深度学习
计算机科学
数据科学
人工智能
深度测序
机器学习
微生物群
大数据
计算生物学
生物信息学
数据挖掘
生物
基因组
生物化学
基因
作者
Artem Danilevsky,Noam Shomron
出处
期刊:Methods in molecular biology
日期:2021-01-01
卷期号:: 169-182
被引量:4
标识
DOI:10.1007/978-1-0716-1103-6_9
摘要
Deep learning is defined as the group of computational techniques allowing for the discovery of latent information within large amounts of data. Recently, many fields have seen the immense potential of deep learning to solve various tasks in ways which outperformed many other traditional methods. Genomic research could be the next frontier to take advantage of deep learning, as it has the perfect combination of vast amounts of data and diverse tasks. Here we present the platform we generated to combine deep learning and genomic sequencing data. We tested the platform on publicly available sequencing data from the gut microbiome of cancer patients. We showed that our platform is capable of classifying patients with higher accuracy than other methods, with some caveats. Overall, we believe genomic research is the next frontline for deep learning as there are exciting avenues waiting to be explored. We think that our platform, presented here, could serve as the basis for such future research.
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