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Shumei Zhang

Researcher at Harbin Medical University

Publications -  15
Citations -  452

Shumei Zhang is an academic researcher from Harbin Medical University. The author has contributed to research in topics: DNA methylation & Breast cancer. The author has an hindex of 6, co-authored 12 publications receiving 286 citations. Previous affiliations of Shumei Zhang include Northeast Forestry University.

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DiseaseMeth version 2.0: a major expansion and update of the human disease methylation database.

TL;DR: The human disease methylation database (DiseaseMeth, http://bioinfo.hrbmu.edu.cn/diseasemeth/) is an interactive database that aims to present the most complete collection and annotation of aberrant DNA methylation in human diseases, especially various cancers.
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SEA: a super-enhancer archive.

TL;DR: A specifically designed web-accessible database, Super-Enhancer Archive, which focuses on integrating super-enhancers in multiple species and annotating their potential roles in the regulation of cell identity gene expression.
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Systematic identification and annotation of human methylation marks based on bisulfite sequencing methylomes reveals distinct roles of cell type-specific hypomethylation in the regulation of cell identity genes

TL;DR: An entropy-based framework termed SMART is proposed to integrate the whole genome bisulfite sequencing methylomes across 42 human tissues/cells and helps to elucidate the critical features and functions of cell type-specific hypomethylation.
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Specific breast cancer prognosis-subtype distinctions based on DNA methylation patterns

TL;DR: Specific classifications by DNA methylation can explain the heterogeneity of previous molecular subgroups in breast cancer and will help in the development of personalized treatments for the new specific subtypes.
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Integrated analysis of the prognostic role of the lymph node ratio in node-positive gastric cancer: A meta-analysis.

TL;DR: LNR was associated with a significantly poorer OS and LNR was an independent predictor of survival in patients with gastric cancer and should be added as one of the parameters to be used in future tumor staging classification systems.