Author

Sajid Mahmud

University of Missouri

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

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:protein structure prediction· 2 Research Focus:benchmarking· 1 Approach:graph neural network· 1 Research Focus:protein design· 1 Assay:protein sequence· 1 Assay:protein structure· 1 Approach:transformer / foundation model· 1

Frequent Co-Authors

Jianlin Jack ChengiD· 2 shared Alex MoreheadiD· 1 shared Farhan QuadiriD· 1 shared Jian LiuiD· 1 shared Zhiye GuoiD· 1 shared

Activity by Year

2022-2023 · peak 1/yr

Co-Author Collaboration Network

5 top collaborators · 7 mutual co-author links

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2 shared papersBioinformatics

Jianlin Jack ChengORCID

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2 papers

Recent·Most cited

Accurate prediction of protein tertiary structural changes induced by single-site mutations with equivariant graph neural networks

Sajid Mahmud, Alex Morehead, Jianlin Jack Cheng

This work introduces an equivariant graph neural network to predict tertiary structural changes from single-site mutations, outperforming AlphaFold in mutant structure prediction.

bioRxiv · Oct 3, 2023 · PreprintBioinformatics

Multi-Head Attention-based U-Nets for Predicting Protein Domain Boundaries Using 1D Sequence Features and 2D Distance Maps

Sajid Mahmud, Zhiye Guo, Farhan Quadir, Jian Liu, Jianlin Jack Cheng

This paper introduces DistDom, a deep learning method that predicts protein domain boundaries using 1D sequence features and 2D distance maps, achieving higher accuracy than existing methods on CASP14 data.

BMC Bioinformatics · Jul 19, 2022Peer-reviewedBioinformatics