Author

Xiaoran Cheng

Shanghai Jiao Tong 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 Synthetic Biology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 3 Research Focus:benchmarking· 2 Research Focus:variant effect prediction· 2 Organism:bacteria (other)· 1 Approach:contrastive learning· 1 Research Focus:drug response / drug discovery· 1 Research Focus:protein design· 1 Assay:protein sequence· 1

Frequent Co-Authors

Liang HongiD· 3 shared Bozitao ZhongiD· 2 shared Mingchen LiiD· 2 shared Yuanxi YuiD· 2 shared Fan JiangiD· 1 shared Fan Jiang· 1 shared Jin HuangiD· 1 shared Liang ZhangiD· 1 shared

Activity by Year

2026-2026 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

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3 shared papersBioinformatics

Liang HongORCID

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Author profile →

3 papers

Recent·Most cited

VenusGenome: Genome-Aware Masked Autoencoding for Microbial Genome Representation Learning

Liang Zhang, Yukun Zhang, Yang Tan, Fan Jiang, Bozitao Zhong, Xiaoran Cheng, Liang Hong, Mingchen Li, Yuanxi Yu

VenusGenome improves microbial genome representation learning by using a genome-aware masked autoencoder, achieving high performance in phenotype prediction and gene-level tasks.

bioRxiv · Oct 27, 2026 · PreprintBioinformatics

MAXWELL: Calibrating the probabilistic outputs of protein language models to the mutation-induced stability change landscape

Mingchen Li, Xiaoran Cheng, Fan Jiang, Liang Hong, Yuanxi Yu

MAXWELL calibrates protein language models to predict mutation-induced stability changes, outperforming existing methods and successfully designing stabilizing mutations in DhaA dehalogenase.

bioRxiv · Aug 4, 2026 · PreprintBioinformatics

Reaction-Conditioned Enzyme Discovery with Multimodal Deep Learning

Ziyi Zhou, Yutong Hu, Yuanzhen Zhang, Xinnan Fu, Runye Huang, Bozitao Zhong, Xiaoran Cheng, Jin Huang, Qin Xu, Shuangjun Lin, Linquan Bai, Liang Hong, Pan Tan

This paper introduces VenusRXN, a deep learning framework for reaction-conditioned enzyme discovery, achieving high accuracy in identifying enzymes for novel reactions.

bioRxiv · Mar 10, 2026 · PreprintSynthetic Biology