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An ogive graph is sometimes called a cumulative frequency polygon. It is one type of frequency polygon that shows cumulative frequency. In other words, the cumulative percentages are added to the graph from left to right. An ogive graph plots cumulative frequency on the vertical y-axis and class boundaries along the horizontal x-axis. It’s very similar to a histogram; only instead of rectangles, an ogive displays a single point where the top right of the rectangle would be. Creating this...
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Graphing Antiderivatives01:30

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The concept of an antiderivative is fundamental in calculus, describing how a function's values accumulate over time. This process is closely related to physical motion, such as the movement of a rolling ball. As the ball progresses, its position changes in response to variations in velocity, just as an antiderivative graph reflects the cumulative effect of the original function's values.Graphing an antiderivative requires interpreting how a function's values influence the shape of its...
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Graphs of functions provide a visual representation of how output values change in response to varying inputs. Each point on the graph corresponds to an ordered pair, where the x-coordinate (independent variable) determines the horizontal position and the y-coordinate (dependent variable) determines the vertical position. Linear functions like y = x give a straight line, indicating a constant rate of change.Nonlinear functions display more complex behaviors. Even power functions generate...
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A bar graph is also called a bar chart and consists of bars that are separated from each other. It either uses horizontal or vertical bars to show comparisons among categories. The bars can be rectangles, or they can be rectangular boxes (used in three-dimensional plots). One axis of the graph represents the specific categories being compared, and the other axis shows a discrete value. In this graph, the length of the bar for each category is proportional to the number or percent of individuals...
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一个可搜索的元数据网络图表,用于微生物组代谢学.

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    微生物组MASST在各种数据集中绘制微生物代谢物的地图,将质谱数据与生物背景联系起来. 这一框架揭示了肠道细菌如何通过脱来使像埃纳拉普利尔这样的药物失活.

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    科学领域:

    • 微生物组研究的研究.
    • 代谢学 代谢学 代谢学
    • 生物信息学是一种生物信息学.

    背景情况:

    • 识别微生物代谢物及其生物作用是具有挑战性的.
    • 现有的数据是分散在许多研究和样本类型.

    研究的目的:

    • 开发一个基于元数据的网络图 (microbiomeMASST) 用于绘制微生物代谢物的地图.
    • 整合多样化的质谱数据集,进行交叉研究分析和生物背景化.

    主要方法:

    • 编制了467个数据集,其中包括来自人类,动物和微生物来源的144,424个质谱档案.
    • 来自单一种植,合成社区和宿主相关样本的综合数据.
    • 开发了一个可查询的网络图表,以追踪跨主机,条件和干预措施的代谢物发生情况.

    主要成果:

    • 对微生物结合胆酸进行了上下文化研究,并研究了微生物组介导的药物代谢.
    • 确定了消化肠道细菌,这些细菌消化了 ACE 抑制剂前药物 enalapril.
    • 在人类,微生物,环境和大猩猩样本中追踪了代谢物,证明了ACE抑制的丧失.

    结论:

    • 微生物组MASST有效地将质谱学/质谱学光谱与生物环境联系起来.
    • 该框架允许将孤立的观测解释为一个全面的微生物组地图.
    • 埃纳拉普利的微生物降解使其治疗效果失活,突出显示了药物代谢相互作用.