Shi‐Jie Chen

Co-transcriptional folding orchestrates sequential multi-effector sensing by a glycine tandem riboswitch

This study reveals how the glycine tandem riboswitch uses co-transcriptional folding and sequential molecular inputs to regulate gene expression.

Machine learning-inferred and energy landscape-guided analyses reveal kinetic determinants of CRISPR/Cas9 gene editing

This study combines machine learning and energy landscape analysis to identify kinetic determinants of CRISPR/Cas9 gene editing, revealing a three-state mechanism and critical nucleotides for cleavage efficiency.

Template-based RNA structure prediction advanced through a blind code competition

The paper describes a Kaggle competition for RNA 3D structure prediction, showing that template-based methods can outperform deep learning approaches.

Blind Prediction of Complex Water and Ion Ensembles Around RNA in CASP16

This paper evaluates blind predictions of dynamic water and ion ensembles around RNA using cryo-EM densities from CASP16, finding that molecular dynamics approaches perform best.

DeepCryoRNA: deep learning-based RNA structure reconstruction from cryo-EM maps

DeepCryoRNA is a deep learning method for reconstructing RNA 3D structures from cryo-EM maps, showing higher accuracy than existing methods on a benchmark dataset.

Structure prediction of the druggable fragments in SARS-CoV-2 untranslated regions

The paper reports RNA 3D structure prediction results for SARS-CoV-2 5'- and 3'-UTRs using computational methods and expert analysis.