AMAnD: an automated metagenome anomaly detection methodology utilizing DeepSVDD neural networks
Description
The composition of metagenomic communities within the human body often reflects localized medical conditions such as upper respiratory diseases and gastrointestinal diseases. Fast and accurate computational tools to flag anomalous metagenomic samples
