A meta-analysis portal for human breast cancer transcriptomics data: BreastCancerVis

被引：0

作者：

Buiga, Petronela ^{[1
]}

Soul, Jamie ^{[1
]}

Schwartz, Jean-Marc ^{[1
]}

机构：

[1] Univ Manchester, Fac Biol Med & Hlth, Manchester, Lancs, England

来源：

PROCEEDINGS 2018 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM) | 2018年

关键词：

Breast cancer; transcriptomics; network medicine; pathways; differential expression; web portal; GENE-EXPRESSION; CLASSIFICATION;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Breast cancer is a major disease posing many therapeutic and societal challenges. The major problem remains the diversity of the disease. Breast cancers are divided in several distinct subtypes, but the specific mechanisms involved in each subtype are not understood. We apply advanced network medicine techniques to the analysis of transcriptomics data of several breast cancer cell lines. We show that different subtypes are characterized by highly heterogeneous pathway activity. Using the overlap between differentially expressed genes and drug-induced expression changes, we present candidate drugs for repurposing. Furthermore, we find different active subnetworks across the subtypes, regulated by distinct transcription factors. All these results are made available via a user-friendly portal at http://phenome.manchester.ac.uk/breastcancer/.

引用

页码：260 / 264

页数：5

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