E3S Web Conf.
Volume 233, 20212020 2nd International Academic Exchange Conference on Science and Technology Innovation (IAECST 2020)
|Number of page(s)||4|
|Section||BFS2020-Biotechnology and Food Science|
|Published online||27 January 2021|
Single-cell transcription group sequencing and the application of artificial intelligence in developmental biology
Biology technology Westa college Westsouth university, Chongqing, 400715, China
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.
© The Authors, published by EDP Sciences 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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