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相关概念视频

Background and Environment Affect Phenotype02:27

Background and Environment Affect Phenotype

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Although the genetic makeup of an organism plays a major role in determining the phenotype, there are also several environmental factors, such as temperature, oxygen availability, presence of mutagens, that can alter an organism’s phenotype.
An example of how genetic background affects phenotype can be seen in horses. The Extension gene in horses is responsible for their coat color. A wild-type gene (EE) produces black pigment in the coat, while a mutant gene (ee) produces red pigment. A...
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相关实验视频

Updated: Jan 8, 2026

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
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通过分析特定上下文的转录组学数据来建模可靠的代谢表型.

Pavan Kumar S1,2,3, Nirav Pravinbhai Bhatt4,5,6,7

  • 1BioSystems Engineering and Control (BiSECt) Lab, Department of Biotechnology, Indian Institute of Technology Madras (IIT Madras), Chennai, Tamil Nadu, India.

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概括
此摘要是机器生成的。

一个新的算法Localgini通过分析基因表达变异性来增强代谢模型. 这种方法准确地识别了特定背景模型的活性代谢反应,改善了生物洞察力.

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High-Throughput Metabolic Profiling for Model Refinements of Microalgae
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Metabolic Labeling of Newly Transcribed RNA for High Resolution Gene Expression Profiling of RNA Synthesis, Processing and Decay in Cell Culture
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科学领域:

  • 计算生物学是一种计算生物学.
  • 系统生物学 系统生物学
  • 代谢建模 代谢建模

背景情况:

  • 基因组规模代谢模型 (GEMs) 提供了对细胞代谢的洞察力,但往往缺乏特定背景的细节.
  • 转录组数据集成是完善疾病和细胞状态的GEM的关键.
  • 目前的方法在准确识别上下文依赖的代谢适应方面扎.

研究的目的:

  • 介绍"Localgini",一种使用基尼系数量化基因表达变异的算法.
  • 开发一种方法,从GEM和转录组数据中构建准确的上下文特定模型 (CSM).
  • 提高用于研究细胞适应性的GEMs的特异性.

主要方法:

  • 开发了Localgini算法来测量样本中的基因表达异质性.
  • 应用Localgini以使用NCI-60癌细胞系和人体组织的转录组数据生成CSM.
  • 根据六种不同的模型提取方法 (MeM) 评估了Localgini.

主要成果:

  • 基于Localgini的CSM证明了改善了家政功能和已知的代谢途径的表现.
  • 由Localgini发现的活性反应集需要MeMs的最小支持.
  • 在具有相同表达数据的不同MeM中生成的CSM中,Localgini降低了CSM的变异性.

结论:

  • 通过整合基因表达异质性,Localgini提供了一种准确的方法来构建特定环境的代谢模型.
  • 该算法增强了GEMs的生物相关性和特异性.
  • 洛卡尔吉尼在各种环境中促进了对细胞代谢的更可靠的计算研究.