Author

Jiating Yu

Chinese Academy of SciencesORCID 0000-0002-6047-1635Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Approach:deep learning· 3 Research Focus:differential expression· 3 Research Focus:gene regulatory network inference· 2 Approach:statistical model· 2 Research Focus:clustering· 1 Research Focus:drug response / drug discovery· 1 Assay:scATAC-seq· 1

Frequent Co-Authors

Ling‐Yun WuiD· 3 shared Jiacheng LengiD· 2 shared Zhichao HouiD· 2 shared Duanchen SuniD· 1 shared Zheng XiaiD· 1 shared

Activity by Year

2022-2025 · peak 1/yr

Co-Author Collaboration Network

5 top collaborators · 8 mutual co-author links

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3 shared papersBioinformatics

Ling‐Yun WuORCID

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3 papers

Recent·Most cited

BioinformaticsbioRxivPreprintAug 31, 2025

Flippable Siamese Differential Neural Network for Differential Graph Inference

Jiacheng Leng, Jiating Yu, Ling‐Yun Wu

The paper introduces FSDiffNet, a neural network for differential graph inference, which outperforms existing methods on simulated and real datasets related to autism and breast cancer.

DOI 10.1101/2025.08.31.673390

deep learningdifferential expression

BioinformaticsBMC BioinformaticsPeer-reviewedNov 15, 2023

PathExpSurv: Pathway Expansion for Explainable Survival Analysis and Disease Gene Discovery

Zhichao Hou, Jiacheng Leng, Jiating Yu…·Ling‐Yun Wu

PathExpSurv integrates known biological pathways with neural networks to improve survival analysis in cancer, identifying disease-related genes through pathway expansion.

7 citations

deep learningstatistical model

BioinformaticsbioRxivPreprintNov 18, 2022

Single-Cell ATAC-seq analysis via Network Refinement with peaks location information

Jiating Yu, Duanchen Sun, Zhichao Hou, Ling‐Yun Wu

SCARP improves scATAC-seq analysis by incorporating peak location information to better characterize co-accessibility and cell heterogeneity.

DOI 10.1101/2022.11.18.517159

scATAC-seqdeep learning