• Molecules and Cells
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• v.38 no.3
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• pp.210-220
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• 2015

Athletic performance is an important criteria used for the selection of superior horses. However, little is known about exercise-related epigenetic processes in the horse. DNA methylation is a key mechanism for regulating gene expression in response to environmental changes. We carried out comparative genomic analysis of genome-wide DNA methylation profiles in the blood samples of two different thoroughbred horses before and after exercise by methylated-DNA immunoprecipitation sequencing (MeDIP-Seq). Differentially methylated regions (DMRs) in the pre-and post-exercise blood samples of superior and inferior horses were identified. Exercise altered the methylation patterns. After 30 min of exercise, 596 genes were hypomethy-lated and 715 genes were hypermethylated in the superior horse, whereas in the inferior horse, 868 genes were hypomethylated and 794 genes were hypermethylated. These genes were analyzed based on gene ontology (GO) annotations and the exercise-related pathway patterns in the two horses were compared. After exercise, gene regions related to cell division and adhesion were hypermethylated in the superior horse, whereas regions related to cell signaling and transport were hypermethylated in the inferior horse. Analysis of the distribution of methylated CpG islands confirmed the hypomethylation in the gene-body methylation regions after exercise. The methylation patterns of transposable elements also changed after exercise. Long interspersed nuclear elements (LINEs) showed abundance of DMRs. Collectively, our results serve as a basis to study exercise-based reprogramming of epigenetic traits.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.31-59
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• 2007

We frequently use search engines to find relevant information in the Web but still end up with too much information. In order to solve this problem of information overload, ranking algorithms have been applied to various domains. As more information will be available in the future, effectively and efficiently ranking search results will become more critical. In this paper, we propose a ranking algorithm for the Semantic Web resources, specifically RDF resources. Traditionally, the importance of a particular Web page is estimated based on the number of key words found in the page, which is subject to manipulation. In contrast, link analysis methods such as Google's PageRank capitalize on the information which is inherent in the link structure of the Web graph. PageRank considers a certain page highly important if it is referred to by many other pages. The degree of the importance also increases if the importance of the referring pages is high. Kleinberg's algorithm is another link-structure based ranking algorithm for Web pages. Unlike PageRank, Kleinberg's algorithm utilizes two kinds of scores: the authority score and the hub score. If a page has a high authority score, it is an authority on a given topic and many pages refer to it. A page with a high hub score links to many authoritative pages. As mentioned above, the link-structure based ranking method has been playing an essential role in World Wide Web(WWW), and nowadays, many people recognize the effectiveness and efficiency of it. On the other hand, as Resource Description Framework(RDF) data model forms the foundation of the Semantic Web, any information in the Semantic Web can be expressed with RDF graph, making the ranking algorithm for RDF knowledge bases greatly important. The RDF graph consists of nodes and directional links similar to the Web graph. As a result, the link-structure based ranking method seems to be highly applicable to ranking the Semantic Web resources. However, the information space of the Semantic Web is more complex than that of WWW. For instance, WWW can be considered as one huge class, i.e., a collection of Web pages, which has only a recursive property, i.e., a 'refers to' property corresponding to the hyperlinks. However, the Semantic Web encompasses various kinds of classes and properties, and consequently, ranking methods used in WWW should be modified to reflect the complexity of the information space in the Semantic Web. Previous research addressed the ranking problem of query results retrieved from RDF knowledge bases. Mukherjea and Bamba modified Kleinberg's algorithm in order to apply their algorithm to rank the Semantic Web resources. They defined the objectivity score and the subjectivity score of a resource, which correspond to the authority score and the hub score of Kleinberg's, respectively. They concentrated on the diversity of properties and introduced property weights to control the influence of a resource on another resource depending on the characteristic of the property linking the two resources. A node with a high objectivity score becomes the object of many RDF triples, and a node with a high subjectivity score becomes the subject of many RDF triples. They developed several kinds of Semantic Web systems in order to validate their technique and showed some experimental results verifying the applicability of their method to the Semantic Web. Despite their efforts, however, there remained some limitations which they reported in their paper. First, their algorithm is useful only when a Semantic Web system represents most of the knowledge pertaining to a certain domain. In other words, the ratio of links to nodes should be high, or overall resources should be described in detail, to a certain degree for their algorithm to properly work. Second, a Tightly-Knit Community(TKC) effect, the phenomenon that pages which are less important but yet densely connected have higher scores than the ones that are more important but sparsely connected, remains as problematic. Third, a resource may have a high score, not because it is actually important, but simply because it is very common and as a consequence it has many links pointing to it. In this paper, we examine such ranking problems from a novel perspective and propose a new algorithm which can solve the problems under the previous studies. Our proposed method is based on a class-oriented approach. In contrast to the predicate-oriented approach entertained by the previous research, a user, under our approach, determines the weights of a property by comparing its relative significance to the other properties when evaluating the importance of resources in a specific class. This approach stems from the idea that most queries are supposed to find resources belonging to the same class in the Semantic Web, which consists of many heterogeneous classes in RDF Schema. This approach closely reflects the way that people, in the real world, evaluate something, and will turn out to be superior to the predicate-oriented approach for the Semantic Web. Our proposed algorithm can resolve the TKC(Tightly Knit Community) effect, and further can shed lights on other limitations posed by the previous research. In addition, we propose two ways to incorporate data-type properties which have not been employed even in the case when they have some significance on the resource importance. We designed an experiment to show the effectiveness of our proposed algorithm and the validity of ranking results, which was not tried ever in previous research. We also conducted a comprehensive mathematical analysis, which was overlooked in previous research. The mathematical analysis enabled us to simplify the calculation procedure. Finally, we summarize our experimental results and discuss further research issues.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.137-152
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• 2012

