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相关概念视频

Behavioral Genetics and Its Designs01:23

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Behavior genetics explores how genetic inheritance influences human behavior. It focuses on how genes, passed from parents to offspring, contribute to the development of behavioral traits and tendencies. This branch of genetics seeks to understand the complex interplay between inherited genetic factors and environmental influences in shaping our behaviors.
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Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
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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.
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Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
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Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
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GENERA:一种结合基因/深度学习算法,用于多目标目标导向的De Novo设计.

Giuseppe Lamanna1,2, Pietro Delre2, Gilles Marcou3

  • 1Chemistry Department, University of Bari "Aldo Moro", Via E. Orabona, 4, I-70125 Bari, Italy.

Journal of chemical information and modeling
|August 9, 2023
PubMed
概括
此摘要是机器生成的。

一个新的算法,GENERA,结合了深度学习和基因算法,用于新的药物设计. 它有效地产生针对特定蛋白质的新药候选者,如ACE2,对于COVID-19等疾病至关重要.

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科学领域:

  • 计算化学是一种计算化学.
  • 药物发现 药物发现
  • 生物信息学是一种生物信息学.

背景情况:

  • ангиотензин转化酶2 (ACE2) 是包括COVID-19在内的各种病理学的关键标.
  • De novo分子设计旨在创建具有特定特性的新型化合物.
  • 现有的方法在生成针对特定目标的优化候选药物方面可能缺乏效率.

研究的目的:

  • 介绍GENERA,这是一个集深度学习 (DeLA-Drug) 和遗传算法 (GA) 的新算法.
  • 评估GENERA使用ACE2目标以目标为导向的de novo设计的能力.
  • 证明GENERA在药物候选物生成多目标优化中的有效性.

主要方法:

  • GENERA将DeLA-Drug用于模拟生成与GA用于属性优化相结合.
  • 该算法应用于ACE2目标.
  • 使用PLANTS和GLIDE的对接模拟被用于评估.
  • 使用了基于对接分数的帕雷托支配性的健身功能.

主要成果:

  • GENERA 成功生成了针对 ACE2 的聚焦分子库.
  • 该算法使用基于帕雷托统治的健身函数证明了有效的多目标优化.
  • 与已知的ACE2结合剂相比,生成的库显示了更好的对接分数.
  • 热内拉迅速产生了有前途的候选药物.

结论:

  • GENERA代表了一种创新的方法,用于以目标为导向的新药设计.
  • 在GA框架内集成基于DL的模拟发电机是一种新的策略.
  • 这种方法有效地为特定的生物目标生成优化的分子库.