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関連する概念動画

Improving Translational Accuracy02:07

Improving Translational Accuracy

11.8K
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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Combinatorial Gene Control02:33

Combinatorial Gene Control

8.4K
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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Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

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Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
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Genomics02:02

Genomics

37.4K
Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Gene Duplication and Divergence02:37

Gene Duplication and Divergence

6.3K
The seminal work of Ohno in 1970 popularized the idea of gene duplication and divergence. DNA sequence comparison studies reveal that a large portion of the genes in bacteria, archaebacteria, and eukaryotes was  generated by gene duplication and divergence, indicating its critical role in evolution.
The duplicated copies of the gene are called Paralogs. Paralogs with similar sequences and functions form a gene family. Across several species, a large number of gene families are...
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DNA Microarrays02:34

DNA Microarrays

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Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
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Updated: Sep 9, 2025

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
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Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

892

欠落した遺伝子発現のインプテーションのためのグラフコンボリューションネットワークの統合

Ying Zhang, Hong-Jin Yu, Zi-Hao Yan

    IEEE transactions on computational biology and bioinformatics
    |September 2, 2025
    PubMed
    まとめ
    この要約は機械生成です。

    GCNgeneは,単細胞RNAシーケンシングと空間トランスクリプトミクスのデータを統合することによって,空間的遺伝子発現を予測します. この新しい方法は 細胞の包括的な空間的理解のために 遺伝子発現を再構築します

    さらに関連する動画

    Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
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    JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
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    JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

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    関連する実験動画

    Last Updated: Sep 9, 2025

    Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
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    Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

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

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    JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
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    JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

    Published on: October 19, 2021

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    科学分野:

    • 生物医学
    • ゲノミクス
    • コンピュータ生物学

    背景:

    • 単細胞RNAシーケンシング (scRNA-seq) は細胞解像度を提供するが,空間的な文脈がない.
    • 空間トランスクリプトミクスは空間マッピングによる遺伝子発現を提供しているが,遺伝子スループットは限られている.
    • 正確な空間的遺伝子発現の予測は,細胞の機能を理解するために不可欠です.

    研究 の 目的:

    • 空間的な遺伝子分布を予測するための新しい計算方法である GCNgene を開発する.
    • 拡張された空間トランスクリプトミックの分析のためにscRNA-seqと空間トランスクリプトミックのデータを統合する.
    • トランスクリプトーム全体の空間的遺伝子発現プロファイリングを可能にする.

    主な方法:

    • GCNgeneはグラフコンボリューションネットワーク (GCN) を使用して,空間トランスクリプトミクスのデータを埋め込みます.
    • 学習されたルールは,参照のscRNA-seqデータと細胞型の比率を組み合わせて遺伝子発現を再構築します.
    • この方法は,正確な遺伝子発現予測のために空間的および単細胞データセットを統合します.

    主要な成果:

    • GCNgeneは検出されていないRNAの空間分布を正確に予測します.
    • このアプローチにより,空間的な文脈で遺伝子発現レベルを再構築できます.
    • 空間分析のための多様なトランスクリプトミックのデータセットの統合に成功しました.

    結論:

    • GCNgeneは空間的な遺伝子発現を予測するための強力な計算ソリューションを提供します
    • この方法は,現在の空間トランスクリプトミックの技術の限界に対応しています.
    • 空間的遺伝子プロファイリングを通じて,細胞の異質性と組織構造のより深い理解を容易にする.