In the generation of Web 2.0, as many users start to make lots of web contents called user created contents by themselves, the World Wide Web is overflowing by countless information. Therefore, it becomes the key to find out meaningful information among lots of resources. Nowadays, the information retrieval is the most important thing throughout the whole field and several types of search services are developed and widely used in various fields to retrieve information that user really wants. Especially, the legal information search is one of the indispensable services in order to provide people with their convenience through searching the law necessary to their present situation as a channel getting knowledge about it. The Office of Legislation in Korea provides the Korean Law Information portal service to search the law information such as legislation, administrative rule, and judicial precedent from 2009, so people can conveniently find information related to the law. However, this service has limitation because the recent technology for search engine basically returns documents depending on whether the query is included in it or not as a search result. Therefore, it is really difficult to retrieve information related the law for general users who are not familiar with legal terms in the search engine using simple matching of keywords in spite of those kinds of efforts of the Office of Legislation in Korea, because there is a huge divergence between everyday words and legal terms which are especially from Chinese words. Generally, people try to access the law information using everyday words, so they have a difficulty to get the result that they exactly want. In this paper, we propose a term mapping methodology between everyday words and legal terms for general users who don't have sufficient background about legal terms, and we develop a search service that can provide the search results of law information from everyday words. This will be able to search the law information accurately without the knowledge of legal terminology. In other words, our research goal is to make a law information search system that general users are able to retrieval the law information with everyday words. First, this paper takes advantage of tags of internet blogs using the concept for collective intelligence to find out the term mapping relationship between everyday words and legal terms. In order to achieve our goal, we collect tags related to an everyday word from web blog posts. Generally, people add a non-hierarchical keyword or term like a synonym, especially called tag, in order to describe, classify, and manage their posts when they make any post in the internet blog. Second, the collected tags are clustered through the cluster analysis method, K-means. Then, we find a mapping relationship between an everyday word and a legal term using our estimation measure to select the fittest one that can match with an everyday word. Selected legal terms are given the definite relationship, and the relations between everyday words and legal terms are described using SKOS that is an ontology to describe the knowledge related to thesauri, classification schemes, taxonomies, and subject-heading. Thus, based on proposed mapping and searching methodologies, our legal information search system finds out a legal term mapped with user query and retrieves law information using a matched legal term, if users try to retrieve law information using an everyday word. Therefore, from our research, users can get exact results even if they do not have the knowledge related to legal terms. As a result of our research, we expect that general users who don't have professional legal background can conveniently and efficiently retrieve the legal information using everyday words.

