Author

Xueliang Li

Shanghai Institute of Nutrition and HealthORCID 0009-0008-7726-8298Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Cancer Biology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1

Frequent Co-Authors

Bihan SheniD· 1 shared Fangyoumin FengiD· 1 shared Hong LiiD· 1 shared Kunshi Li· 1 shared Liangxiao MaiD· 1 shared Zhixuan TangiD· 1 shared

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2024-2024 · peak 1/yr

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6 top collaborators · 15 mutual co-author links

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1 shared paperCancer Biology

Bihan ShenORCID

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1 paper

Recent·Most cited

Cancer BiologyBioinformaticsPeer-reviewedOct 1, 2024

Dual-view jointly learning improves personalized drug synergy prediction

Xueliang Li, Bihan Shen, Fangyoumin Feng…·Hong Li

This paper introduces JointSyn, a dual-view learning method for predicting drug synergy, showing improved accuracy and generalization across datasets.

20 citations

deep learningdrug response / drug discovery

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