Author

Cong Xie

Hainan Normal UniversityORCID 0000-0001-5950-8202Unclaimed ORCID profile · follow to get notified of new preprints

Additional preprints under this name without ORCID

Cong Xie2 papers · Beijing Normal University

Biology Disciplines

Click to filter author papers

Bioinformatics· 2 Cancer Biology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:statistical model· 3 Research Focus:benchmarking· 2 Assay:metabolomics· 2 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Organism:human· 1 Assay:protein structure· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Changbin Brad YuiD· 3 shared Junjie TongiD· 3 shared Miaoshan LuiD· 3 shared Jinyin WangiD· 2 shared Ruimin WangiD· 2 shared Shaowei AniD· 2 shared Hengxuan JiangiD· 1 shared Jingjing CheniD· 1 shared

Activity by Year

2023-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 33 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

3 shared papersBioinformatics

Changbin Brad YuORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Cancer BiologybioRxivPreprintMar 26, 2025

AlphaFold3 and RoseTTAFold All-Atom structures enable radiosensitizers discovery by targeting multiple DNA damage repair proteins

Junjie Tong, Xixi Wang, Miaoshan Lu…·Changbin Brad Yu

The paper identifies radiosensitizers by docking natural products against AI-predicted and experimental DNA repair protein structures, finding compounds that effectively target tumor radioresistance.

DOI 10.1101/2025.03.26.645385

humanprotein structure

𝕏 PostBluesky

BioinformaticsJournal of Proteome ResearchPeer-reviewedApr 19, 2024

How much storage precision can be lost: Guidance for near-lossless compression of untargeted metabolomics mass spectrometry data

Junjie Tong, Miaoshan Lu, Ruimin Wang…·Changbin Brad Yu

The paper evaluates precision loss in metabolomics mass spectrometry data compression and provides thresholds to minimize impact on downstream analysis.

7 citations

metabolomicsstatistical model

𝕏 PostBluesky

BioinformaticsbioRxivPreprintJul 2, 2023

Entropy-based decoy generation methods for accurate FDR estimation in large-scale metabolomics annotations.

Shaowei An, Miaoshan Lu, Ruimin Wang…·Changbin Brad Yu

This paper introduces entropy-based decoy generation methods to improve FDR estimation in metabolomics and presents a tool for accurate FDR-controlled analysis.

DOI 10.1101/2023.07.02.547371

metabolomicsstatistical model

𝕏 PostBluesky