Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
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 JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

RNA-seq03:21

RNA-seq

9.7K
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...
9.7K

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

Synergistic engineering of Casδ nuclease for robust genome editing.

Journal of integrative plant biology·2026
Same author

Global prevalence and associated risk factors of work-related musculoskeletal disorders among steelworkers: a systematic review and meta-analysis.

Frontiers in public health·2026
Same author

SpaBalance: Balanced Learning for Efficient Spatial Multi-Omics Decoding.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2025
Same author

Weakly space-confined all-inorganic perovskites for light-emitting diodes.

Nature·2025
Same author

Atomic-Scale Insights into Flexoelectricity and the Enhanced Photovoltaic Effect at the Grain Boundary in Halide Perovskites.

Nano letters·2025
Same author

GCPNet: An interpretable Generic Crystal Pattern graph neural Network for predicting material properties.

Neural networks : the official journal of the International Neural Network Society·2025
Same journal

OpenIMC: an open-source platform for analyzing single-cell and spatial proteomics by imaging mass cytometry.

BMC bioinformatics·2026
Same journal

NAP: an open source pipeline for cross-domain microbiome profiling using Nanopore sequencing-derived amplicon data.

BMC bioinformatics·2026
Same journal

SurvGME: an R package for survival analysis with graphical and measurement error models.

BMC bioinformatics·2026
Same journal

SimMapNet: a Bayesian framework for gene regulatory network inference using gene ontology similarities as external hint.

BMC bioinformatics·2026
Same journal

Dual channel drug-drug interactions extraction based on cross attention.

BMC bioinformatics·2026
Same journal

FeSseqdb: a curated sequence-level database and interpretable machine learning framework for identifying iron-sulfur proteins.

BMC bioinformatics·2026
查看所有相关文章

相关实验视频

Updated: May 9, 2025

Ultra-long Read Sequencing for Whole Genomic DNA Analysis
10:34

Ultra-long Read Sequencing for Whole Genomic DNA Analysis

Published on: March 15, 2019

22.6K

快速杂的长阅读对齐与多层次并行性.

Zeyu Xia1, Canqun Yang1,2,3, Chenchen Peng1

  • 1College of Computer Science and Technology, National University of Defense Technology, 410073, Changsha, China.

BMC bioinformatics
|May 2, 2025
PubMed
概括
此摘要是机器生成的。

ParaHAT是一种新的并行对齐算法,旨在从单分子实时 (SMRT) 测序进行噪音较大的长读取. 它通过克服单个CPU的局限性来显著加快数据分析的速度.

关键词:
不同质的平行化异质的平行化在MPI中,MPI是MPI.平行处理是平行处理.这就是 SMRT 的意思.序列对齐方式 序列对齐方式在矢量级平行化上进行向量级平行化.

更多相关视频

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

15.1K
G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome
06:40

G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome

Published on: March 22, 2018

5.7K

相关实验视频

Last Updated: May 9, 2025

Ultra-long Read Sequencing for Whole Genomic DNA Analysis
10:34

Ultra-long Read Sequencing for Whole Genomic DNA Analysis

Published on: March 15, 2019

22.6K
Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

15.1K
G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome
06:40

G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome

Published on: March 22, 2018

5.7K

科学领域:

  • 基因组学就是基因组学.
  • 生物信息学是一种生物信息学.
  • 计算生物学 计算生物学

背景情况:

  • 第二代测序具有诸如短读长度和PCR偏差等局限性.
  • 单分子实时 (SMRT) 测序提供了更长的读数,但产生了大量的数据,并具有很高的错误率.
  • 由于读取长度,错误率和单个CPU性能瓶,现有的对齐工具与SMRT数据扎.

研究的目的:

  • 开发一种高效的平行对齐算法,用于SMRT测序产生的噪声长读数.
  • 为应对数据量增加和SMRT数据错误率所带来的计算挑战.
  • 为了克服单个CPU对序列对齐的性能限制.

主要方法:

  • 介绍ParaHAT,一个并行对齐算法,包含向量级,线程级,过程级和异质并行.
  • 重新设计动态编程矩阵以消除数据依赖性,实现有效的向量化以实现基层对齐.
  • 使用消息传递接口 (MPI) 实现多节点计算和异质并行技术以提高速度.

主要成果:

  • 与现有方法相比,ParaHAT实现了10.03倍的基础水平对齐速度.
  • 在128个节点上表现出高平行加速度比率 (94.61%) 和弱可扩展性 (98.98%).
  • 有效地处理杂的长读数,克服单节点处理的计算限制.

结论:

  • ParaHAT提供了一个可扩展和高效的解决方案,用于从SMRT测序对准杂的长读数.
  • 平行架构显著提高了对齐速度和吞吐量.
  • 帕拉哈特克服了关键的计算瓶,使得SMRT数据分析更加可行.