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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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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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Two structural features of the DNA molecule provide a basis for the mechanisms of heredity: the four nucleotide bases and its double-stranded nature. The Watson-Crick model of double-helical DNA structure, proposed in 1952, drew heavily upon the X-ray crystallography work of researchers Rosalind Franklin and Maurice Wilkins. Watson, Crick, and Wilkins jointly received the Nobel Prize in Physiology or Medicine for their work in 1962. Franklin was, controversially, excluded from the prize for...
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Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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基因组语言模型:机遇和挑战

Gonzalo Benegas1, Chengzhong Ye2, Carlos Albors1

  • 1Computer Science Division, University of California, Berkeley, CA, USA.

Trends in genetics : TIG
|January 3, 2025
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概括

基因组语言模型 (gLMs) 是一种在DNA上训练的大型语言模型 (LLM),为了解基因组功能和相互作用提供了强大的工具. 为复杂基因组开发有效的glm仍然具有挑战性,但对生物医学研究具有重大潜力.

关键词:
基因组语言模型的基因组语言模型机器学习是机器学习.序列设计设计的设计.转移学习转移学习变体效应预测变体效应预测

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科学领域:

  • 基因组学就是基因组学.
  • 生物信息学是一种生物信息学.
  • 计算生物学 计算生物学

背景情况:

  • 大型语言模型 (LLM) 正在彻底改变科学研究,包括生物医学科学.
  • 了解生物序列,特别是DNA,是生物学中的一个核心目标.
  • 基因组语言模型 (gLMs) 将LLM原则应用于基因组分析的DNA序列.

研究的目的:

  • 突出gLMs在推进基因组理解方面的潜力.
  • 展示gLMs在功能约束预测,序列设计和转移学习中的关键应用.
  • 讨论开发和评估glm的挑战和考虑,特别是复杂的基因组.

主要方法:

  • 在DNA序列的大型数据集上培训LLM.
  • 应用gLM来预测基因组内的功能约束.
  • 使用gLMs进行DNA序列设计和生成.
  • 探索不同物种或基因组背景的glms的转移学习技术.

主要成果:

  • gLMs显示出破译基因组功能和DNA元素相互作用的巨大潜力.
  • 在功能约束预测,序列设计和转移学习中的应用显示出有希望的结果.
  • gLMs可以帮助阐明DNA元素如何为复杂的生物功能做出贡献.

结论:

  • 基因组研究 (gLM) 是基因组研究的强大新兴工具,具有广泛的应用性.
  • 在开发高效和有效的glm方面仍然存在挑战,特别是在大型和复杂的基因组中.
  • 对gLM开发和评估的进一步研究对于释放它们在基因组学和生物医学科学中的全部潜力至关重要.