Earticle

초록

영어

OBJECTIVE: To verify the feasibility of identification of different phenotypes of breast cancer by metabolic pathways-based two-step selective cluster analysis. METHODS: Gene expression data of breast cancer (series number GSE10810) were available through Gene Expression Omnibus (GEO) database of National Center for Biotechnology Information (NCBI). Breast cancer samples served as study materials. Samples were analyzed by two-step selective clustering method based on several pathways. After the first clustering analysis, samples with fair results were retained; the other samples were chosen to do the second clustering analysis and got the final results. Cluster3.0 software was applied to clustering analysis. RESULTS AND CONCLUSION: Finally, breast cancer samples were well identified by analyzing of 3 date sets of KEGG pathways. The results confirm the feasibility of discernment of different phenotypes by this method.

목차

Abstract
 1. Introduction
 2. Materials and methods
  2.1. Date obtaining
  2.2. Centroid-linkage clustering analysis
  2.3. Clustering analysis process
 3. Result
  3.1. Results of clustering analysis of lymph node and ER
  3.2. Clustering analysis result of degree of differentiation
 4. Discussion
 Acknowledgements
 References

키워드

저자

• Zhao-qi Wang [ School of Basic Medical Science, Capital Medical University ]
• Ping Chen [ School of Basic Medical Science, Capital Medical University ]
• Hong Xia [ School of Biomedical Engineering, Capital Medical University ]
• Ping Zhou [ School of Biomedical Engineering, Capital Medical University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Bio-Science and Bio-Technology

• 간기

  격월간

• pISSN

  2233-7849

• 수록기간

  2009~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605