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相关概念视频

Gene Families01:57

Gene Families

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Genome Annotation and Assembly03:36

Genome Annotation and Assembly

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The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
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Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

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The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
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Gene Therapy00:59

Gene Therapy

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Gene therapy is a technique where a gene is inserted into a person’s cells to prevent or treat a serious disease. The added gene may be a healthy version of the gene that is mutated in the patient, or it could be a different gene that inactivates or compensates for the patient’s disease-causing gene. For example, in patients with severe combined immunodeficiency (SCID) due to a mutation in the gene for the enzyme adenosine deaminase, a functioning version of the gene can be...
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Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
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相关实验视频

Updated: Sep 8, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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作为基因分析OpenAI模型的替代品的小型开源文本嵌入模型

Dailin Gan1, Jun Li1

  • 1Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN, USA.

Computational and structural biotechnology journal
|August 20, 2025
PubMed
概括
此摘要是机器生成的。

开源文本嵌入模型为基因表达分析提供了具有成本效益和隐私保护的 OpenAI 替代方案. 这些模型在没有大量微调的情况下与GenePT性能相匹配或超过.

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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
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A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
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科学领域:

  • 生物信息学
  • 计算生物学
  • 基因组学

背景情况:

  • 基因表达分析的基础变压器模型在计算上昂贵.
  • GenePT使用OpenAI的文本嵌入功能来编码基因信息.
  • 由于其封闭源码的在线性质,OpenAI的服务引发了数据隐私和可访问性的担忧.

研究的目的:

  • 调查替换OpenAI的文本嵌入模型以开源替代方案的可行性.
  • 评估用于基因表达数据分析的轻量级开源变压器模型的性能.
  • 为了确定这些开源模型的最佳性能是否需要微调.

主要方法:

  • 识别了十个小型的,基于计算的轻型变压器嵌入式文本模型.
  • 在四个不同的基因分类任务中评估模型性能.
  • 将开源模型的性能与OpenAI的文本嵌入功能进行比较.

主要成果:

  • 一些已识别的开源模型在基因分类任务中与OpenAI的文本嵌入功能匹配或超越.
  • 选择的开源模型更小,更容易安装,并且需要更少的计算资源.
  • 微调开源模型并不总是带来显著的性能改善.

结论:

  • 开源文本嵌入模型提供了像OpenAI这样的专有解决方案的可行和潜在的优越替代方案.
  • 这些模型提供了数据隐私,成本效益和可访问性.
  • 这项研究表明,经过预先训练的开源模型可以在没有进行大量微调的基因分类任务时有效地使用.