Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
Methods Mol Biol. 2021;2243:169-182. doi: 10.1007/978-1-0716-1103-6_9.
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.
深度学习被定义为一组计算技术，可用于从大量数据中发现潜在信息。最近，许多领域都看到了深度学习在以超越许多其他传统方法的方式解决各种任务方面的巨大潜力。基因组研究可能是利用深度学习的下一个前沿领域，因为它具有大量数据和各种任务的完美结合。在这里，我们展示了我们生成的用于结合深度学习和基因组测序数据的平台。我们在来自癌症患者肠道微生物组的公开可用测序数据上测试了该平台。我们表明，我们的平台能够比其他方法更准确地对患者进行分类，但也存在一些限制。总的来说，我们认为基因组研究是深度学习的下一个前沿领域，因为有许多令人兴奋的途径等待探索。我们认为，我们在这里展示的平台可以作为未来此类研究的基础。