• Journal of Life Science
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• v.34 no.7
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• pp.465-475
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• 2024

Lactiplantibacillus plantarum K9 is a probiotic strain that can be utilized from various bioactive substances isolated from Protaetia brevitarsis seulensis larvae. In this study, a genetic analysis of L. plantarum K9 revealed the existence of a bacterial chromosome and three plasmids. The glycolysis pathway and pentose phosphate pathway were examined for their normal functioning via an analysis of the core metabolic pathways of L. plantarum K9. Since the key enzymes, fluctose-1,6-bisphospatase (EC: 3.1.3.11) and 6-phosphogluconate dehydratase (EC: 4.2.1.12)/2-keto-deoxy-6-phosphogluconate (KDPG) aldolase (EC: 4.2.1.55), of gluconeogenesis and the ED pathway were not identified from the L. plantarum K9 genome, we suggest that gluconeogenesis and the ED pathway are not performed in L. plantarum K9. Additionally, while some enzymes, related to fumarate and malate biosyntheses, involved in the TCA cycle were identified from L. plantarum K9, the enzymes associated with the remaining TCA cycle were absent, indicating that the TCA cycle cannot proceed. Meanwhile, based on our findings, we propose that the oxidative electron transport system performs class IIB-type (bd-type) electron transfer. In summary, we assert that L. plantarum K9 performs homolactic fermentation, executes gluconeogenesis and the pentose phosphate pathway, and carries out energy metabolism through the class IIB-type oxidative electron transport system. Therefore, we suggest that L. plantarum K9 has relatively high lactic acid production, and that it has excellent antibacterial activity, as a result, compared to other lactic acid bacterial strains. Moreover, we speculate that L. plantarum K9 has an oxidative electron transport capability, indicating that it is highly resistant to oxygen and suggesting that it has fine cultivation characteristics, which collectively make it highly suitable for use as a probiotic.

• Journal of Intelligence and Information Systems
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• v.17 no.2
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• pp.39-60
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• 2011

Since the introduction of web 2.0 technology, social network service has been recognized as the foundation of an important future information technology. The advent of web 2.0 has led to the change of content creators. In the existing web, content creators are service providers, whereas they have changed into service users in the recent web. Users share experiences with other users improving contents quality, thereby it has increased the importance of social network. As a result, diverse forms of social network service have been emerged from relations and experiences of users. Social network is a network to construct and express social relations among people who share interests and activities. Today's social network service has not merely confined itself to showing user interactions, but it has also developed into a level in which content generation and evaluation are interacting with each other. As the volume of contents generated from social network service and the number of connections between users have drastically increased, the social network extraction method becomes more complicated. Consequently the following problems for the social network extraction arise. First problem lies in insufficiency of representational power of object in the social network. Second problem is incapability of expressional power in the diverse connections among users. Third problem is the difficulty of creating dynamic change in the social network due to change in user interests. And lastly, lack of method capable of integrating and processing data efficiently in the heterogeneous distributed computing environment. The first and last problems can be solved by using FOAF, a tool for describing ontology-based user profiles for construction of social network. However, solving second and third problems require a novel technology to reflect dynamic change of user interests and relations. In this paper, we propose a novel method to overcome the above problems of existing social network extraction method by applying FOAF (a tool for describing user profiles) and RSS (a literary web work publishing mechanism) to OLAP system in order to dynamically innovate and manage FOAF. We employed data interoperability which is an important characteristic of FOAF in this paper. Next we used RSS to reflect such changes as time flow and user interests. RSS, a tool for literary web work, provides standard vocabulary for distribution at web sites and contents in the form of RDF/XML. In this paper, we collect personal information and relations of users by utilizing FOAF. We also collect user contents by utilizing RSS. Finally, collected data is inserted into the database by star schema. The system we proposed in this paper generates OLAP cube using data in the database. 'Dynamic FOAF Management Algorithm' processes generated OLAP cube. Dynamic FOAF Management Algorithm consists of two functions: one is find_id_interest() and the other is find_relation (). Find_id_interest() is used to extract user interests during the input period, and find-relation() extracts users matching user interests. Finally, the proposed system reconstructs FOAF by reflecting extracted relationships and interests of users. For the justification of the suggested idea, we showed the implemented result together with its analysis. We used C# language and MS-SQL database, and input FOAF and RSS as data collected from livejournal.com. The implemented result shows that foaf : interest of users has reached an average of 19 percent increase for four weeks. In proportion to the increased foaf : interest change, the number of foaf : knows of users has grown an average of 9 percent for four weeks. As we use FOAF and RSS as basic data which have a wide support in web 2.0 and social network service, we have a definite advantage in utilizing user data distributed in the diverse web sites and services regardless of language and types of computer. By using suggested method in this paper, we can provide better services coping with the rapid change of user interests with the automatic application of FOAF.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.59-76
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• 2014

