Toward ordered -omics data science: Researchers on the magic of turning metagenomic chaos into image-like patterns

Wan Xiang Shen; Yu Zong Chen

doi:10.1016/j.patter.2022.100673

Toward ordered -omics data science: Researchers on the magic of turning metagenomic chaos into image-like patterns

Patterns (N Y). 2023 Jan 13;4(1):100673. doi: 10.1016/j.patter.2022.100673.

Authors

Wan Xiang Shen^{1

2}, Yu Zong Chen^{1

3}

Affiliations

¹ Bioinformatics and Drug Design (BIDD) Group and Center for Computational Science and Engineering, Department of Pharmacy, National University of Singapore, Singapore 117559, Singapore.
² Department of Chemistry, Faculty of Science, National University of Singapore, Singapore 117543, Singapore.
³ The State Key Laboratory of Chemical Oncogenomics, Key Laboratory of Chemical Biology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, PR China.

Abstract

Wan Xiang Shen, a postdoctoral researcher at National University of Singapore, and Yu Zong Chen, the PI of the Bioinformatics and Drug Design (BIDD) group, have developed an AI pipeline for enhanced deep learning of metagenomic data. Their Patterns paper highlights the advantages of unsupervised data restructuring in microbiome-based disease prediction and biomarker discovery. They talk about their view of data science and the backstory of the article published in Patterns.

Publication types

News