Author

Zheng Jing

University of MichiganORCID 0000-0003-0111-5056Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Genetic & Genomic Medicine· 2 Bioinformatics· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:benchmark study· 2 Research Focus:benchmarking· 2 Approach:deep learning· 2 Organism:human· 2 Research Focus:protein structure prediction· 2 Assay:spatial transcriptomics· 2 Approach:statistical model· 2 Assay:bulk RNA-seq· 1

Frequent Co-Authors

Bing HeiD· 2 shared Lana X. GarmireiD· 2 shared Eun-Young Karen ChoiiD· 1 shared Jian KangiD· 1 shared Kumardeep ChaudharyiD· 1 shared Lana Xia GarmireiD· 1 shared Maria A. WesterhoffiD· 1 shared Noshad HosseiniiD· 1 shared

Activity by Year

2021-2021 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersBioinformatics

Bing HeORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

BioinformaticsbioRxivPreprintAug 27, 2021

Benchmarking Computational Integration Methods for Spatial Transcriptomics Data

Yijun Li, Stefan Stanojevic, Bing He…·Lana X. Garmire

This study benchmarks integration methods for spatial transcriptomics data, showing that combining highly variable and spatially variable genes improves clustering performance.

7 citations

spatial transcriptomicsstatistical model

𝕏 PostBluesky

Genetic & Genomic MedicineGenome MedicinePeer-reviewedJul 14, 2021

DeepProg: an ensemble of deep-learning and machine-learning models for prognosis prediction using multi-omics data

Olivier Poirion, Zheng Jing, Kumardeep Chaudhary…·Lana X. Garmire

DeepProg predicts patient survival subtypes using multi-omics data, identifying two optimal subtypes and improving risk-stratification across multiple cancers.

299 citationstop 1%

humanmultiome

𝕏 PostBluesky

Genetic & Genomic MedicineNAR Genomics and BioinformaticsPeer-reviewedJan 6, 2021

Two-stage biologically interpretable neural-network models for liver cancer prognosis prediction using histopathology and transcriptomic data

Zhucheng Zhan, Zheng Jing, Bing He…·Lana Xia Garmire

The paper develops a two-stage neural network model for liver cancer prognosis using histopathology and transcriptomic data, showing improved accuracy compared to existing methods.

28 citations

humanbulk RNA-seq

𝕏 PostBluesky