Databases and tools for constructing signal transduction networks in cancer

Citations

WEB OF SCIENCE

2
Citations

SCOPUS

3

초록

Traditionally, biologists have devoted their careers to studying individual biological entities of their own interest, partly due to lack of available data regarding that entity. Large, high-throughput data, too complex for conventional processing methods (i.e., "big data"), has accumulated in cancer biology, which is freely available in public data repositories. Such challenges urge biologists to inspect their biological entities of interest using novel approaches, firstly including repository data retrieval. Essentially, these revolutionary changes demand new interpretations of huge datasets at a systems-level, by so called "systems biology". One of the representative applications of systems biology is to generate a biological network from high-throughput big data, providing a global map of molecular events associated with specific phenotype changes. In this review, we introduce the repositories of cancer big data and cutting-edge systems biology tools for network generation, and improved identification of therapeutic targets.

키워드

CancerNetwork biologySignaling networkSystems biologyGENE-EXPRESSION DATASYSTEMS BIOLOGYCOVARIANCE-SELECTIONSETVISUALIZATIONENCYCLOPEDIAINTEGRATIONPROTEOMICSINFERENCEALGORITHM
제목
Databases and tools for constructing signal transduction networks in cancer
저자
Nam, Seungyoon
DOI
10.5483/BMBRep.2017.50.1.135
발행일
2017-01
유형
Review
저널명
BMB Reports
50
1
페이지
12 ~ 19