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関連する概念動画

Diffusion01:12

Diffusion

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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...
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RNA-seq03:21

RNA-seq

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
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Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models00:57

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models

140
Physiological pharmacokinetic models, often called flow-limited or perfusion models, typically assume a swift drug distribution between tissue and venous blood, creating a rapid drug equilibrium. This premise is based on the idea that drug diffusion is extremely fast, and the cell membrane presents no barrier to drug permeation. In this scenario, where no drug binding occurs, the drug concentration in the tissue equals that of the venous blood leaving the tissue. This greatly simplifies the...
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Regulated mRNA Transport02:22

Regulated mRNA Transport

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In eukaryotes, transcription and translation are compartmentalized; an mRNA is first synthesized in the nucleus and then selectively transported to the cytoplasm for protein synthesis. Before transport, a pre-mRNA undergoes several steps of post-transcriptional modifications including splicing, 5' capping, and the addition of a poly-adenine tail. Various proteins bind to the pre-mRNA during these modifications. The mRNA transport takes place with the help of multiple proteins playing...
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Improving Translational Accuracy02:07

Improving Translational Accuracy

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Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
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Protein Diffusion in the Membrane01:24

Protein Diffusion in the Membrane

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Proteins show rotational as well as lateral diffusion across the membrane. The lateral diffusion of proteins was confirmed through the cell fusion experiment where mouse and human cells were fused, resulting in hybrid cells. When the human and mouse cells fused, the specific membrane proteins on human and mouse cells were marked with the red and green-fluorescent markers, respectively. Initially, the red and green fluorescence was located on the respective hemisphere of the cell. As time...
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ディスコ:空間トランスクリプトミクスの拡散モデル

Ziheng Duan1, Xi Li1, Zhuoyang Zhang2

  • 1University of California, Irvine.

Proceedings. International Conference on Image Processing
|September 5, 2025
PubMed
まとめ
この要約は機械生成です。

空間トランスクリプトミクスのデータには,しばしば欠落している領域があります. DISCO (Diffusion model for Spatial transcriptomics data COmpletion) は,拡散モデルとグラフニューラルネットワークを使用して,この欠けているデータを効果的に再構築します.

キーワード:
データの完全性拡散モデル地域 完成空間トランスクリプトミクス

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科学分野:

  • 分子生物学
  • バイオ情報学
  • ゲノミクス

背景:

  • 空間的トランスクリプトミックは,その空間的文脈内の遺伝子発現を分析することによって,組織組織と機能に関する重要な洞察を提供します.
  • 空間トランスクリプトミクスの実験における技術的な限界は,多くの場合,包括的な分析と生物学的解釈を妨げ,実質的なデータギャップにつながります.

研究 の 目的:

  • DISCO (スペーストランスクリプトミクスのデータ完成のためのDIffusionモデル) を導入し,空間トランスクリプトミクスのデータ不足の問題に対処するために設計された新しい枠組みです.
  • 改善された下流分析のための空間トランスクリプトミクスのデータセットの正確性と完全性を高める.

主な方法:

  • DISCOは,グラフニューラルネットワークベースの領域エンコーダーを使用して,観測された領域からの空間および遺伝子発現データを統合します.
  • フレームワークには2つの拡散モジュールが含まれています.一つは欠けている領域の空間的位置を予測するためのもので,もう一つは遺伝子発現プロファイルを生成するためのものです.
  • 隣接する地域の情報は,推論中に統合され,生物学的一貫性があり,スムーズなデータ再構築を確保します.

主要な成果:

  • DISCOは,さまざまな空間トランスクリプトミクスデータセットで,大きな欠落したデータ領域を再構築する際の有意な効果を示しています.
  • 複数のシーケンシングプラットフォームと種間で検証されることで,DISCOのフレームワークの強さと一般化性が確認されています.
  • この方法は,これまで観察されていない領域の生物学的に妥当な遺伝子発現プロファイルと空間的レイアウトを成功裏に生成します.

結論:

  • DISCOは空間トランスクリプトミクスの欠けているデータを補完する強力なソリューションを提供し,それによってデータの質を向上させ,より深い生物学的洞察を可能にします.
  • DISCOのオープンソース実装により,研究者は空間トランスクリプトミクスのデータを強化し,この分野を前進させることができます.
  • この枠組みは,データギャップの影響を軽減することによって,より正確な組織組織と機能分析を促進します.