Author

Laks V. S. Lakshmanan

University of British ColumbiaORCID 0000-0002-9775-4241Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Research Focus:deconvolution· 1 Approach:deep learning· 1 Research Focus:protein design· 1 Research Focus:protein structure prediction· 1 Assay:proteomics· 1 Approach:transformer / foundation model· 1

Frequent Co-Authors

Boyan SuniD· 1 shared Cheng ChangiD· 1 shared Guangshuai Wang· 1 shared Guibin WangiD· 1 shared Leyuan LiiD· 1 shared Muhammad Abdul-MageediD· 1 shared Nanqing DongiD· 1 shared Sheng XuiD· 1 shared

Activity by Year

2024-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperBioinformatics

Boyan SunORCID

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1 paper

Recent·Most cited

π-PrimeNovo: An Accurate and Efficient Non-Autoregressive Deep Learning Model for De Novo Peptide Sequencing

Xiang Zhang, Tianze Ling, Zhi Xiang Jin, Sheng Xu, Zhiqiang Gao, Boyan Sun, Zijie Qiu, Nanqing Dong, Guangshuai Wang, Guibin Wang, Leyuan Li, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Wanli Ouyang, Cheng Chang, Siqi Sun

π-PrimeNovo is a non-autoregressive deep learning model for de novo peptide sequencing that achieves higher accuracy and 69x faster performance than existing methods.

bioRxiv · May 17, 2024 · PreprintBioinformatics