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Genomics02:02

Genomics

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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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深度学习驱动的多态分析:增强癌症诊断和治疗方法

Jiayang Zhang1,2, Yilin Che2, Rongrong Liu2

  • 1Department of Radiology, The Second Hospital of Jilin University, 218 zigiang Street, Changchun, 130041, People's Republic of China.

Briefings in bioinformatics
|August 28, 2025
PubMed
概括

深度学习 (DL) 是一种人工智能 (AI),分析复杂的癌症多组数据以改善早期检测,诊断和预后. 它的先进模式识别能力正在彻底改变个性化癌症医学.

关键词:
人工智能癌症的早期发现深度学习多种类型瘤生物标志物

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科学领域:

  • 癌症学
  • 生物信息学
  • 人工智能

背景情况:

  • 多组技术的快速发展导致癌症数据量激增,对分析构成重大挑战.
  • 人工智能 (AI),特别是深度学习 (DL),为处理和提取大,高维数据集的见解提供了强大的能力.
  • 在自动特征提取和模式识别方面表现出色.

研究的目的:

  • 审查深度学习 (DL) 模型在分析癌症多组数据中的多种应用.
  • 突出DL在提高癌症研究领域的作用,包括早期检测,诊断,分子分类,生物标志物发现和预后.
  • 强调DL在推进个性化癌症治疗方法方面的潜力.

主要方法:

  • 审查各种深度学习 (DL) 模型及其方法.
  • 跨基因组学,表观基因组学,转录基因组学,蛋白质基因组学,放射基因组学和单细胞基因组学数据的DL应用分析.
  • 检查DL在复杂癌症数据集中的模式识别和特征提取中的作用.

主要成果:

  • 深度学习 (DL) 模型越来越多地应用于癌症研究,因为它们具有强大的数据处理能力.
  • DL有效地整合了高维多态数据,以提高对癌症发展的理解.
  • 在早期检测,诊断,分类和预测患者预后和治疗反应方面,DL具有显著的潜力.

结论:

  • 深度学习 (DL) 是癌症多学科研究中的一个变革性工具,提供先进的分析能力.
  • 预计DL的应用将扩大,进一步加快个性化癌症医学的进展.
  • DL有助于更深入地了解癌症生物学,并提高诊断和治疗策略的准确性.