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相关概念视频

Proteomics01:33

Proteomics

9.2K
A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
9.2K

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相关实验视频

Updated: Jan 11, 2026

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
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Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools

Published on: August 19, 2025

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科伊纳:为蛋白质组学研究实现机器学习的民主化

Ludwig Lautenbacher1,2, Kevin L Yang3, Tobias Kockmann4

  • 1Computational Mass Spectrometry, Technical University of Munich (TUM), Freising, Germany.

Nature communications
|November 11, 2025
PubMed
概括
此摘要是机器生成的。

我们介绍Koina,一个用于蛋白质学中的机器学习 (ML) 模型的开源存储库. 科伊纳提高了模型的可访问性和集成到数据分析管道中,加速了 ML 在现场采用.

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Shotgun Proteomics Sample Processing Automated by an Open-Source Lab Robot
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JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
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相关实验视频

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科学领域:

  • 蛋白质组学是指蛋白质组学.
  • 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:

  • 机器学习 (ML) 和深度学习显示出蛋白质组学应用的前景,例如光谱图书馆生成和鉴定.
  • 蛋白质组学中新型ML模型的缓慢采用受阻于难以找到,可访问性和整合性挑战.
  • 现有的蛋白质组学软件往往缺乏用于整合新型ML模型的直接方法.

研究的目的:

  • 介绍Koina,一个开源的,分散的,在线可访问的蛋白质组学ML模型库.
  • 在蛋白质组学社区中促进ML模型的发布,发现和可用性.
  • 为了证明ML模型的无集成到现有的蛋白质组学数据分析工作流中.

主要方法:

  • 开发Koina,一个开源的,分散的,在线可访问的ML模型库平台.
  • 实现一个易于使用的在线界面来访问和使用ML模型.
  • 将Koina与用于蛋白质组学数据分析的FragPipe计算平台进行集成.

主要成果:

  • 科伊纳为蛋白质组学中的ML模型可查和可访问性提供了一个集中的解决方案.
  • 该平台可以将ML模型直接集成到已建立的数据分析管道中.
  • 与FragPipe成功集成,展示了改进的蛋白质组学数据分析能力.

结论:

  • 科伊纳显著降低了在蛋白质组学研究中采用ML模型的障碍.
  • 该存储库促进了最终用户对ML模型的可复制性和可重复使用性.
  • 科伊纳代表了计算蛋白质组学的关键进步,使得ML的更广泛应用成为可能.