[HTML][HTML] Identification of breast cancer risk modules via an integrated strategy

W Li, G Deng, J Zhang, E Hu, Y He, J Lv, X Sun… - Aging (Albany …, 2019 - ncbi.nlm.nih.gov
Breast cancer is one of the most common malignant cancers among females worldwide.
This complex disease is not caused by a single gene, but resulted from multi-gene …

[HTML][HTML] Identification of breast cancer prognostic modules based on weighted protein‑protein interaction networks

W Li, X Bai, E Hu, H Huang, Y Li, Y He… - Oncology …, 2017 - spandidos-publications.com
Breast cancer is one of the leading causes of mortality in females. A number of prognostic
markers have been identified, including single genes, multi‑gene signatures and network …

[HTML][HTML] Predicting breast cancer risk using interacting genetic and demographic factors and machine learning

H Behravan, JM Hartikainen, M Tengström… - Scientific reports, 2020 - nature.com
Breast cancer (BC) is a multifactorial disease and the most common cancer in women
worldwide. We describe a machine learning approach to identify a combination of …

Identification of breast cancer prognostic modules via differential module selection based on weighted gene Co-expression network analysis

L Guo, L Mao, WT Lu, J Yang - Biosystems, 2021 - Elsevier
Breast cancer is a complex cancer which includes many different subtypes. Identifying
prognostic modules, ie, functionally related gene networks that play crucial roles in cancer …

[HTML][HTML] Comparative analysis of gene correlation networks of breast cancer patients based on mutations in TP53

B Park, J Im, K Han - Biomolecules, 2022 - mdpi.com
Breast cancer is one of the most prevalent cancers in females, with more than 450,000
deaths each year worldwide. Among the subtypes of breast cancer, basal-like breast cancer …

[HTML][HTML] Multi-omics marker analysis enables early prediction of breast tumor progression

H Xu, T Lien, H Bergholtz, T Fleischer… - Frontiers in …, 2021 - frontiersin.org
Ductal carcinoma in situ (DCIS) is a preinvasive form of breast cancer with a highly variable
potential of becoming invasive and affecting mortality of the patients. Due to the lack of …

Refinement of breast cancer risk prediction with concordant leading edge subsets from prognostic gene signatures

CC Huang, SH Tu, HH Lien, CS Huang… - Breast cancer research …, 2014 - Springer
Several prognostic signatures have been identified for breast cancer. However, these
signatures vary extensively in their gene compositions, and the poor concordance of the risk …

[HTML][HTML] Inferring gene dependency network specific to phenotypic alteration based on gene expression data and clinical information of breast cancer

X Zhou, J Liu - PLoS One, 2014 - journals.plos.org
Although many methods have been proposed to reconstruct gene regulatory network, most
of them, when applied in the sample-based data, can not reveal the gene regulatory …

[HTML][HTML] Core module biomarker identification with network exploration for breast cancer metastasis

R Yang, BJ Daigle, LR Petzold, FJ Doyle - BMC bioinformatics, 2012 - Springer
Background In a complex disease, the expression of many genes can be significantly
altered, leading to the appearance of a differentially expressed" disease module". Some of …

[HTML][HTML] Mining the tissue-tissue gene co-expression network for tumor microenvironment study and biomarker prediction

Y Xiang, J Zhang, K Huang - BMC genomics, 2013 - Springer
Background Recent discovery in tumor development indicates that the tumor
microenvironment (mostly stroma cells) plays an important role in cancer development. To …