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相关概念视频

Data Reporting and Recording01:24

Data Reporting and Recording

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Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...
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Quartile01:15

Quartile

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Quartiles are numbers that separate the data into quarters. Quartiles may or may not be part of the data. To find the quartiles, first, find the median or second quartile. The first quartile, Q1, is the middle value of the lower half of the data, and the third quartile, Q3, is the middle value, or median, of the upper half of the data. To get the idea, consider the same data set:
1; 1; 2; 2; 4; 6; 6.8; 7.2; 8; 8.3; 9; 10; 10; 11.5
The median or second quartile is seven. The lower half of the...
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Lineage Commitment01:21

Lineage Commitment

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Commitment is the  process whereby stem cells:
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Percentile01:18

Percentile

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A percentile indicates the relative standing of a data value when data are sorted into numerical order from smallest to largest. It represents the percentages of data values that are less than or equal to the pth percentile. For example, 15% of data values are less than or equal to the 15th percentile.
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Confidence Coefficient01:24

Confidence Coefficient

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The confidence coefficient is also known as the confidence level or degree of confidence. It is the percent expression for the probability, 1-α, that the confidence interval contains the true population parameter assuming that the confidence interval is obtained after sufficient unbiased sampling; for example, if the CL = 90%, then in 90 out of 100 samples the interval estimate will enclose the true population parameter. Here α is the area under the curve, distributed equally under...
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Quality Assurance01:19

Quality Assurance

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Quality assurance is the overarching term used to describe the activities employed to ensure the proper performance of a system. These activities can be classified into three categories: quality control, quality assessment, and internal corrective measures. Typically, these activities work cyclically: quality control is performed before and during the analysis, while quality assessment occurs during and after the investigation. Internal corrective measures are implemented based on the findings...
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Updated: Jun 8, 2025

The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time
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20年后的PRIDE数据库:2025年更新

Yasset Perez-Riverol1, Chakradhar Bandla1, Deepti J Kundu1

  • 1European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.

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概括

蛋白质组学IDEntifications (PRIDE) 数据库通过改进的基础设施和像聊天机器人这样的新工具来增强蛋白质组学数据共享. 它现在每月支持超过534个数据集,提高了数据的可访问性和重用性.

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科学领域:

  • 生物化学 生物化学
  • 生物信息学是一种生物信息学.
  • 数据科学数据科学数据科学

背景情况:

  • 蛋白质组学IDEntifications (PRIDE) 数据库是基于质谱 (MS) 的蛋白质组学数据的领先存储库.
  • 它是ProteomeXchange联盟的关键成员,促进数据标准化和共享.
  • 持续开发对于管理日益增长的蛋白质组学数据量至关重要.

研究的目的:

  • 总结过去三年中PRIDE数据库及其相关工具的最新发展和改进.
  • 突出基础设施,数据提交管道和新功能方面的进步.
  • 展示数据再利用和传播到其他有价值的生物资源的努力.

主要方法:

  • 基础设施的增强,包括Globus用于大型文件传输和自动验证流程.
  • 开发一个新的数据再提交管道.
  • 为PRIDE聊天机器人集成开源大型语言模型,并改进对MS交联数据的支持.

主要成果:

  • 骄傲档案每月平均收到534个新数据集,这表明数据提交量增加了.
  • 在数据提交,验证和传输效率方面显著改进.
  • 引入聊天机器人,并加强对专业数据集的支持,如交叉连接实验.

结论:

  • PRIDE成功地扩展了其基础设施,并引入了创新的工具来管理和支持不断增长的蛋白质组学数据量.
  • 这些进步促进了更容易的数据提交,验证和可访问性.
  • 增强数据的重复使用和传播到像UniProt和Ensembl这样的资源中,最大限度地提高了提交的蛋白质组学数据的价值.