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相关概念视频

Proteomics01:33

Proteomics

7.2K
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...
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Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

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Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...
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Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
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血统过器:使用元蛋白组学和机器学习改进复杂样本的原型化.

Hamid Hachemi1,2, Jean Armengaud1, Lucia Grenga1

  • 1Département Médicaments et Technologies pour la Santé (DMTS), Université Paris-Saclay, CEA, INRAE, SPI, 30200 Bagnols-sur-Cèze, France.

Journal of proteome research
|October 19, 2024
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概括

LineageFilter是一款新的人工智能软件,用于完善复杂微生物样本的metaproteomics分析. 它通过使用机器学习来评估分类种的存在来改善分类学分类,有助于准确的样本特定数据库构建.

关键词:
机器学习是机器学习.形态保护学与社会主义.微生物组就是微生物组.蛋白质类型的形成.分类学 分类学.

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A Clinical Metaproteomics Workflow Implemented within Galaxy Bioinformatics Platform to Analyze Host-Microbiome Interactions Underlying Human Disease
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An Aquatic Microbial Metaproteomics Workflow: From Cells to Tryptic Peptides Suitable for Tandem Mass Spectrometry-based Analysis
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科学领域:

  • 微生物学 微生物学
  • 生物信息学是一种生物信息学.
  • 蛋白质组学是指蛋白质组学.

背景情况:

  • 甲基蛋白学分析微生物蛋白质含量,以了解微生物群的功能.
  • 从元蛋白质组数据中精确地对复杂微生物群落进行分类学分析是具有挑战性的.
  • 目前的方法难以精确识别,仅基于序列.

研究的目的:

  • 为了介绍LineageFilter,一个基于Python的AI软件.
  • 为了使复杂样本的精细蛋白型化使用元蛋白质组学数据和机器学习.
  • 提高微生物群落分类组合评估的准确性.

主要方法:

  • LineageFilter使用机器学习算法.
  • 它从metaproteomic数据处理分类列表,丰度和分数.
  • 该软件计算了所有分类学等级的分类群特定特征.

主要成果:

  • LineageFilter根据计算的特征评估了分类种存在的可能性.
  • 它为复杂的微生物样本提供了精细的蛋白型.
  • 该软件有助于构建特定样本的数据库.

结论:

  • LineageFilter增强了对微生物群体分析的元蛋白质组数据的解释.
  • 由人工智能驱动的方法提高了分类学分辨率和准确性.
  • 这个工具有助于更深入地了解微生物生态系统的功能.