Boosting Single-cell Gene Regulatory Network Reconstruction via Bulk-cell Transcriptomic Data
Hantao Shu, Fan Ding, Jingtian Zhou, Yexiang Xue, Dan Zhao, Jianyang Zeng*, Jianzhu Ma*: Computational recovery of gene regulatory network (GRN) has recently undergone a great shift from bulk-cell towards designing algorithms targeting single-cell data. In this work, we investigate whether the widely available bulk-cell data could be leveraged to assist the GRN predictions for single cells.
A DNA-based Non-infectious Replicon System to Study SARS-CoV-2 RNA Synthesis
Xiaolong Feng, Xiaofan Zhang, Shuangying Jiang, Yuanwei Tang, Chao Cheng, Parthasarathy Abinand Krishna, Xiaoting Wang, Junbiao Dai, Jianyang Zeng*, Tian Xia*, Dan Zhao*: The coronavirus disease-2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has seriously affected public health around the world. In-depth studies on the pathogenic mechanisms of SARS-CoV-2 is urgently necessary for pandemic prevention.
KPGT: Knowledge-Guided Pre-training of Graph Transformer for Molecular Property Prediction
Li H, Zhao D*, Zeng J*: Designing accurate deep learning models for molecular property prediction plays an increasingly essential role in drug and material discovery. Recently, due to the scarcity of labeled molecules, self-supervised learning methods for learning generalizable and transferable representations of molecular graphs have attracted lots of attention.
Modeling Gene Regulatory Networks Using Neural Network Architectures
Hantao Shu, Jingtian Zhou, Qiuyu Lian, Han Li, Dan Zhao, Jianyang Zeng*, Jianzhu Ma*: Gene regulatory networks (GRNs) encode the complex molecular interactions that govern cell identity. Here we propose DeepSEM, a deep generative model that can jointly infer GRNs and biologically meaningful representation of single-cell RNA sequencing (scRNA-seq) data.
Modeling Multi-species RNA Modification through Multi-task Curriculum Learning
Yuanpeng Xiong#, Xuan He#, Dan Zhao, Tingzhong Tian, Lixiang Hong, Tao Jiang*, and Jianyang Zeng*: N6-methyladenosine (m6A) is the most pervasive modification in eukaryotic mRNAs. Numerous biological processes are regulated by this critical post-transcriptional mark, such as gene expression, RNA stability, RNA structure and translation. Recently, various experimental techniques and computational methods have been developed to characterize the transcriptome-wide landscapes
A Novel Machine Learning Based Framework for Modeling Transcription Elongation
Peiyuan Feng#, An Xiao#, Meng Fang, Fangping Wan, Shuya Li, Peng Lang, Dan Zhao*, and Jianyang Zeng*: RNA polymerase II (Pol II) generally pauses at certain positions along gene bodies, thereby interrupting the transcription elongation process, which is often coupled with various important biological functions, such as precursor mRNA splicing and gene expression regulation.
MoTSE: An Interpretable Task Similarity Estimator for Small Molecular Property Prediction Tasks
Han Li, Xinyi Zhao, Shuya Li, Fangping Wan, Dan Zhao*, and Jianyang Zeng*: Deeply understanding the properties (e.g., chemical or biological characteristics) of small molecules plays an essential role in drug development. A large number of molecular property datasets have been rapidly accumulated in recent years. However, most of these datasets contain only a limited amount of data,
An Integrative Drug Repositioning Framework Discovered a Potential Therapeutic Agent Targeting COVID-19
Yiyue Ge#, Tingzhong Tian#, Sulin Huang#, Fangping Wan#, Jingxin Li#, Shuya Li, Hui Yang, Lixiang Hong, Nian Wu, Enming Yuan, Lili Cheng, Yipin Lei, Hantao Shu, Xiaolong Feng, Ziyuan Jiang, Ying Chi, Xiling Guo, Lunbiao Cui, Liang Xiao, Zeng Li, Chunhao Yang, Zehong Miao, Haidong Tang, Ligong Chen, Hainian Zeng, Dan Zhao*, Fengcai Zhu*, Xiaokun Shen*, Jianyang Zeng*: The global spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)