在计算生物学和生物信息学中的大数据分析.
Prakash Kumar1, Ranjit Kumar Paul1, Himadri Shekhar Roy1
1ICAR-Indian Agricultural Statistics Research Institute, Pusa, New Delhi, India.
Methods in molecular biology (Clifton, N.J.)
|October 6, 2023
概括
大数据分析在计算生物学和生物信息学中至关重要,它利用高通量技术来获得生物学见解. 它为推进研究,疾病预测和药物开发带来了挑战和机会.
科学领域:
- 计算生物学和生物信息学
- 基因组学,转录组学和代谢组学.
背景情况:
- 高通量技术产生了庞大的生物数据集.
- 由于这些技术,计算生物学和生物信息学领域已经大幅增长.
- 分析大型数据集对于提取有意义的生物见解至关重要.
研究的目的:
- 在计算生物学和生物信息学中提供大数据分析的概述.
- 讨论数据采集,存储,处理和分析方面的问题.
- 突出生物研究大数据分析的挑战和机遇.
主要方法:
- 审查当前的大数据分析方法.
- 讨论从获取到分析的数据处理.
- 确定关键的挑战和机会.
主要成果:
- 大数据分析对于从高通量生物数据中提取见解至关重要.
- 挑战包括数据管理和计算需求.
- 机遇包括开发算法,识别生物标志物,预测疾病和药物向发现.
结论:
- 大数据分析对于推动生物学理解和应用至关重要.
- 克服大数据分析方面的挑战,在各个研究领域都为我们带来了重大机遇.
- 计算生物学和生物信息学的持续发展是利用大数据潜力的关键.
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