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Antibodies, also known as immunoglobulins (Ig), are essential players of the adaptive immune system. These antigen-binding proteins are produced by B cells and make up 20 percent of the total blood plasma by weight. In mammals, antibodies fall into five different classes, which each elicits a different biological response upon antigen binding.
The Y-Shaped Structure of Antibodies Consists of Four Polypeptide Chains
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Allergic reactions related to drugs are hypersensitivity responses driven by the immune system and bear no connection to the drug's therapeutic action. While drugs in isolation do not trigger an immune response, they can interact with endogenous proteins to form antigens. These antigens stimulate lymphocytes to produce antibodies. IgE-type antibodies attach themselves to mast cells. Upon subsequent exposure to the same stimulus, the antigen-antibody interaction is initiated, unleashing...
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Antigens Involved in Adaptive Immunity01:26

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An antigen is any substance the immune system identifies as foreign and potentially harmful to the body, prompting an immune response. Antigens have two functional properties: immunogenicity and reactivity. Immunogenicity is the ability of an antigen to stimulate a specific immune response. At the same time, reactivity describes the antigen's ability to react with the cells and antibodies produced in response to it.
Complete Antigens
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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.
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Application of Biochip Microfluidic Technology to Detect Serum Allergen-specific Immunoglobulin E sIgE
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基于深度学习的组合方法用于蛋白质过敏原分类.

Arun Kumar1, Prashant Singh Rana1

  • 1Computer Science and Engineering, Thapar Institute of Engineering and Technology, Patiala, Punjab, India.

PeerJ. Computer science
|October 23, 2023
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种深度学习组合模型,用于检测加工食品中的蛋白质过敏原. 新方法准确地识别出潜在的过敏原,这对于预防过敏反应至关重要.

关键词:
过敏反应过敏反应生物信息学是一种生物信息学.深度学习是一种深度学习.组合学习学习 组合学习机器学习 机器学习蛋白质过敏原是一种蛋白质过敏原.

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科学领域:

  • 生物信息学是一种生物信息学.
  • 计算生物学 计算生物学
  • 食品科学 食品科学 食品科学

背景情况:

  • 全球人口的增加推动了对加工食品的需求,通常涉及蛋白质修饰.
  • 食品加工中的蛋白质修饰可以无意中产生蛋白质过敏原,造成健康风险.
  • 精确检测蛋白质过敏原对于食品安全,诊断和过敏管理至关重要.

研究的目的:

  • 开发和评估用于识别蛋白质过敏原的计算方法.
  • 为了提高过敏原检测准确度,利用深度学习和组合技术.
  • 为检测食品中的潜在过敏原提供一个强大的工具.

主要方法:

  • 使用了结合Extra Tree,Deep Belief Network (DBN) 和CatBoost模型的深度学习组合方法.
  • 员工多数投票,以整合来自单个模型的预测,以提高准确性.
  • 在标准蛋白质过敏原数据集上评估模型的性能.

主要成果:

  • 拟议的整体模型实现了高蛋白质过敏原检测准确率的89.16%.
  • 与现有的最先进的方法相比,整体方法显示出更高的性能.
  • 该模型有效地从氨基酸序列数据中识别出潜在的蛋白质过敏原.

结论:

  • 深度学习组合模型为蛋白质过敏原检测提供了一个有希望和准确的方法.
  • 计算方法,特别是深度学习,是食品安全和过敏管理的有效工具.
  • 这项研究有助于预防和诊断与食物相关的过敏状况.