Efficient Storage for Semi-Structured Microarray Data Exploiting Structural Similarity
نویسندگان
چکیده
In this paper, we propose an alternative mapping strategy to mine the structural similarity and an advanced mapping rule from the algorithm. Objectrelational mapping technique is used for extracting advanced storage design schema for microarray data and structural similarity of elements is evaluated for efficient storage construction. The mapping strategy reduced the number of relational tables remarkably.
منابع مشابه
Efficient Storage Construction for Semi-Structured Microarray Data Exploiting Structural Similarity
To promote molecular biology studies, public repositories for microarray data need to be constructed; the minimum contents for analysis of microarray experiment have been defined and standardized. Public repositories have been constructed by some researches which follow the standards such as MIAME-compliant data and MAGE-OM/ML. However, enough consideration has not been taken into the design of...
متن کاملAn Efficient Storage Mapping Method For Semi-Structured Microarray Data Based On Structural Similarity
Public repositories for microarray data have been constructed by some researches which follow the standards such as MIAME-compliant data and MAGE-OM/ML. However, enough consideration has not been taken into the design of storage structure for the hierarchy of microarray data. In this paper, we propose alternative mapping strategy to mine the structural similarity and an advanced mapping rule fr...
متن کاملExploiting Local Similarity for Indexing Paths in Graph-Structured Data
XML and other semi-structured data may have partially specified or missing schema information, motivating the use of a structural summary which can be automatically computed from the data. These summaries also serve as indices for evaluating the complex path expressions common to XML and semi-structured query languages. However, to answer all path queries accurately, summaries must encode infor...
متن کاملExploiting Structural Information in Semi-structured Document Classification
We investigate methods for exploiting structural information in semi-structured documents in order to improve classification performance of the popular Naive Bayes text classifier. A novel method based on natural language modeling is introduced which effectively combines the expressive power of a structureaware classifier with more reliable parameter estimation of the flat-text model. We provid...
متن کاملLeveraging the Storage Layer to Support XML Similarity Joins in XDBMSs
XML is widely applied to describe semi-structured data commonly generated and used by modern information systems. XML database management systems (XDBMSs) are thus essential platforms in this context. Most XDBMS architectures proposed so far aim at reproducing functionalities found in relational systems. As such, these architectures inherit the same deficiency of traditional systems in dealing ...
متن کامل