• Title/Summary/Keyword: target databases

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Prediction of Mammalian MicroRNA Targets - Comparative Genomics Approach with Longer 3' UTR Databases

  • Nam, Seungyoon;Kim, Young-Kook;Kim, Pora;Kim, V. Narry;Shin, Seokmin;Lee, Sanghyuk
    • Genomics & Informatics
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    • v.3 no.3
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    • pp.53-62
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    • 2005
  • MicroRNAs play an important role in regulating gene expression, but their target identification is a difficult task due to their short length and imperfect complementarity. Burge and coworkers developed a program called TargetScan that allowed imperfect complementarity and established a procedure favoring targets with multiple binding sites conserved in multiple organisms. We improved their algorithm in two major aspects - (i) using well-defined UTR (untranslated region) database, (ii) examining the extent of conservation inside the 3' UTR specifically. Average length in our UTR database, based on the ECgene annotation, is more than twice longer than the Ensembl. Then, TargetScan was used to identify putative binding sites. The extent of conservation varies significantly inside the 3' UTR. We used the 'tight' tracks in the UCSC genome browser to select the conserved binding sites in multiple species. By combining the longer 3' UTR data, TargetScan, and tightly conserved blocks of genomic DNA, we identified 107 putative target genes with multiple binding sites conserved in multiple species, of which 85 putative targets are novel.

A search mechanism for moving objects in a spatial database (공간 데이타베이스에서 이동 객체의 탐색기법)

  • 유병구;황수찬;백중환
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.35C no.1
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    • pp.25-33
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    • 1998
  • This paepr presents an algorithm for searching an object in a fast way which contains a continuous moving object in multi-dimensional spatical databases. This algorithm improves the search method of R-tree for the case that a target object is continuously moving in a spatial database. It starts the searching from the current node instead of the root of R-tree. Thus, the algorithm will find the target object from the entries of current node or sibling nodes in the most cases. The performance analysis shows that it is more efficient than the existing algorithm for R-tree when search windows or target objects are continuously moving.

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Automatic Quality Measurement of Gray-scale Handwriting Based on Extended Average Entropy (확장된 평균 엔트로피에 기반한 명도 영상 필기 데이터의 품질 자동 평가)

  • 박정선
    • Korean Journal of Cognitive Science
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    • v.10 no.3
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    • pp.77-83
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    • 1999
  • With a surge of interest in OCR in 1990s a large number of handwriting or h handprinting databases have been built one after another around the world. One problem that researches encounter today is that all the databases differ in various ways including the script qualities. This paper proposes a method for measuring handwriting qualities that can be used for comparison of databases and objective test for character recognizers. The key idea i involved is classifying character samples into a number of groups each characterizing a set of qualities. In order to evaluate the proposed method we carried out experiments on KU-1 database. The result we achieve is meaningful and the method is helpful for the target tasks.

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Bulk Insertion Method for R-tree using Seeded Clustering (R-tree에서 Seeded 클러스터링을 이용한 다량 삽입)

  • 이태원;문봉기;이석호
    • Journal of KIISE:Databases
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    • v.31 no.1
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    • pp.30-38
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    • 2004
  • In many scientific and commercial applications such as Earth Observation System (EOSDIS) and mobile Phone services tracking a large number of clients, it is a daunting task to archive and index ever increasing volume of complex data that are continuously added to databases. To efficiently manage multidimensional data in scientific and data warehousing environments, R-tree based index structures have been widely used. In this paper, we propose a scalable technique called seeded clustering that allows us to maintain R-tree indexes by bulk insertion while keeping pace with high data arrival rates. Our approach uses a seed tree, which is copied from the top k levels of a target R-tree, to classify input data objects into clusters. We then build an R-tree for each of the clusters and insert the input R-trees into the target R-tree in bulk one at a time. We present detailed algorithms for the seeded clustering and bulk insertion as well as the results from our extensive experimental study. The experimental results show that the bulk insertion by seeded clustering outperforms the previously known methods in terms of insertion cost and the quality of target R-trees measured by their query performance.

Selection Criteria of Target Systems for Quality Management of National Defense Data (국방데이터 품질관리를 위한 대상 체계 선정 기준)

  • Jiseong Son;Yun-Young Hwang
    • Journal of Internet Computing and Services
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    • v.24 no.6
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    • pp.155-160
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    • 2023
  • In principle, data from all databases and systems managed by the Ministry of Defense or public institutions must be guaranteed to have a certain level of quality or higher, but since most information systems are built and operated, data quality management for all systems is realistically limited. Most defense data is not disclosed due to the nature of the work, and many systems are strategically developed or integrated and managed by the military depending on the need and importance of the work. In addition, many types of data that require data quality management are being accumulated and generated, such as sensor data generated from weapon systems, unstructured data, and artificial intelligence learning data. However, there is no data quality management guide for defense data and a guide for selecting quality control targets, and the selection criteria are ambiguous to select databases and systems for quality control of defense data according to the standards of the public data quality management manual. Depends on the person in charge. Therefore, this paper proposes criteria for selecting a target system for quality control of defense data, and describes the relationship between the proposed selection criteria and the selection criteria in the existing manual.

