A Filtering Method for Identification of Significant Target mRNAs of Coexpressed and Differentially Expressed MicroRNA Clusters.

MicroRNA (miRNA) binding is primarily based on sequence, but structure-specific binding is also possible. Various prediction algorithms have been developed for predicting miRNA target genes; the results, however, have relatively high levels of false positives, and the degree of overlap between predicted targets from different methods is poor or null. We devised a new method for identifying significant miRNA target genes from an extensive list of predicted miRNA target gene relationships using hypergeometric distributions.

Utilization of a Clinical Trial Management System for the Whole Clinical Trial Process as an Integrated Database: System Development.

Background: Clinical trials pose potential risks in both communications and management due to the various stakeholders involved when performing clinical trials. The academic medical center has a responsibility and obligation to conduct and manage clinical trials while maintaining a sufficiently high level of quality, therefore it is necessary to build an information technology system to support standardized clinical trial processes and comply with relevant regulations.

Objective: The objective of the study was to address the challenges identified while performing clinical trials at an academic medical center, Asan Medical Center (AMC) in Korea, by developing and utilizing a clinical trial management system (CTMS) that complies with standardized processes from multiple departments or units, controlled vocabularies, security, and privacy regulations.

Establishment of Kawasaki disease database based on metadata standard.

Kawasaki disease (KD) is a rare disease that occurs predominantly in infants and young children. To identify KD susceptibility genes and to develop a diagnostic test, a specific therapy, or prevention method, collecting KD patients' clinical and genomic data is one of the major issues. For this purpose, Kawasaki Disease Database (KDD) was developed based on the efforts of Korean Kawasaki Disease Genetics Consortium (KKDGC).

CCR+: Metadata Based Extended Personal Health Record Data Model Interoperable with the ASTM CCR Standard.

Objectives: Extension of the standard model while retaining compliance with it is a challenging issue because there is currently no method for semantically or syntactically verifying an extended data model. A metadata-based extended model, named CCR+, was designed and implemented to achieve interoperability between standard and extended models.

Methods: Furthermore, a multilayered validation method was devised to validate the standard and extended models.

Establishing semantic interoperability of biomedical metadata registries using extended semantic relationships.

Achieving semantic interoperability is critical for biomedical data sharing between individuals, organizations and systems. The ISO/IEC 11179 MetaData Registry (MDR) standard has been recognized as one of the solutions for this purpose. The standard model, however, is limited.

GOChase-II: correcting semantic inconsistencies from Gene Ontology-based annotations for gene products.

Background: The Gene Ontology (GO) provides a controlled vocabulary for describing genes and gene products. In spite of the undoubted importance of GO, several drawbacks associated with GO and GO-based annotations have been introduced. We identified three types of semantic inconsistencies in GO-based annotations; semantically redundant, biological-domain inconsistent and taxonomy inconsistent annotations.