The revolution of smart media such as smart phone, smart TV and tablets has brought easiness for people to get contents and related information anywhere and anytime. The characteristics of the smart media have changed user behavior for watching the contents from passive attitude into active one. Video is a kind of multimedia resources and widely used to provide information effectively. People not only watch video contents, but also search for related information to specific objects appeared in the contents. However, people have to use extra views or devices to find the information because the existing video contents provide no information through the contents. Therefore, the interaction between user and media is becoming a major concern. The demand for direct interaction and instant information is much increasing. Digital media environment is no longer expected to serve as a one-way information service, which requires user to search manually on the internet finding information they need. To solve the current inconvenience, an interactive service is needed to provide the information exchange function between people and video contents, or between people themselves. Recently, many researchers have recognized the importance of the requirements for interactive services, but only few services provide interactive video within restricted functionality. Only cooking domain is chosen for an interactive cooking video query service in this research. Cooking is receiving lots of people attention continuously. By using smart media devices, user can easily watch a cooking video. One-way information nature of cooking video does not allow to interactively getting more information about the certain contents, although due to the characteristics of videos, cooking videos provide various information such as cooking scenes and explanation for each recipe step. Cooking video indeed attracts academic researches to study and solve several problems related to cooking. However, just few studies focused on interactive services in cooking video and they still not sufficient to provide the interaction with users. In this paper, an interactive cooking video query service system with linked data to provide the interaction functionalities to users. A linked recipe schema is used to handle the linked data. The linked data approach is applied to construct queries in systematic manner when user interacts with cooking videos. We add some classes, data properties, and relations to the linked recipe schema because the current version of the schema is not enough to serve user interaction. A web crawler extracts recipe information from allrecipes.com. All extracted recipe information is transformed into ontology instances by using developed instance generator. To provide a query function, hundreds of questions in cooking video web sites such as BBC food, Foodista, Fine cooking are investigated and analyzed. After the analysis of the investigated questions, we summary the questions into four categories by question generalization. For the question generalization, the questions are clustered in eleven questions. The proposed system provides an environment associating UI (User Interface) and UX (User Experience) that allow user to watch cooking videos while obtaining the necessary additional information using extra information layer. User can use the proposed interactive cooking video system at both PC and mobile environments because responsive web design is applied for the proposed system. In addition, the proposed system enables the interaction between user and video in various smart media devices by employing linked data to provide information matching with the current context. Two methods are used to evaluate the proposed system. First, through a questionnaire-based method, computer system usability is measured by comparing the proposed system with the existing web site. Second, the answer accuracy for user interaction is measured to inspect to-be-offered information. The experimental results show that the proposed system receives a favorable evaluation and provides accurate answers for user interaction.

• Horticultural Science & Technology
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• v.31 no.5
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• pp.607-616
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• 2013

Light with two faces, beneficial and harmful effects is an important signal for every living cell. Optimal adaptation to light environment enhances the fitness of an organism and survival in nature. Understandings of light quality and plant growth provide with the economical guides for artificial light sources like LEDs. Compared with those under white light, the 1 week seedlings of Chinese cabbage (Brassica rapa) under monochromic red and blue light showed normal development and growth. In contrast to extremely long and etiolated hypocotyls of the seedlings under dark, those under far-red etiolated were extremely short. Based on the microarray analysis, blue light induced the vigorous development and growth and two fold changes of transcripts than red light condition. To have insight of gene products under different light qualities conditions, GO term enrichments were calculated and each gene according to their GO terms were categorized. The blue and red lights affected the expressions of genes related to biological process. Especially, the genes related to metabolic process and developmental process and plastid and chloroplast in the cellular component category were induced under blue light. This study provided the molecular biological evidence for various light qualities on the growing process of B. rapa.