Zelin Zang

Task-dependent Performance of Single-cell Foundation Models under Low Supervision

This study evaluates seven single-cell foundation models across five tasks, finding varying performance depending on the downstream task and highlighting task-specific strengths.

Expanding the RNA Virus Universe by Scalable Structure-Guided Discovery

Rider improves RNA virus discovery from metatranscriptomes by combining structure-informed screening with structural validation, outperforming existing tools and recovering divergent sequences.

Structure-Preserving Visualization for Single-cell RNA-Seq Profiles Using Deep Manifold Transformation with Batch-Correction

This paper introduces a visualization method for scRNA-seq data that preserves data structure and corrects batch effects, showing its effectiveness across multiple datasets.

Phenotype Prediction using a Tensor Representation and Deep Learning from Data Independent Acquisition Mass Spectrometry

This paper develops a deep learning method using DIA tensor for phenotype prediction from mass spectrometry data, achieving high accuracy in cancer classification.