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相关概念视频

Combinatorial Gene Control02:33

Combinatorial Gene Control

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Combinatorial gene control is the synergistic action of several transcriptional factors to regulate the expression of a single gene. The absence of one or more of these factors may lead to a significant difference in the level of gene expression or repression.
The expression of more than 30,000 genes is controlled by approximately 2000-3000 transcription factors. This is possible because a single transcription factor can recognize more than one regulatory sequence. The specificity in gene...
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Regulation of Expression at Multiple Steps01:23

Regulation of Expression at Multiple Steps

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The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors—these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5' capping, splicing, and the...
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Constitutive and Regulated Gene Expression01:27

Constitutive and Regulated Gene Expression

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Gene expression in prokaryotes is governed by constitutive and regulated systems, allowing cells to balance the production of essential proteins with adaptive responses to environmental changes.Constitutive Gene ExpressionConstitutive, or housekeeping, genes are continuously expressed as they encode proteins vital for fundamental cellular processes. These include enzymes for glycolysis, ribosomal components for protein synthesis, and proteins involved in DNA replication. Their constant...
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Master Transcription Regulators02:23

Master Transcription Regulators

7.7K
Master transcription regulators are regulatory proteins that are predominantly responsible for regulating the expression of multiple genes. Often these genes work in concert to drive a  complex process. Activation of a master transcription regulator can lead to a cascade of transcriptional activation necessary for that outcome. These regulators can directly bind to the regulatory sequences of the various genes involved, or they can indirectly regulate transcription by binding to regulatory...
7.7K
Cis-regulatory Sequences02:02

Cis-regulatory Sequences

11.6K
Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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相关实验视频

Updated: Jan 17, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
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机器学习方法用于基因调节网络推断推断的基因调节网络.

Akshata Hegde1,2, Tom Nguyen1,2, Jianlin Cheng1,2

  • 1Department of Electrical Engineering and Computer Science, University of Missouri, 416 S 6th St, Columbia, MO 65201, United States.

Briefings in bioinformatics
|September 18, 2025
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概括
此摘要是机器生成的。

这篇评论探讨了用于推断基因调节网络 (GRNs) 的机器学习,并突出了AI.

关键词:
在 GRN GRN GRN 中.深度学习是一种深度学习.基因监管网络 基因监管网络推理推论是指一个推理.机器学习是机器学习.俄米克斯 (omicsics) 是一个电子产品.

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科学领域:

  • 计算生物学和生物信息学
  • 基因组学和系统生物学

背景情况:

  • 基因调节网络 (GRNs) 控制基因表达以响应生物信号.
  • 高通量测序和计算生物学已经推进了GRN推理.
  • 人工智能 (AI),特别是机器学习 (ML),对于分析omics数据以了解基因相互作用至关重要.

研究的目的:

  • 提供基于ML的GRN推断方法的全面审查.
  • 支持GRN推理的应用和新的ML方法的开发.
  • 讨论数据集,评估指标和GRN推断中的挑战.

主要方法:

  • 对GRN推断的监督,无监督,半监督和对比学习技术的审查.
  • 分析常用的数据集和现场评估指标.
  • 强调深度学习方法,以提高推断性能.

主要成果:

  • 人工智能和机器学习技术显著提高了GRN推断的准确性.
  • 深度学习方法在提高GRN推理性能方面表现有前途.
  • 确定了用于评估GRN推理模型的常用数据集和指标.

结论:

  • 机器学习,特别是深度学习,是破译复杂GRN的强大工具.
  • 对新的ML方法和解决当前挑战的进一步研究将推动GRN推断.
  • 本综述是GRN推断和ML开发研究人员的指南.