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関連する概念動画

Master Transcription Regulators02:23

Master Transcription Regulators

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...
Alternative RNA Splicing02:18

Alternative RNA Splicing

Alternative RNA splicing is the regulated splicing of exons and introns to produce different mature mRNAs from a single pre-mRNA. Unlike in constitutive splicing where a single gene produces a single type of mRNA, alternative splicing allows an organism to produce multiple proteins from a single gene and plays an important role in protein diversity.
There are five types of alternative RNA splicing that vary in the ways the pre-mRNA segments are removed or retained in the mature mRNA. The first...
General Transcription Factors01:30

General Transcription Factors

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...
Chromatin Structure and RNA Splicing02:41

Chromatin Structure and RNA Splicing

In eukaryotic cells, nascent mRNA transcripts need to undergo many post-transcriptional modifications to reach the cell cytoplasm and translate into functional proteins. For a long time, transcription and pre-mRNA processing were considered two independent events that occur sequentially in the cell. However, it has now been well established that transcription and pre-mRNA processing are two simultaneous processes that are precisely regulated inside the cell.
The chromatin structure, especially...
Alternative RNA Splicing02:18

Alternative RNA Splicing

Alternative RNA splicing is the regulated splicing of exons and introns to produce different mature mRNAs from a single pre-mRNA. Unlike in constitutive splicing where a single gene produces a single type of mRNA, alternative splicing allows an organism to produce multiple proteins from a single gene and plays an important role in protein diversity.
There are five types of alternative RNA splicing that vary in the ways the pre-mRNA segments are removed or retained in the mature mRNA. The first...
Master Transcription Regulators02:23

Master Transcription Regulators

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...

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An Approach to Study Shape-Dependent Transcriptomics at a Single Cell Level
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MuST:単細胞空間トランスクリプトミクスのための多様性構造変換

Zelin Zang1,2, Liangyu Li1, Yongjie Xu1

  • 1Westlake Institute for Advanced Studies, Westlake University, HangZhou, 310000, China.

Briefings in bioinformatics
|August 28, 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 (ST) のデータは,支配的モダリティによってバイアスされる可能性があります. 多様性の構造変換 (MuST) を開発し 複雑な生物学的システムの 組織構造とバイオマーカー分析を 統合しました

キーワード:
バイオマーカーの識別モダリティーバイアスマルチモダリティ統合空間トランスクリプトミクス (ST)トポロジーの発見

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科学分野:

  • ゲノミクス
  • バイオ情報学
  • コンピュータ生物学

背景:

  • 空間トランスクリプトミクス (ST) は,組織生物学の研究のための多様式データ (トランスクリプトミクス,空間,形態学) を提供します.
  • STデータにおけるモダリティバイアスは,分析において支配的なモダリティを好む不一致のモダリティ貢献から生じる.
  • ST研究における下流分析の精度には,模様バイアスの緩和が不可欠です.

研究 の 目的:

  • マルチモダリティ構造変換 (MuST) を導入し,STデータにおけるモダリティバイアスを解決する新しい方法論を導入する.
  • STデータからのマルチモダルの情報を統一された潜在空間に効果的に統合する.
  • STにおける様々な下流分析のタスクに堅固な基盤を提供すること.

主な方法:

  • MuSTはトポロジーの発見戦略とトポロジーの融合損失関数を使用しています.
  • 異なるモダリティの間の不一致を解決するために 固有の局所構造を学習します
  • トポロジーベースの技術とディープラーニング技術を組み合わせて,マルチモダルのデータ統合を実現します.

主要な成果:

  • MuSTはマルチモダルのSTデータを 均一な潜伏空間に効果的に統合します
  • 組織構造やバイオマーカーを特定し保存する現行の方法よりも優れています
  • 異なるモダリティの精度と調整の利点を示しています.

結論:

  • MuSTは,STデータを用いて複雑な生物学的システムを分析するための汎用的なツールキットを提供します.
  • 方法論は,下流のタスクパフォーマンスを向上させ,モダリティバイアスをうまく軽減します.
  • 生物学的洞察を向上させるための高度なSTデータ分析の基盤を提供します.