disease related genes and the development of personalized drugs through facilitating the reconstruction of haplotype maps.

A Collaborative Video Annotation and Browsing System using Linked Data (링크드 데이터를 이용한 협업적 비디오 어노테이션 및 브라우징 시스템)

  • Lee, Yeon-Ho;Oh, Kyeong-Jin;Sean, Vi-Sal;Jo, Geun-Sik
    • Journal of Intelligence and Information Systems
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    • v.17 no.3
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    • pp.203-219
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    • 2011
  • Previously common users just want to watch the video contents without any specific requirements or purposes. However, in today's life while watching video user attempts to know and discover more about things that appear on the video. Therefore, the requirements for finding multimedia or browsing information of objects that users want, are spreading with the increasing use of multimedia such as videos which are not only available on the internet-capable devices such as computers but also on smart TV and smart phone. In order to meet the users. requirements, labor-intensive annotation of objects in video contents is inevitable. For this reason, many researchers have actively studied about methods of annotating the object that appear on the video. In keyword-based annotation related information of the object that appeared on the video content is immediately added and annotation data including all related information about the object must be individually managed. Users will have to directly input all related information to the object. Consequently, when a user browses for information that related to the object, user can only find and get limited resources that solely exists in annotated data. Also, in order to place annotation for objects user's huge workload is required. To cope with reducing user's workload and to minimize the work involved in annotation, in existing object-based annotation automatic annotation is being attempted using computer vision techniques like object detection, recognition and tracking. By using such computer vision techniques a wide variety of objects that appears on the video content must be all detected and recognized. But until now it is still a problem facing some difficulties which have to deal with automated annotation. To overcome these difficulties, we propose a system which consists of two modules. The first module is the annotation module that enables many annotators to collaboratively annotate the objects in the video content in order to access the semantic data using Linked Data. Annotation data managed by annotation server is represented using ontology so that the information can easily be shared and extended. Since annotation data does not include all the relevant information of the object, existing objects in Linked Data and objects that appear in the video content simply connect with each other to get all the related information of the object. In other words, annotation data which contains only URI and metadata like position, time and size are stored on the annotation sever. So when user needs other related information about the object, all of that information is retrieved from Linked Data through its relevant URI. The second module enables viewers to browse interesting information about the object using annotation data which is collaboratively generated by many users while watching video. With this system, through simple user interaction the query is automatically generated and all the related information is retrieved from Linked Data and finally all the additional information of the object is offered to the user. With this study, in the future of Semantic Web environment our proposed system is expected to establish a better video content service environment by offering users relevant information about the objects that appear on the screen of any internet-capable devices such as PC, smart TV or smart phone.