Author

Li Zhao

Jilin University

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

Same name, identified by ORCID

Biology Disciplines

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Bioinformatics· 1 Biophysics· 1 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Research Focus:differential expression· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Bissan Al‐LazikaniiD· 1 shared Chunjie JiangiD· 1 shared Costas MitsopoulosiD· 1 shared P. Andrew FutrealiD· 1 shared Patrizio Di MiccoiD· 1 shared Rongzhuo LongiD· 1 shared Stephanie SchmidtiD· 1 shared Xiaosheng WangiD· 1 shared

Activity by Year

2024-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 17 mutual co-author links

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1 shared paperCancer Biology

Bissan Al‐LazikaniORCID

Mutual co-authors in cluster

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3 papers

Recent·Most cited

Large-scale simulations reveal evolutionary constraints on intrinsically disordered regions imposed by full-length protein architecture

Yang Jiang, Xiaoyang Liu, Li Zhao, Zhong‐Yuan Lu

The paper uses large-scale simulations to show that intrinsically disordered regions in proteins are structurally and evolutionarily constrained by their full-length protein architecture.

bioRxiv · Feb 28, 2026 · PreprintBiophysics

Inferring phenotypes of single cells based on the expression profiles of phenotype-associated marker genes in bulks and single cells

Yin He, Rongzhuo Long, Li Zhao, Xiaosheng Wang

The paper introduces ScPP, an algorithm that infers single-cell phenotypes using bulk and single-cell marker gene expression profiles, showing improved performance over existing methods.

Interdisciplinary Sciences Computational Life Sciences · Jan 28, 2026Peer-reviewedBioinformatics

Probabilistic graph-based model uncovers previously unseen druggable vulnerabilities in major solid cancers

Ying Zhu, Stephanie Schmidt, Li Zhao, Chunjie Jiang, Patrizio Di Micco, Costas Mitsopoulos, P. Andrew Futreal, Bissan Al‐Lazikani

This paper introduces a graph-based model to identify druggable vulnerabilities in solid cancers, finding 43 novel targets by leveraging cooperativity in molecular networks.

bioRxiv · Jun 4, 2024 · PreprintCancer Biology