Jove
Visualize
お問い合わせ
JoVE
x logofacebook logolinkedin logoyoutube logo
JoVEについて
概要リーダーシップブログJoVEヘルプセンター
著者向け
出版プロセス編集委員会範囲と方針査読よくある質問投稿
図書館員向け
推薦の声購読アクセスリソース図書館諮問委員会よくある質問
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experimentsアーカイブ
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教員リソースセンター教員サイト
利用規約
プライバシーポリシー
ポリシー

関連する概念動画

How Data are Classified: Numerical Data00:59

How Data are Classified: Numerical Data

37.0K
Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical...
37.0K
How Data are Classified: Categorical Data01:11

How Data are Classified: Categorical Data

43.1K
A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
43.1K
Dynamic Equilibrium02:20

Dynamic Equilibrium

62.0K
A reversible chemical reaction represents a chemical process that proceeds in both forward (left to right) and reverse (right to left) directions. When the rates of the forward and reverse reactions are equal, the concentrations of the reactant and product species remain constant over time and the system is at equilibrium. A special double arrow is used to emphasize the reversible nature of the reaction. The relative concentrations of reactants and products in equilibrium systems vary greatly;...
62.0K
Data Reporting and Recording01:24

Data Reporting and Recording

5.4K
Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...
5.4K
Data Collection I01:30

Data Collection I

7.9K
Data collection gathers information needed to make accurate judgments about a patient's present condition. During a health history interview, subjective data is collected from the patient, their caregivers, or family members, and objective data is collected through observations and physical assessment. Patients are the primary source of subjective data. Thus information gathered from patients through interviews, observations, and physical examination is primary data. Secondary sources of...
7.9K
Data Validation01:03

Data Validation

6.4K
Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
6.4K

こちらも読む

関連記事

共著者、ジャーナル、引用グラフによってこの研究に関連する記事。

並び替え
Same author

Collective interactions along recombinase-bound D-loops could speed repair of double-strand breaks by destabilizing flanking homoduplex tails.

Nucleic acids research·2026
Same author

Effects of surface finishing procedure, 3D printer type, and accelerated UV-aging on the surface roughness, translucency parameter, and color change of a 3D-printed permanent photopolymer resin.

BMC oral health·2026
Same author

A Comparative Investigation of the Mannose Binding Interface in DC-SIGN and MRC1 Carbohydrate Recognition Domains with All-Atom Molecular Dynamics Simulations.

Biochemistry·2026
Same author

The role of DHH motifs in PRUNE1 gene on ion channels: A new insight into epilepsy pathogenesis.

Epilepsy research·2026
Same author

Exploring the potential of AlphaFold distograms for predicting binding-induced hinge motions.

FEBS letters·2026
Same author

Sticky Salts: Overbinding of Monovalent Cations to Phosphorylations in All-Atom Force Fields.

Journal of chemical information and modeling·2025
Same journal

UPF3A and UPF3B shape the transcriptome cooperatively yet oppose cell function.

Journal of molecular biology·2026
Same journal

Antibody-secreting cells integrate efficient NMD with non‑canonical UPR signaling to maintain proteostasis and support massive immunoglobulin synthesis.

Journal of molecular biology·2026
Same journal

Small molecule stabilization of diverse amyloidogenic immunoglobulin light chains revealed by hydrogen-deuterium exchange mass spectrometry.

Journal of molecular biology·2026
Same journal

UPF1 at Work: Structural and Mechanistic Insights Into a Master Regulator of Nonsense-Mediated mRNA Decay.

Journal of molecular biology·2026
Same journal

Structural basis for the pro-amyloidogenic action and ligand binding of a novel W72R variant of human apolipoprotein A-I.

Journal of molecular biology·2026
Same journal

Cryo-EM Structure of the C. elegans Septin Tetramer Reveals a Revised Architecture and Conserved Positional Orthology.

Journal of molecular biology·2026
関連記事をすべて見る

関連する実験動画

Updated: Jan 24, 2026

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
08:49

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

1.2K

DynaBench: ドッキングベンチマークのための動的データ

Aye Berçin Barlas1, Benoist Laurent2, Ezgi Karaca1

  • 1Izmir Biomedicine and Genome Center, Izmir, Turkey.

Journal of molecular biology
|January 22, 2026
PubMed
まとめ
この要約は機械生成です。

DynaBenchは、分子動力学シミュレーションを使用したタンパク質間相互作用ダイナミクスの新しいベンチマークを提供します。このリソースは、界面の柔軟性を理解し、構造モデリングの精度を向上させるのに役立ちます。

キーワード:
All-atom Molecular DynamicsProtein dynamicsProtein interfacesProtein-protein interactionsdocking

さらに関連する動画

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
11:52

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Published on: February 9, 2017

6.5K
Use of Viral Entry Assays and Molecular Docking Analysis for the Identification of Antiviral Candidates against Coxsackievirus A16
06:03

Use of Viral Entry Assays and Molecular Docking Analysis for the Identification of Antiviral Candidates against Coxsackievirus A16

Published on: July 15, 2019

8.3K

関連する実験動画

Last Updated: Jan 24, 2026

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
08:49

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

1.2K
Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
11:52

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Published on: February 9, 2017

6.5K
Use of Viral Entry Assays and Molecular Docking Analysis for the Identification of Antiviral Candidates against Coxsackievirus A16
06:03

Use of Viral Entry Assays and Molecular Docking Analysis for the Identification of Antiviral Candidates against Coxsackievirus A16

Published on: July 15, 2019

8.3K

科学分野:

  • 生化学
  • 構造生物学
  • 計算生物学

背景:

  • タンパク質間相互作用は、輸送やシグナル伝達などの細胞機能にとって重要です。
  • 現在の構造モデリングツール(例:AlphaFold)は静的な表現を提供し、重要なインターフェースの柔軟性を無視しています。
  • タンパク質インターフェースダイナミクスの理解は、正確な機能的洞察にとって不可欠です。

研究 の 目的:

  • タンパク質間インターフェースダイナミクスのための包括的なベンチマークであるDynaBenchを導入すること。
  • タンパク質複合体のための分子動力学(MD)シミュレーションの大規模データセットを提供すること。
  • タンパク質アセンブリの計算モデリングと分析の進歩を促進すること。

主な方法:

  • Docking Benchmark 5.5の200以上のタンパク質間複合体に対して広範なMDシミュレーションを実行しました。
  • 各複合体について、100 nsの3つの軌道レプリカを生成しました。
  • すべてのシミュレーションデータを分子動力学データベース(MDDB)内のMDpositプラットフォームを通じて公開しました。

主要な成果:

  • タンパク質複合体のダイナミクスに関する実質的なデータセットを生成し、界面の柔軟性を捉えました。
  • タンパク質構造予測のための機械学習モデルのトレーニングに価値あるリソースを確立しました。
  • タンパク質複合体モデルの評価のための新しい精度メトリクスの探索を可能にしました。

結論:

  • DynaBenchは、重要なインターフェースダイナミクスデータを提供することにより、静的モデルの限界に対処します。
  • このベンチマークは、計算構造生物学と創薬のための重要なリソースとして機能します。
  • 公開されているデータは、タンパク質複合体モデリングと機能分析におけるさらなる研究を促進します。