BCMA:一个综合性的多尺度和多组学乳腺癌分子图谱数据库。

IF 4.1 2区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Computational and structural biotechnology journal Pub Date : 2025-06-20 eCollection Date: 2025-01-01 DOI:10.1016/j.csbj.2025.06.031
Wenbo Guo, Zikang Yin, Qinglin Mei, Lianshuo Li, Yonghui Gong, Xinqi Li, Wei Zhang, Wenjie Lei, Bingqiang Liu, Lin Hou, Mei Yang, Jin Gu
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引用次数: 0

摘要

乳腺癌(BC)是全世界女性中最常见的癌症类型之一。了解BC复杂的分子和细胞特征对于推进精准治疗至关重要。为了获得更可靠和可重复的生物学发现,从不同的BC队列中收集分子数据并建立一个综合的、通用的分析平台至关重要。在这里,我们提出BCMA(乳腺癌分子图谱,http://lifeome.net/database/bcma/),一个多尺度,多组学BC数据库,包括6个批量多组学数据集和9个单细胞转录组学数据集,共覆盖5424例和236,363个细胞。BCMA系统地表征了BC的分子特征,包括基因突变、拷贝数改变、RNA表达、miRNA表达、DNA甲基化以及临床表型和细胞异质性。同时,提供以基因为中心的搜索界面,实现临床信息统计、基因组事件分析、差异多组学特征鉴定、功能富集分析、生存分析、共表达分析以及单细胞基因表达谱分析和细胞类型标注。该平台在增强对BC分子特征的理解和促进疾病相关生物标志物的识别方面具有巨大的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
BCMA: An integrative and versatile database for multi-scale and multi-omics molecular atlas of breast cancer.

Breast cancer (BC) is one of the most common cancer types among women worldwide. Understanding the complex molecular and cellular characteristics of BC is crucial for advancing precision treatment. To enable more reliable and reproducible biological discoveries, it is critical to collect molecular data from diverse BC cohorts and establish an integrative, versatile analysis platform. Here, we present BCMA (Breast Cancer Molecular Atlas, http://lifeome.net/database/bcma/), a multi-scale, multi-omics BC database that encompasses 6 bulk multi-omics datasets and 9 single-cell transcriptomics datasets, collectively covering 5424 cases and 236,363 cells. The BCMA systemically characterizes the molecular features of BC, including gene mutations, copy number alterations, RNA expression, miRNA expression, DNA methylation, as well as clinical phenotypes and cell heterogeneity. Meanwhile, a user-friendly interface for gene-centered search is provided, achieving the clinical information statistics, genomic events analysis, differential multi-omics feature identification, functional enrichment analysis, survival analysis, co-expression analysis, as well as single-cell gene expression profiling and cell type annotation. This platform holds great potential to enhance the understanding of molecular characteristics underlying BC and to facilitate the identification of disease-associated biomarkers.

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来源期刊
Computational and structural biotechnology journal
Computational and structural biotechnology journal Biochemistry, Genetics and Molecular Biology-Biophysics
CiteScore
9.30
自引率
3.30%
发文量
540
审稿时长
6 weeks
期刊介绍: Computational and Structural Biotechnology Journal (CSBJ) is an online gold open access journal publishing research articles and reviews after full peer review. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to: Structure and function of proteins, nucleic acids and other macromolecules Structure and function of multi-component complexes Protein folding, processing and degradation Enzymology Computational and structural studies of plant systems Microbial Informatics Genomics Proteomics Metabolomics Algorithms and Hypothesis in Bioinformatics Mathematical and Theoretical Biology Computational Chemistry and Drug Discovery Microscopy and Molecular Imaging Nanotechnology Systems and Synthetic Biology
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