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関連する概念動画

Transcription Factors02:16

Transcription Factors

82.9K
Tissue-specific transcription factors contribute to diverse cellular functions in mammals. For example, the gene for beta globin, a major component of hemoglobin, is present in all cells of the body. However, it is only expressed in red blood cells because the transcription factors that can bind to the promoter sequences of the beta globin gene are only expressed in these cells. Tissue-specific transcription factors also ensure that mutations in these factors may impair only the function of...
82.9K
Diffusion01:12

Diffusion

221.8K
Diffusion is the passive movement of substances down their concentration gradients—requiring no expenditure of cellular energy. Substances, such as molecules or ions, diffuse from an area of high concentration to an area of low concentration in the cytosol or across membranes. Eventually, the concentration will even out, with the substance moving randomly but causing no net change in concentration. Such a state is called dynamic equilibrium, which is essential for maintaining overall...
221.8K
Diffusion01:21

Diffusion

6.6K
Diffusion is a type of passive transport. In passive transport, a substance tends to move from an area of high concentration to an area of low concentration until the concentration is equal across the space. For example, take the diffusion of substances through the air. When someone opens a perfume bottle in a room filled with people, the perfume is at its highest concentration in the bottle and is at its lowest at the edges of the room. The perfume vapor will diffuse, or spread away, from the...
6.6K
Transcription01:10

Transcription

157.1K
Overview
Transcription is the process of synthesizing RNA from a DNA sequence by RNA polymerase. It is the first step in producing a protein from a gene sequence. Additionally, many other proteins and regulatory sequences are involved in the proper synthesis of messenger RNA (mRNA). Regulation of transcription is responsible for the differentiation of all the different types of cells and often for the proper cellular response to environmental signals.
Transcription Can Produce Different Kinds...
157.1K
Transcription Elongation Factors02:35

Transcription Elongation Factors

14.1K
Transcription elongation is a dynamic process that alters depending upon the sequence heterogeneity of the DNA being transcribed. Hence, it is not surprising that the elongation complex's composition also varies along the way while transcribing a gene.
The transcription elongation is regulated via pausing of RNA polymerase on several occasions during transcription. In bacteria, these halts are necessary because the transcription of DNA into mRNA is coupled to the translation of that mRNA...
14.1K
Eukaryotic Transcription Activators02:42

Eukaryotic Transcription Activators

12.9K
Transcription activators are proteins that promote the transcription of genes from DNA to RNA. In most cases, these proteins contain two separate domains ‒ a domain that binds to DNA and a domain for activating transcription; however, in some cases, a single domain is responsible for both binding and activation of transcription, as seen in the glucocorticoid receptor and MyoD.
The binding domains are capable of recognizing and interacting with regulatory sequences on the DNA. These...
12.9K

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関連する実験動画

Updated: Feb 13, 2026

Rapid in vivo Drug Response Prediction Using Leukemia Cell Grafts in Zebrafish Embryos
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Rapid in vivo Drug Response Prediction Using Leukemia Cell Grafts in Zebrafish Embryos

Published on: May 23, 2025

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多条件拡散トランスフォーマーを使用して,薬物による転写反応の予測.

Qifan Hu1, Zeyu Chen1, Jin Gu1

  • 1MOE Key Laboratory of Bioinformatics BNRIST Bioinformatics Division Department of Automation Tsinghua University Beijing China.

Quantitative biology (Beijing, China)
|February 12, 2026
PubMed
まとめ
この要約は機械生成です。

私たちは,薬剤によって破壊されたトランスクリプトームを効率的に生成するために,新しい拡散トランスフォーマーモデルである PertDiT を開発しました. このAIアプローチは,既存の方法よりも正確に転写変化を予測することによって,薬剤発見とパーソナライズド医療を加速します.

キーワード:
拡散モデルの拡散モデル干渉による干渉である.トランスクリプトーム transcriptome

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RNA Secondary Structure Prediction Using High-throughput SHAPE
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RNA Secondary Structure Prediction Using High-throughput SHAPE

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Patient-Derived Tumor Explants As a "Live" Preclinical Platform for Predicting Drug Resistance in Patients
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Patient-Derived Tumor Explants As a "Live" Preclinical Platform for Predicting Drug Resistance in Patients

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関連する実験動画

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Rapid in vivo Drug Response Prediction Using Leukemia Cell Grafts in Zebrafish Embryos
10:46

Rapid in vivo Drug Response Prediction Using Leukemia Cell Grafts in Zebrafish Embryos

Published on: May 23, 2025

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RNA Secondary Structure Prediction Using High-throughput SHAPE
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RNA Secondary Structure Prediction Using High-throughput SHAPE

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Patient-Derived Tumor Explants As a "Live" Preclinical Platform for Predicting Drug Resistance in Patients
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科学分野:

  • コンピュータ生物学 コンピュータ生物学
  • ゲノミクスゲノミクスとは
  • 人工知能 (AI) とは,人工知能 (AI) のことです.

背景:

  • 薬物による変異性トランスクリプトームは,パーソナライズド医療と薬物発見において極めて重要です.
  • 現在の高通量スクリーニング方法は,高価で時間がかかります.

研究 の 目的:

  • 混乱トランスクリプトームを生成するための新しいマルチコンディション拡散トランスフォーマーモデル,PertDiTを導入する.
  • 薬物テキスト情報に基づくトランスクリプトームの条件付き生成を可能にする.

主な方法:

  • テキスト表現のための大型言語モデルとトランスフォーマーアーキテクチャを統合した PertDiT を開発しました.
  • 組み込みの新型乱およびトランスクリプトーム融合モジュール.
  • 薬物発見とパーソナライズド医療のためのCrossDiTとCatCrossDiTのネットワーク構造を設計しました.

主要な成果:

  • PertDiTは,トランスクリプトームの再構築における優れたパフォーマンスを示した.
  • このモデルは,干渉による転写変化を正確に予測した.
  • 総合的な指標とデータ分割戦略で既存の方法を上回った.

結論:

  • PertDiTは,薬剤によって乱されたトランスクリプトームを生成するための効率的かつ効果的なアプローチを提供します.
  • このモデルは,薬剤発見とパーソナライズド医療の進歩に大きな期待を示しています.
  • モデルのアーキテクチャと有効性は厳格に検証されました.