عنوان انگلیسی مقاله:
MetaPheno: A critical evaluation of deep learning and machine learning in metagenome-based disease prediction
ترجمه فارسی عنوان مقاله:
MetaPheno: یک ارزیابی مهم از یادگیری عمیق و یادگیری ماشینی در پیش بینی بیماری مبتنی بر متروژن
Sciencedirect - Elsevier - Methods, 166 (2019) 74-82: doi:10:1016/j:ymeth:2019:03:003
Nathan LaPierre, Chelsea J.-T. Ju, Guangyu Zhou, Wei Wang⁎
The human microbiome plays a number of critical roles, impacting almost every aspect of human health and
well-being. Conditions in the microbiome have been linked to a number of significant diseases. Additionally,
revolutions in sequencing technology have led to a rapid increase in publicly-available sequencing data.
Consequently, there have been growing efforts to predict disease status from metagenomic sequencing data, with
a proliferation of new approaches in the last few years. Some of these efforts have explored utilizing a powerful
form of machine learning called deep learning, which has been applied successfully in several biological domains.
Here, we review some of these methods and the algorithms that they are based on, with a particular focus
on deep learning methods. We also perform a deeper analysis of Type 2 Diabetes and obesity datasets that have
eluded improved results, using a variety of machine learning and feature extraction methods. We conclude by
offering perspectives on study design considerations that may impact results and future directions the field can
take to improve results and offer more valuable conclusions. The scripts and extracted features for the analyses
conducted in this paper are available via GitHub:https://github.com/nlapier2/metapheno.
Keywords: Deep learning | Machine learning | Metagenomics | Phenotype prediction