Author

Jin Shen

Carnegie Mellon University

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 2 Developmental Biology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:DNA methylation· 2 Research Focus:gene regulatory network inference· 2 Research Focus:benchmarking· 1 Assay:ChIP-seq· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1 Assay:imaging· 1

Frequent Co-Authors

Chaoyang Xiong· 1 shared Chen TaniD· 1 shared Dupeng Ma· 1 shared Ge GaoiD· 1 shared Guohong LiiD· 1 shared Huangqingbo SuniD· 1 shared Jingyi LiiD· 1 shared Jun Chen· 1 shared

Activity by Year

2021-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 22 mutual co-author links

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1 shared paperDevelopmental Biology

Chaoyang Xiong

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

DAXX governs the silencing of LINE1 during spermatogenesis in mice

Zejia Li, Chaoyang Xiong, Jin Shen, Chen Tan, Dupeng Ma, Jun Chen, Rong Liu, Qi Sun, Weihao Gong, Wenming Yuan, Mengya Huang, Li Huang, Yue‐Qiu Tan, Guohong Li, Mengcheng Luo

This study identifies DAXX as a regulator of LINE1 silencing during spermatogenesis in mice, showing its role in maintaining DNA methylation and preventing transposable element activation.

Nucleic Acids Research · Feb 9, 2026Peer-reviewedDevelopmental Biology

Improving and evaluating deep learning models of cellular organization

Huangqingbo Sun, Xuecong Fu, Serena Abraham, Jin Shen, Robert F. Murphy

The paper improves GAN-based deep learning models for cell organization and introduces evaluation criteria to assess synthetic cell images' accuracy.

Bioinformatics · Oct 18, 2022Peer-reviewedBioinformatics

Identifying complex motifs in massive omics data with a variable-convolutional layer in deep neural network

Jingyi Li, Jin Shen, Xinming Tu, Yang Ding, Ge Gao

The paper introduces a variable-convolutional layer for motif identification in omics data, showing improved performance over standard convolutional layers.

Briefings in Bioinformatics · May 28, 2021Peer-reviewedBioinformatics