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ER is the primary site for the maturation and folding of soluble and transmembrane secretory proteins. The calnexin cycle is a specific chaperone system that folds and assesses the confirmation of N-glycosylated proteins before they can exit the ER lumen. The primary players of this quality check pipeline are the lectins, ER-resident chaperones, and a glucosyl transferase enzyme. In case the calnexin system in the lumen fails to salvage a misfolded protein, it is transported to the cytoplasm...
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The mass analyzer is a crucial component of the mass spectrometer. In the ionization chamber, the vaporized sample is bombarded with a high-energy electron beam to generate a radical cation and further fragment into neutral molecules, radicals, and cations. A series of negatively charged accelerator plates accelerate the cations into the mass analyzer. The mass analyzer separates ions according to their mass-to-charge (m/z) ratios and then directs them to the detector. The common types of mass...
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The underlying principle of Raman spectroscopy is based on the interaction between light and matter, specifically molecules' inelastic scattering of photons. When a monochromatic beam of light, typically from a laser source, interacts with a sample, most scattered light has the same frequency as the incident light. This is known as Rayleigh scattering.
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A conventional Raman spectrophotometer includes a laser source, a sample holding system, a wavelength selector, and a detector.
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spammR:一个用于分析和整合空间多原子测量的R包

Yannick Mahlich, Harkirat Sohi, Paul Piehowski

    bioRxiv : the preprint server for biology
    |September 5, 2025
    PubMed
    概括

    一个新的R包,spammR,提供空间数据分析工具,特别是质谱. 它解决了样本规模小和数据缺失等挑战,使数据驱动的洞察力从空间多层次的测量中获得.

    科学领域:

    • 空间经济学和多经济学一体化
    • 计算生物学和生物信息学
    • 基于质谱的欧米分析

    背景情况:

    • 空间奥米克技术迅速发展,使得分子数据的高分辨率测量成为可能.
    • 目前的分析工具主要支持空间转录组,限制了其他类型的应用.
    • 基于质谱的空间奥米克数据集具有独特的挑战,包括小样本大小,空间稀疏性和缺失的数据.

    研究的目的:

    • 介绍spammR,一个用于端到端分析空间数据的R包.
    • 专门解决质谱学衍生空间奥米克数据集的分析挑战.
    • 在没有对特定基因或蛋白质的先验知识的情况下,提供数据驱动的方法来分析空间多组测量.

    主要方法:

    • 开发用于空间数据分析的spammRR包.
    • 适用于小样本大小,空间稀疏性和质谱学中常见的缺失数据的方法的实施.
    • 专注于完全数据驱动的分析框架.

    主要成果:

    • spammR能够对空间数据进行全面分析,特别是来自质谱的数据.
    • 该套件有效处理具有有限样本和显著缺失值的数据集.
    • 它有助于数据驱动的空间多态图案的探索.

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    结论:

    • spammR为推进基于质谱的空间奥米学研究提供了有价值的计算工具.
    • 该方案将对具有挑战性的空间多态数据集的分析进行民主化.
    • 通过强大,数据驱动的空间分析来支持新发现.