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関連する概念動画

Average Acceleration01:30

Average Acceleration

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The importance of understanding acceleration spans our day-to-day experiences, as well as the vast reaches of outer space and the tiny world of subatomic physics. In everyday conversation, to accelerate means to speed up. For instance, we are familiar with the acceleration of our car; the harder we apply our foot to the gas pedal, the faster we accelerate. The greater the acceleration, the greater the change in velocity over a given time. Acceleration is widely seen in experimental physics. In...
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Average Velocity01:12

Average Velocity

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To calculate the other physical quantities in kinematics, we must introduce the time variable. The time variable allows us not only to state the position of the object during its motion, but also how fast it is moving. The speed at which an object is moving is given by the rate at which the position changes with time. For each position xi, we assign a particular time ti. If the details of the motion at each instant are not important, the rate is usually expressed as the average velocity. This...
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Average Value of a Function01:17

Average Value of a Function

64
The average value of a function over a closed interval can be interpreted geometrically as the height of a rectangle whose area equals the net area under the curve across that interval. This net area accounts for both positive and negative contributions of the function, providing a single representative value that reflects the function’s overall behaviorA practical illustration of this idea arises when monitoring the temperature inside a greenhouse over a twenty-four-hour period. Although...
64
Average Power01:13

Average Power

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In practical electrical applications, the concept of time-varying instantaneous power is not frequently utilized. Instead, focus shifts to the more practical quantity known as average power. Average power is determined by integrating the instantaneous power over a specified time period and subsequently dividing it by that duration.
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Average and Instantaneous Velocity Vectors01:12

Average and Instantaneous Velocity Vectors

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To calculate other physical quantities in kinematics, the time variable must be introduced. The time variable not only allows us to state where an object is (its position) during its motion, but also how fast it’s moving. The speed at which an object is moving is given by the rate at which the position changes with time. For each position, a particular time is assigned. If the details of the motion at each instant are not important, the rate is usually expressed as the average velocity v.
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Antibody Structure01:10

Antibody Structure

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Overview
Antibodies, also known as immunoglobulins (Ig), are essential players of the adaptive immune system. These antigen-binding proteins are produced by B cells and make up 20 percent of the total blood plasma by weight. In mammals, antibodies fall into five different classes, which each elicits a different biological response upon antigen binding.
The Y-Shaped Structure of Antibodies Consists of Four Polypeptide Chains
Antibodies consist of four polypeptide chains: two identical heavy...
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Subnanometer-resolution Structural Determination of Hemagglutinin from Cryo-electron Tomography of Influenza Viruses
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IsoNet2：平均化なしでサブ分子分解能で細胞構造を決定

Z Hong Zhou, Yun-Tao Liu, Hongcheng Fan

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    |February 6, 2026
    PubMed
    まとめ
    この要約は機械生成です。

    IsoNet2は、クライオ電子トモグラムから3D密度を再構成するディープラーニングツールです。この方法は、平均化なしで細胞構造を高解像度で達成し、原子レベルの解釈を可能にします。

    キーワード:
    IsoNet2Cryo-ETdeep learning3D reconstructionsubmolecular resolutionstructural biology

    さらに関連する動画

    Determination of Molecular Structures of HIV Envelope Glycoproteins using Cryo-Electron Tomography and Automated Sub-tomogram Averaging
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    Subnanometer-resolution Structural Determination of Hemagglutinin from Cryo-electron Tomography of Influenza Viruses
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    Determination of Molecular Structures of HIV Envelope Glycoproteins using Cryo-Electron Tomography and Automated Sub-tomogram Averaging
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    科学分野:

    • 構造生物学
    • クライオ電子線トモグラフィー（Cryo-ET）
    • 顕微鏡法におけるディープラーニング

    背景:

    • クライオ電子線トモグラフィー（Cryo-ET）は、原子に近い解像度で細胞構造を視覚化するために重要です。
    • Cryo-ETデータからの高品質な3D密度の再構成は、ノイズ、コントラスト伝達関数（CTF）の不完全性、および欠損ウェッジアーチファクトによってしばしば制限されます。
    • 既存の手法では平均化や手動介入が必要な場合が多く、個々の細胞成分への適用が制限されます。

    研究 の 目的:

    • クライオETデータからの直接的な3D密度再構成のためのエンドツーエンドの自己教師ありディープラーニング手法であるIsoNet2を紹介すること。
    • 粒子平均化の必要なしに高解像度の構造情報を達成すること。
    • 特定のデータセットに対して手法を微調整するためのユーザーフレンドリーなインターフェースを提供すること。

    主な方法:

    • デノイジング、CTF補正、および欠損ウェッジ修復を同時に実行する統合ディープラーニングネットワークを開発しました。
    • 広範なラベル付きデータの必要性を最小限に抑える自己教師あり学習アプローチを採用しました。
    • アクセス可能で、データセット固有の微調整のためのグラフィカルユーザーインターフェース（GUI）を統合しました。

    主要な成果:

    • 平均化なしでトモグラムから直接約20 Ⅰ の解像度の再構成を達成しました。
    • HIVカプシドタンパク質構造、リボソーム内のtRNA占有率、ミトコンドリア呼吸複合体など、複雑な生物学的構造を解決しました。
    • 細胞環境の原子レベルの解釈能力を実証しました。

    結論:

    • IsoNet2は、直接的で高解像度の3D密度再構成を可能にすることにより、Cryo-ETの能力を大幅に進歩させます。
    • この手法の自己教師あり性質とユーザーフレンドリーなGUIは、複雑な細胞アーキテクチャの分析を民主化します。
    • IsoNet2は、ネイティブな細胞コンテキスト内での生物学的巨大分子の詳細な構造的および機能的洞察を促進します。