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BioKG: An analytical Web-based Portal in assisting clinical decision support using clinical and genomic data

원문정보

초록

영어
There are many openly available medical resources, which include structural clinical and genomic data for cancer patients. The data sources are provided with primitive toolsets which provide minimal descriptive statistics to help in initial exploratory analysis. However, this minimal support is not sufficient in many ways. Firstly, with an individual data source, the tools are not supporting statistical models and visualization to infer preferable clinical association with gnomically mutated patient data. Secondly, these data tools are not coherent to integrate the external toolsets for sharing the data and analytical outcomes. To target this limitation, the paper provides a technical detail of the development of Webbased tools – known as BioKG portal (Biological Knowledge Graph). At this moment, the BioKG is coming with features; a) provide unified data-model (influenced from knowledge graph), b) integration of different data sources with propriety data support – such as CSV files, JSON based API, other custom delimited files, c) integrated gene set enrichment analysis support on unified clinical and genomic data, and d) visualization support for the analytical outcomes. The BioKG portal is demonstrated in thyroid cancer by integrating data from openly available portals – TCGA and cBioPortal. This web-based toolset's key advantages are facilitating stakeholders with diverse capabilities – such as clinicians, bioinformaticians, and computer scientists.

목차

Abstract
I. INTRODUCTION
II. PROPOSED METHOD: BIOKG PORTAL
A. Data Acquisition
B. Data pre-processing
C. Descriptive analysis
D. Building of data summarization and association
E. Knowledge extraction
F. Knowledge Representation
III. BIOKG PORTAL IMPLEMENTATION
ACKNOWLEDGMENT
REFERENCES

저자

  • Muhammad Ameen [ Department of Computer Science Bahria University Pakistan ]
  • Amaad Hussain [ Department of Computer Science Bahria University Pakistan ] Corresponding Author
  • Rukhsana [ Department of Biosciences Sejong University ]
  • Maqbool Hussain [ Department of Software Sejong University ]
  • Songyoung Lee [ Dept. Computer Engineering Kyung Hee University ]

참고문헌

자료제공 : 네이버학술정보

    간행물 정보

    • 간행물
      한국차세대컴퓨팅학회 학술대회
    • 간기
      반년간
    • 수록기간
      2021~2025
    • 십진분류
      KDC 566 DDC 004