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関連する概念動画

Operon Model01:23

Operon Model

The operon model represents a fundamental mechanism of gene regulation in prokaryotes, enabling coordinated expression of genes involved in related metabolic or functional pathways. Operons consist of structural genes, a promoter, and an operator, with transcription regulated by repressors, activators, and small effector molecules.Structure and Function of OperonsAn operon is a cluster of structural genes transcribed together under the control of a single promoter. The promoter region...
Neural Regulation01:37

Neural Regulation

Digestion begins with a cephalic phase that prepares the digestive system to receive food. When our brain processes visual or olfactory information about food, it triggers impulses in the cranial nerves innervating the salivary glands and stomach to prepare for food.
Organization of Genes02:07

Organization of Genes

Overview
Organization of Genes02:07

Organization of Genes

Overview
Cis-regulatory Sequences02:02

Cis-regulatory Sequences

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...
Cis-regulatory Sequences02:02

Cis-regulatory Sequences

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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関連する実験動画

Updated: May 18, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
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Published on: December 7, 2021

ENCODEデータから派生した人間の規制ネットワークのアーキテクチャ.

Mark B Gerstein1,2,3, Anshul Kundaje4, Manoj Hariharan5

  • 1Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, CT 06520, USA.

Nature
|September 8, 2012
PubMed
まとめ

この研究は,ヒトの転写因子ネットワークをマッピングし,文脈特有の結合と階層的な組織を明らかにしています. 遺伝子調節に関するこれらの洞察は,ヒトの生物学と病気を理解するための鍵です.

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Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

関連する実験動画

Last Updated: May 18, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data
09:47

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data

Published on: December 15, 2023

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

科学分野:

  • ゲノミクスゲノミクスとは
  • システム生物学 システム生物学
  • 分子生物学は分子生物学である.

背景:

  • 遺伝子調節は,特定の組み合わせでDNAを結合する転写因子に依存しています.
  • 人間の転写制御ネットワークを理解することは,細胞機能と疾患の解読に不可欠です.

研究 の 目的:

  • 119人のヒトの転写因子のゲノム結合をマッピングする.
  • これらの因子の結合結合パターンとネットワーク特性を分析する.

主な方法:

  • 転写因子ゲノム結合情報を決定するために450以上の実験を行いました.
  • 組織化された結合データを階層的なネットワークにまとめ,マイクロRNAの調節のような他のゲノムデータと統合した.

主要な成果:

  • 遺伝子に近いもの,遠いものから異なる転写因子の文脈特有の結合結合を特定した.
  • 上位レベルの要因が表現に影響を及ぼし,中位レベルの要因がボトルネックを軽減する階層的なネットワーク構造を明らかにした.
  • ノイズバッファリングフィードフォワードループなど,強化されたネットワークモチーフを発見した.
  • 高度な接続性の高いネットワーク構成要素は,より強い選択を受け,アレル特異的な活性を示していることが判明しました.

結論:

  • 人間の転写制御ネットワークは,複雑で文脈に依存する組織を現しています.
  • この詳細な規制マップは,個人のゲノムを解釈し,ヒトの生物学と病気を理解するための基礎を提供します.