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Yin-Chun Lin

As seen in: BioRxiv
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Articles

SMART 2.0 Statistical Metabolomics Analysis: An R Tool 2.0

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By Yu-Jen Liang, Chih-Ting Yang, Chia-Wei Chen, Yin-Chun Lin
| dx.doi.org
Introduction Click to copy section linkSection link copied! Metabolomics has been widely applied to characterize small molecules both intra- and intercellularly and to analyze dynamic molecular changes in response to physiological stimuli and environmental exposures in healthy and disease states. (1,2) Metabolomics encompasses two primary study designs that lead to untargeted and targeted analyses, each with its respective strengths and limitations.
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Subtyping of major SARS-CoV-2 variants reveals different transmission dynamics

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By Hsin-Chou Yang, Jen-Hung Wang, Chih-Ting Yang, Yin-Chun Lin
| BioRxiv
Abstract SARS-CoV-2 continues to evolve, causing waves of the pandemic. Up to March 2022, eight million genome sequences have accumulated, which are classified into five major variants of concern. With the growing number of sequenced genomes, analysis of the big dataset has become increasingly challenging. Here we developed systematic approaches for comprehensive subtyping and pattern recognition for transmission dynamics.
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