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相关概念视频

Synthetic Biology02:55

Synthetic Biology

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Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
Golden rice
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An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
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Ampere-Maxwell's Law: Problem-Solving

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A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
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相关实验视频

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通过超大规模的HPC,AI和量子计算来推进生物分子模拟.

Edward O Pyzer-Knapp1, Alessandro Curioni2

  • 1IBM Research Europe, Daresbury, United Kingdom.

Current opinion in structural biology
|May 11, 2024
PubMed
概括

生物分子模拟为实验提供了洞察力,并设计了新的化合物. 超尺度时代和未来的AI/量子计算将彻底改变计算生物学和大规模模拟.

科学领域:

  • 计算生物学 计算生物学
  • 生物分子模拟技术

背景情况:

  • 生物分子模拟作为数字显微镜用于理解实验数据.
  • 它还作为设计和评估新型化合物的预测工具 in silico.
  • 越来越多的科学复杂性需要计算能力的进步.

研究的目的:

  • 为了回顾Exascale时代的计算环境.
  • 探索新的计算系统和模拟方法的开发.
  • 推测人工智能和量子计算对生物分子模拟的未来影响.

主要方法:

  • 对当前计算系统及其发展的调查.
  • 模拟技术及其应用的分析.
  • 探索新兴技术,如人工智能和量子计算.

主要成果:

  • 埃克萨斯级时代正在推动更强大的计算系统的发展.
  • 模拟变得越来越复杂,有助于科学发现.
  • 人工智能和量子计算显示出改变该领域的前景.

结论:

  • 生物分子模拟对于理解过去的实验和预测未来的分子行为至关重要.

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  • 随着Exascale计算,人工智能和量子计算的出现,该领域已准备好进行重大转型.
  • 这些进步将使更深入的见解和更强大的in silico设计能力成为可能.