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RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

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Updated: Jan 9, 2026

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

一个DSSM网络用于推断和优先考虑单细胞RNA-seq数据的细胞类型特定调节.

Yaxin Fan¹, Yichao Mei¹, Shengbao Bao¹

¹Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, 430070, China.

BMC bioinformatics

|December 7, 2025

概括

本研究介绍了推断规则的深度结构语义模型 (DSSMReg),这是一种用于识别细胞类型特定基因调节网络的新方法. DSSMReg使用单细胞转录组数据准确地优先考虑调节,优于现有的算法.

关键词:

细胞类型特异性细胞类型特异性深度学习是一种深度学习.深度结构化的语义模型.在 Regulon Regulon 中使用.这就是scRNA-seqq.

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Single-cell RNA Sequencing and Analysis of Human Pancreatic Islets

Single-cell RNA Sequencing and Analysis of Human Pancreatic Islets

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Last Updated: Jan 9, 2026

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

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科学领域:

计算生物学计算生物学
基因组学就是基因组学.
生物信息学是一种生物信息学.

背景情况:

基因调节依赖于转录因子和向基因,形成细胞类型特定的调节.
整合多样化的数据集,如单细胞转录组和ChIP-seq,对于识别活跃的 regulons 是具有挑战性的.
了解细胞类型特定的调节素对于破译细胞功能和疾病机制至关重要.

研究的目的:

开发一个计算模型来准确推断和优先考虑细胞类型特定的规则.
解决整合单细胞转录组和转录因子基因数据的挑战.
为分析不同细胞类型的基因调节网络提供强大的工具.

主要方法:

开发了一个深度结构语义模型 (DSSMReg).
DSSMReg使用单细胞转录组和基因数据将转录因子和目标基因映射到一个低维的语义空间中.
代数相似度计算了调节强度,AUCell算法对调节的重要性进行了排名.

主要成果:

与其他五种基因调节推理算法相比,DSSMReg表现出优异的性能,实现了高AUROC和AUPRC指标.
该模型成功地从三阴性乳腺癌和造血干细胞数据集中推断出细胞类型特定的规律.
发现高AUCell分数的规则显示出显著的生物相关性.

结论:

DSSMReg是一种高效的工具,可以从单细胞RNA测序数据中推断和优先考虑细胞类型特定的调节子.
该方法为各种生物环境中的基因调节机制提供了宝贵的见解.
源代码是公开可用的,用于更广泛的研究应用.