Jing Zhang
Orcid: 0000-0002-5970-0509Affiliations:
- Department of Computer Science, University of California, Irvine, CA, USA
- Yale University, Department of Molecular Biophysics and Biochemistry, New Haven, CT, USA (former)
According to our database1,
Jing Zhang
authored at least 23 papers
between 2018 and 2024.
Collaborative distances:
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Bibliography
2024
scACT: Accurate Cross-modality Translation via Cycle-consistent Training from Unpaired Single-cell Data.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024
iMIRACLE: An Iterative Multi-View Graph Neural Network to Model Intercellular Gene Regulation From Spatial Transcriptomic Data.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024
2023
iHerd: an integrative hierarchical graph representation learning framework to quantify network changes and prioritize risk genes in disease.
PLoS Comput. Biol., 2023
2022
Venus: An efficient virus infection detection and fusion site discovery method using single-cell and bulk RNA-seq data.
PLoS Comput. Biol., October, 2022
Structure Detection in Three-Dimensional Cellular Cryoelectron Tomograms by Reconstructing Two-Dimensional Annotated Tilt Series.
J. Comput. Biol., 2022
Translator: A <i>Trans</i>fer <i>L</i>earning Approach to Facilitate Single-Cell <i>AT</i>AC-Seq Data Analysis fr<i>o</i>m <i>R</i>eference Dataset.
J. Comput. Biol., 2022
Deep-Precognitive Diagnosis: Preventing Future Pandemics by Novel Disease Detection With Biologically-Inspired Conv-Fuzzy Network.
IEEE Access, 2022
Unsupervised Multi-Task Learning for 3D Subtomogram Image Alignment, Clustering and Segmentation.
Proceedings of the 2022 IEEE International Conference on Image Processing, 2022
Proceedings of the 2022 IEEE International Conference on Image Processing, 2022
2021
Bayesian structural time series for biomedical sensor data: A flexible modeling framework for evaluating interventions.
PLoS Comput. Biol., 2021
Forest Fire Clustering: Cluster-oriented Label Propagation Clustering and Monte Carlo Verification Inspired by Forest Fire Dynamics.
CoRR, 2021
Active learning to classify macromolecular structures in situ for less supervision in cryo-electron tomography.
Bioinform., 2021
DECODE: a Deep-learning framework for Condensing enhancers and refining boundaries with large-scale functional assays.
Bioinform., 2021
Unsupervised Domain Alignment Based Open Set Structural Recognition of Macromolecules Captured By Cryo-Electron Tomography.
Proceedings of the 2021 IEEE International Conference on Image Processing, 2021
2020
Sensors, 2020
Few-shot learning for classification of novel macromolecular structures in cryo-electron tomograms.
PLoS Comput. Biol., 2020
PLoS Comput. Biol., 2020
NIMBus: a negative binomial regression based Integrative Method for mutation Burden Analysis.
BMC Bioinform., 2020
DiNeR: a Differential graphical model for analysis of co-regulation Network Rewiring.
BMC Bioinform., 2020
Bioinform., 2020
PUB-SalNet: A Pre-Trained Unsupervised Self-Aware Backpropagation Network for Biomedical Salient Segmentation.
Algorithms, 2020
2018
MOAT: efficient detection of highly mutated regions with the Mutations Overburdening Annotations Tool.
Bioinform., 2018