Sheng‐Feng Shen

MorphQ provides a label-free method to quantify and visualize complex morphology from standardized images, outperforming PCA and supervised models in downstream biological analysis.

The paper uses genomic and ecological data to show that a critically endangered salmonid population has hidden resilience and supports targeted conservation strategies.

The paper uses circadian activity data and machine learning to predict breeding phenology in Nicrophorus nepalensis across different elevations and photoperiods, achieving high accuracy.

The paper uses mathematical models to explore alternative strategies to bet-hedging for adapting to fluctuating environments, finding a strategy that increases mean fitness despite higher variance.