Single-cell transcription group sequencing and the application of artificial intelligence in developmental biology

Author:

Yang Le

Abstract

In the past two or three years, genome sequencing technology has been rapidly developed. Large-scale sequencing projects such as the Human Genome Project and the Cancer Genome Project have been launched one after another. Up to now, due to the emergence and research of artificial intelligence, it has brought us many possibilities. The purpose of this article is to use artificial intelligence to help single-cell transcription sequencing as much as possible. Based on the idea of Euclid algorithm, an improved K-means algorithm is proposed, which to a certain extent avoids the phenomenon of clustering results falling into local solutions, and reduces the appearance of the original K-means algorithm due to the use of error squares criterion function. In the case of dividing large clusters, the simulation experiment results show that the improved K-means algorithm is better than the original algorithm and has better stability.

Publisher

EDP Sciences

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3