Performance Analysis for Maintaining Distributed Views

  • Lee, Wookey
    • Proceedings of the Korea Database Society Conference
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    • 1997.10a
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    • pp.515-523
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    • 1997
  • Maintaining materialized views and/or replica can basically be considered as a client-sewer architecture that extracts the changes of the distributed source data and transfers them to the relevant target sites. View maintenance and materialized views are considered to be important for suggesting solutions to the problems such as a decision support, active databases, a data warehouse, temporal databases, internet applications, etc. In this paper an analysis is addressed that formulates the cost functions and evaluates them as the propagation subjects, objects, and update policies. The propagation subject can be the client side, sewer side, and the third: and the objects can be base tables, semi-base tables, and delta files: And the update policies can be the immediate, deferred and periodic ones, respectively.

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Reliability Prediction of Hybrid Rocket Ignition System (하이브리드 로켓 점화 장치의 신뢰도 예측)

  • Moon, Keun-Hwan;Moon, Hee-Jang;Choi, Joo-Ho;Kim, Jin-Kon
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.24 no.4
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    • pp.26-34
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    • 2016
  • In this study, reliability prediction of the ignition system of hybrid rocket is performed. The FMECA is preceded to the reliability prediction. To this end, the ignition system is divided into 5 components and 19 potential failure modes. The failure cause and effects are identified and criticality analysis is carried out for each failure mode, in which the criticality number is estimated using the failure rate databases. Among the numbers, the failure modes and components with higher criticality and severity are chosen and allocated with higher weighting factor. The reliability predictions are performed using the failure rate databases, from which the current ignition system is found to satisfy the target reliability.

Relational Data Extraction and Transformation: A Study to Enhance Information Systems Performance

  • Forat Falih, Hasan;Muhamad Shahbani Abu, Bakar
    • Journal of information and communication convergence engineering
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    • v.20 no.4
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    • pp.265-272
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    • 2022
  • The most effective method to improve information system capabilities is to enable instant access to several relational database sources and transform data with a logical structure into multiple target relational databases. There are numerous data transformation tools available; however, they typically contain fixed procedures that cannot be changed by the user, making it impossible to fulfill the near-real-time data transformation requirements. Furthermore, some tools cannot build object references or alter attribute constraints. There are various situations in which tool changes in data type cause conflicts and difficulties with data quality while transforming between the two systems. The R-programming language was extensively used throughout this study, and several different relational database structures were utilized to complete the proposed study. Experiments showed that the developed study can improve the performance of information systems by interacting with and exchanging data with various relational databases. The study addresses data quality issues, particularly the completeness and integrity dimensions of the data transformation processes.

Elastic Rule Discovering in Sequence Databases (시퀀스 데이터베이스에서 유연 규칙의 탐사)

  • Park, Sang-Hyun;Kim, Sang-Wook;Kim, Man-Soon
    • Journal of Industrial Technology
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    • v.21 no.A
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    • pp.147-153
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    • 2001
  • This paper presents techniques for discovering rules with elastic patterns. Elastic patterns are useful for discovering rules from data sequences with different sampling rates. For fast discovery of rules whose heads and bodies are elastic patterns, we construct a suffix tree from succinct forms of data sequences. The suffix tree is a compact representation of rules, and is also used as an index structure for finding rules matched to a target head sequence. When matched rules cannot be found, the concept of rule relaxation is introduced. Using a cluster hierarchy and a relaxation error, we find the least relaxed rules that provide the most specific information on a target head sequence. Performance evaluation through extensive experiments reseals the effectiveness of the proposed approach.

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Prediction the efficacy and mechanism of action of Daehwangmokdanpitang to treat psoriasis based on network pharmacology (네트워크 약리학 기반 대황목단피탕(大黃牧丹皮湯)의 건선 조절 효능 및 작용 기전 예측)

  • Bitna Kweon;Dong-Uk Kim;Gabsik Yang; Il-Joo Jo
    • The Korea Journal of Herbology
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    • v.38 no.6
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    • pp.73-91
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    • 2023
  • Objectives : This study used a network pharmacology approach to elucidate the efficacy and molecular mechanisms of Daehwangmokdanpitang (DHMDPT) on Psoriasis. Methods : Using OASIS databases and PubChem database, compounds of DHMDPT and their target genes were collected. The putative target genes of DHMDPT and known target genes of psoriasis were compared and found the correlation. Then, the network was constructed using Cytoscape 3.10.1. The key target genes were screened by Analyzer network and their functional enrichment analysis was conducted based on the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathways to predict the mechanisms. Results : The result showed that total 30 compounds and 439 related genes were gathered from DHMDPT. 264 genes were interacted with psoriasis gene set, suggesting that the effects of DHMDPT are closely related to psoriasis. Based on GO enrichment analysis and KEGG pathways, 'Binding', 'Cytokine Activity', 'Receptor Ligand Activity' 'HIF-1 signaling pathway', 'IL-17 signaling pathway', 'Toll-like receptor signaling pathway', and 'TNF signaling pathway' were predicted as functional pathways of 16 key target genes of DHMDPT on psoriasis. Among the target genes, IL6, IL1B, TNF, AKT1 showed high correlation with the results of KEGG pathways. Additionally, Emodin, Acetovanillone, Gallic acid, and Ferulic acid showed a high relevance with key genes and their mechanisms. Conclusion : Through a network pharmacological method, DHMDPT was predicted to have high relevance with psoriasis. This study could be used as a basis for studying therapeutic effects of DHMDPT on psoriasis.