Author

Tsung-Ting Hsieh

Taiwan AI LabsORCID 0000-0002-5082-4572Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:gene regulatory network inference· 2 Assay:ATAC-seq· 1 Assay:DNA methylation· 1 Assay:GWAS summary statistics· 1 Organism:human· 1 Research Focus:polygenic risk· 1 Approach:statistical model· 1

Frequent Co-Authors

Chien‐Yu CheniD· 3 shared Yi‐An Tung· 2 shared Yu‐Chuan ChangiD· 2 shared Chia-Lin YangiD· 1 shared Geng-Zhi Fann· 1 shared Hsueh‐Fen JuaniD· 1 shared Huai‐Kuang TsaiiD· 1 shared Hung-Ching Chang· 1 shared

Activity by Year

2020-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 28 mutual co-author links

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3 shared papersBioinformatics

Chien‐Yu ChenORCID

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3 papers

Recent·Most cited

PGSbuilder: An end-to-end platform for human genome association analysis and polygenic risk score predictions

Ko-Han Lee, Yi‐Lun Lee, Tsung-Ting Hsieh, Yu‐Chuan Chang, Su-Shia Wang, Geng-Zhi Fann, Wei‐Che Lin, Hung-Ching Chang, Ting-Fu Chen, Peng-Husan Li, Ya-Ling Kuo, Pei‐Lung Chen, Hsueh‐Fen Juan, Huai‐Kuang Tsai, Chien‐Yu Chen, Jia‐Hsin Huang

PGSbuilder provides a web platform for GWAS and PRS analysis, enabling medical professionals to assess genetic risk using variant annotations and multiple PRS methods.

bioRxiv · Apr 12, 2023 · PreprintBioinformatics

ezGeno: An Automatic Model Selection Package for Genomic Data Analysis

Jun-Liang Lin, Tsung-Ting Hsieh, Yi‐An Tung, Xuan-Jun Chen, Yu-Chun Hsiao, Chia-Lin Yang, Tyng-Luh Liu, Chien‐Yu Chen

ezGeno automates deep neural network design for genomic data analysis, outperforming existing tools in efficiency and accuracy for tasks like TF binding prediction and enhancer activity prediction.

Bioinformatics · Aug 13, 2021Peer-reviewedBioinformatics

accuEnhancer: Accurate enhancer prediction by integration of multiple cell type data with deep learning

Yi‐An Tung, Wen-Tse Yang, Tsung-Ting Hsieh, Yu‐Chuan Chang, June‐Tai Wu, Yen‐Jen Oyang, Chien‐Yu Chen

This study develops a deep learning model to predict enhancer activity in new cell types by integrating DNase data across multiple cell types.

bioRxiv · Nov 10, 2020 · PreprintBioinformatics