Search research articles

相关概念视频

Synthetic Biology

Synthetic Biology

Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
Golden rice
Golden rice is a genetically modified...

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序

Same author

Spatial epitranscriptomics: from Cinderella to queen.

Nature methods·2026

Same author

Gene mutant dosage is associated with prognosis and metastatic tropism in 60,000 clinical cancer samples.

medRxiv : the preprint server for health sciences·2026

Same author

The histone methyltransferase NSD3 oncogene triggers ribosomal DNA transcription, interfering with FOSL2 in cancer.

Cell death & disease·2026

Same author

DPY30 Is an Epigenetic Decoupler Linking Replication Stress to Immunoediting in Pancreatic Cancer.

Cancer research·2026

Same author

TIGIT disruption rescues the antitumor activity of low avidity TCR-engineered T cells by increasing TCR signal strength.

Nature communications·2026

Same author

Comprehensive analysis of mutational processes across 20 000 adult and pediatric tumors.

Nucleic acids research·2025

关于 JoVE

概览领导团队博客 JoVE 帮助中心

作者

出版流程编辑委员会范围与政策同行评审常见问题投稿

图书馆员

用户评价订阅访问资源图书馆顾问委员会常见问题

研究

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments 存档

教育

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual 教师资源中心教师网站

使用条款与条件

Search research articles

相关实验视频

Updated: May 3, 2026

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

使用生成式对抗网络,可扩展地整合多原子单细胞数据.

Valentina Giansanti^1,2, Francesca Giannese², Oronza A Botrugno^3,4

¹Department of Informatics, Systems and Communication, Università degli Studi di Milano-Bicocca, Milan, 20125, Italy.

Bioinformatics (Oxford, England)

|May 2, 2024

概括

这项研究介绍了一种新的Multi-Omic数据集成框架,使用了Wasserstein生成对抗网络. 这种方法有效地整合了单细胞中的多个分子层,克服了当前的计算限制.

更多相关视频

Reusable Single Cell for Iterative Epigenomic Analyses

Reusable Single Cell for Iterative Epigenomic Analyses

Published on: February 11, 2022

Author Spotlight: Integrating Organoid Models with Single-Cell and Spatial Transcriptomics Technologies

Author Spotlight: Integrating Organoid Models with Single-Cell and Spatial Transcriptomics Technologies

Published on: March 29, 2024

相关实验视频

Last Updated: May 3, 2026

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

Reusable Single Cell for Iterative Epigenomic Analyses

Reusable Single Cell for Iterative Epigenomic Analyses

Published on: February 11, 2022

Author Spotlight: Integrating Organoid Models with Single-Cell and Spatial Transcriptomics Technologies

Author Spotlight: Integrating Organoid Models with Single-Cell and Spatial Transcriptomics Technologies

Published on: March 29, 2024

科学领域:

计算生物学是一种计算生物学.
基因组学就是基因组学.
多个omics的分析分析.

背景情况:

单细胞分析对于理解生物复杂性至关重要.
技术进步使单细胞的多原子测量 (基因组,表观基因组,蛋白质组) 成为可能.
现有的计算框架难以整合两个以上的分子数据类型.

研究的目的:

从单细胞数据中集成多个分子层的计算框架.
为了解决当前处理 >2 omic 模式的方法的局限性.
通过全面的单细胞数据分析,促进更深入的生物学见解.

主要方法:

开发一个名为MOWGAN的多OMIC数据集成框架.
使用Wasserstein生成对抗网络 (WGAN) 来进行数据集成.
采用一个单一的网络,训练所有模式,以减少计算负担.

主要成果:

拟议的框架成功地集成了来自单个单元格的多个omic数据类型 (> 2).
它可以处理配对和不配对的多原子数据集.
单一网络方法可以有效地管理高维的多原子数据.

结论:

MOWGAN框架为多原子单细胞数据集成提供了一个可扩展的解决方案.
它通过结合多样化的分子信息来分析复杂的生物系统.
该框架推进了单细胞多组体分析领域.