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相关概念视频

What is Population Genetics?01:25

What is Population Genetics?

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A population is composed of members of the same species that simultaneously live and interact in the same area. When individuals in a population breed, they pass down their genes to their offspring. Many of these genes are polymorphic, meaning that they occur in multiple variants. Such variations of a gene are referred to as alleles. The collective set of all the alleles within a population is known as the gene pool.
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Collisions in Multiple Dimensions: Problem Solving01:06

Collisions in Multiple Dimensions: Problem Solving

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In multiple dimensions, the conservation of momentum applies in each direction independently. Hence, to solve collisions in multiple dimensions, we should write down the momentum conservation in each direction separately. To help understand collisions in multiple dimensions, consider an example.
A small car of mass 1,200 kg traveling east at 60 km/h collides at an intersection with a truck of mass 3,000 kg traveling due north at 40 km/h. The two vehicles are locked together. What is the...
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Multi-species Conserved Sequences02:51

Multi-species Conserved Sequences

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Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale  studies have provided new insights into the evolutionary relationship between organisms.
Although the genome of each species varies greatly from each other, a few sequences are highly conserved. Such conserved...
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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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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.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
324
Conservation of Small Populations02:04

Conservation of Small Populations

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Small population sizes put a species at extreme risk of extinction due to a lack of variation, and a consequent decrease in adaptability. This weakens the chances of survival under pressures such as climate change, competition from other species, or new diseases. Large populations are more likely to survive pressures such as these, as such populations are more likely to harbor individuals that have genetic variants that are adaptive under new stresses. Small populations are much less...
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Genetics of Speciation02:16

Genetics of Speciation

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Speciation is the evolutionary process resulting in the formation of new, distinct species—groups of reproductively isolated populations.
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Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3
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一个基于机会和控制的多种群遗传算法,用于解决大规模的多个序列对齐问题.

Jun Hong, Jinghui Zhong, Zhi-Hui Zhan

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    此摘要是机器生成的。

    一个新的基于机会和控制的多种群遗传算法 (CC-MPGA) 提高了多重序列对齐 (MSA) 的准确性和速度. 这种进化计算方法在大规模的生物信息学挑战中表现出色.

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    科学领域:

    • 生物信息学是一种生物信息学.
    • 计算生物学 计算生物学
    • 进化计算是一种进化计算.

    背景情况:

    • 多重序列对齐 (MSA) 对于蛋白质结构预测和遗传学建模至关重要.
    • 现有的基于进化计算 (EC) 的MSA方法在准确性和可扩展性方面面临挑战.
    • 需要新的进化框架和操作员来提高MSA的性能.

    研究的目的:

    • 为改进多重序列对齐 (MSA) 提出一种新的进化算法.
    • 为了解决当前基于EC的MSA方法的可扩展性和准确性限制.
    • 引入基于机会和控制的多种群遗传算法 (CC-MPGA).

    主要方法:

    • 开发了一个基于机会和控制的多种群遗传算法 (CC-MPGA).
    • 整合了一个新的多种群框架与遗传算法 (GA).
    • 设计基于偶然的交叉和基于控制的突变运营商,根据MSA特征量身定制.

    主要成果:

    • 在基准数据集 (Balibase,ExtHomfam) 上,CC-MPGA表现出卓越的性能.
    • 在精度和计算速度之间取得了有利的平衡.
    • 对大规模的MSA问题展示了有效性和效率.

    结论:

    • 拟议的CC-MPGA显著提高了MSA的准确性和效率.
    • 新的进化框架和操作者对复杂的生物信息学任务是有效的.
    • CC-MPGA为大规模多个序列对齐挑战提供了一个有希望的解决方案.