Xiaodan Fan

gSV: a general structural variant detector using the third-generation sequencing data

gSV improves structural variant detection in long-read sequencing data by integrating alignment and assembly approaches, showing better sensitivity for complex variants and uncovering new SVs in breast cancer.

RoBep: A Region-Oriented Deep Learning Model for B-Cell Epitope Prediction

RoBep predicts B-cell epitopes by modeling spatial continuity, improving performance on benchmark datasets and providing antibody-antigen binding regions.

Exhaustive Cross-linking Search with Protein Feedback

This paper introduces ECL-PF, a method for cleavable XL-MS data analysis that improves sensitivity in detecting protein-protein interactions and structures.

Revealing Free Energy Landscape from MD Data via Conditional Angle Partition Tree

This paper introduces a new method to analyze free energy landscapes from MD data, showing improved performance on benchmark datasets.

Deep6mA: a deep learning framework for exploring similar patterns in DNA N6-methyladenine sites across different species

Deep6mA is a deep learning framework for identifying DNA 6mA sites, achieving high accuracy across species and revealing conserved sequence patterns and regulatory roles of 6mA.

Molecular and cellular heterogeneity of gastric cancer explained by methylation-driven key regulators

The paper identifies 11 methylation-driven key regulators in gastric cancer and shows they contribute to tumor heterogeneity and clinical outcomes.