• Genomics & Informatics
• /
• 제11권4호
• /
• pp.186-190
• /
• 2013

The advances in electronic medical records (EMRs) and bioinformatics (BI) represent two significant trends in healthcare. The widespread adoption of EMR systems and the completion of the Human Genome Project developed the technologies for data acquisition, analysis, and visualization in two different domains. The massive amount of data from both clinical and biology domains is expected to provide personalized, preventive, and predictive healthcare services in the near future. The integrated use of EMR and BI data needs to consider four key informatics areas: data modeling, analytics, standardization, and privacy. Bioclinical data warehouses integrating heterogeneous patient-related clinical or omics data should be considered. The representative standardization effort by the Clinical Bioinformatics Ontology (CBO) aims to provide uniquely identified concepts to include molecular pathology terminologies. Since individual genome data are easily used to predict current and future health status, different safeguards to ensure confidentiality should be considered. In this paper, we focused on the informatics aspects of integrating the EMR community and BI community by identifying opportunities, challenges, and approaches to provide the best possible care service for our patients and the population.

• 정보과학회 논문지
• /
• 제43권10호
• /
• pp.1115-1123
• /
• 2016

가정기반진리관리 시스템(ATMS)은 추론 시스템의 추론 과정을 저장하고 비단조추론을 지원할 수 있는 도구이다. 또한 의존기반 backtracking을 지원하므로 매우 넓은 공간 탐색 문제를 해결 할 수 있는 강력한 도구이다. 모든 추론 과정을 기록하고, 특정한 컨텍스트에서 지능형시스템의 Belief를 매우 빠르게 확인하고 비단조 추론 문제에 대한 해결책을 효율적으로 제공할 수 있게 한다. 그러나 최근 데이터의 양이 방대해지면서 기존의 단일 머신을 사용하는 경우 문제 해결 프로그램의 대용량의 추론과정을 저장하는 것이 불가능하게 되었다. 대용량 데이터에 대한 문제 해결 과정을 기록하는 것은 많은 연산과 메모리 오버헤드를 야기한다. 이러한 단점을 극복하기 위해 본 논문에서는 Apache Spark 환경에서 functional 및 객체지향 방식 기반의 점진적 컨텍스트 추론을 유지할 수 있는 방법을 제안한다. 이는 가정(Assumption)과 유도과정을 분산 환경에 저장하며, 실체화된 대용량 데이터셋의 변화를 효율적으로 수정가능하게 한다. 또한 ATMS의 Label, Environment를 분산 처리하여 대규모의 추론 과정을 효과적으로 관리할 수 있는 방안을 제시하고 있다. 제안하는 시스템의 성능을 측정하기 위해 5개의 노드로 구성된 클러스터에서 LUBM 데이터셋에 대한 OWL/RDFS 추론을 수행하고, 데이터의 추가, 설명, 제거에 대한 실험을 수행하였다. LUBM2000에 대하여 추론을 수행한 결과 80GB데이터가 추론되었고, ATMS에 적용하여 추가, 설명, 제거에 대하여 수초 내에 처리하는 성능을 보였다.

• Plant Biotechnology Reports
• /
• 제4권4호
• /
• pp.311-319
• /
• 2010

Lettuce is an economically important leafy vegetable that accumulates a milk-like sap called latex in the laticifer. Previously, we conducted a large-scale lettuce latex proteomic analysis. However, the identified proteins were obtained only from lettuce ESTs and proteins deposited in NCBI databases. To extend the number of known latex proteins, we carried out an analysis identifying 302 additional proteins that were matched to the NCBI non-redundant protein database. Interestingly, the newly identified proteins were not recovered from lettuce EST and protein databases, indicating the usefulness of this hetero system in MudPIT analysis. Gene ontology studies revealed that the newly identified latex proteins are involved in many processes, including many metabolic pathways, binding functions, stress responses, developmental processes, protein metabolism, transport and signal transduction. Application of the non-redundant plant protein database led to the identification of an increased number of latex proteins. These newly identified latex proteins provide a rich source of information for laticifer research.

• 대한한의학회지
• /
• 제44권2호
• /
• pp.106-118
• /
• 2023

Objectives: Network pharmacology is a method of constructing and analyzing a drug-compound-target network to predict potential efficacy and mechanisms related to drug targets. In that large-scale analysis can be performed in a short time, it is considered a suitable tool to explore the function and role of herbal medicine. Thus, we investigated the potential functions and pathways of Chongmyunggongjin-dan (CMGJD) on Alzheimer's disease (AD) via network pharmacology analysis. Methods: Using public databases and PubChem database, compounds of CMGJD and their target genes were collected. The putative target genes of CMGJD and known target genes of AD were compared and found the correlation. Then, the network was constructed using Cytoscape 3.9.1. and functional enrichment analysis was conducted based on the Gene Ontology (GO) Biological process and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathways to predict the mechanisms. Results: The result showed that total 104 compounds and 1157 related genes were gathered from CMGJD. The network consisted of 1157nodes and 10034 edges. 859 genes were interacted with AD gene set, suggesting that the effects of CMGJD are closely related to AD. Target genes of CMGJD are considerably associated with various pathways including 'Positive regulation of chemokine production', 'Cellular response to toxic substance', 'Arachidonic acid metabolic process', 'PI3K-Akt signaling pathway', 'Metabolic pathways', 'IL-17 signaling pathway' and 'Neuroactive ligand-receptor interaction'. Conclusion: Through a network pharmacological method, CMGJD was predicted to have high relevance with AD by regulating inflammation. This study could be used as a basis for effects of CMGJD on AD.