The Research page highlights chromatin regulation, enhancer modeling, and biomedical data applications.
Neuroscience-related papers are fully listed here and can be filtered above. Corresponding authors are marked with *.
2026
UniChrom: a universal deep learning architecture for cross-scale chromatin interaction prediction
TransSE: A Transfer Learning-Based Predictive Model for Distinguishing Super Enhancers and Typical Enhancers
Genetic and pathway complexity in Alzheimer's disease: Insights from multi-omic data about the immune response and mitochondrial function
2025
ETNet: an interpretable transformer framework for enhancer-enhancer interaction prediction with cross-context transferability
Integrated Multi-Omics Analysis and Cross-Model Validation Reveal Mitochondrial Signatures in Alzheimer's Disease
Systematic Identification of Mitochondrial Signatures in Alzheimer's Disease and Inflammatory Bowel Disease
Deciphering novel mitochondrial signatures: multi-omics analysis uncovers cross-disease markers and oligodendrocyte pathways in Alzheimer's disease and glioblastoma
2022
CharID: a two-step model for universal prediction of interactions between chromatin accessible regions
2020
The genome of jojoba (Simmondsia chinensis): A taxonomically isolated species that directs wax ester accumulation in its seeds
2019
A deep learning model based on sparse auto-encoder for prioritizing cancer-related genes and drug target combinations
This page is a maintained list aligned with ORCID and PubMed. For corrections, email shenyin@ahmu.edu.cn.