Author

Manali Singha

Louisiana State UniversityORCID 0000-0002-8049-9643Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 2 Approach:graph neural network· 2 Research Focus:cell-cell communication· 1 Approach:deep learning· 1 Assay:protein structure· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

Jagannathan RamanujamiD· 2 shared Limeng PuiD· 2 shared Michał BrylińskiiD· 2 shared Abd-El-Monsif ShawkyiD· 1 shared Hsiao‐Chun WuiD· 1 shared Konstantin Busch· 1 shared Wentao ShiiD· 1 shared

Activity by Year

2020-2021 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 18 mutual co-author links

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2 shared papersBioinformatics

Jagannathan RamanujamORCID

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2 papers

Recent·Most cited

Graphsite: ligand-binding site classification using deep graph neural network

Wentao Shi, Manali Singha, Limeng Pu, Jagannathan Ramanujam, Michał Bryliński

GraphSite classifies ligand-binding sites using a deep graph neural network, achieving 81.28% test accuracy on 14 classes.

bioRxiv · Dec 6, 2021 · PreprintBioinformatics

GraphGR: A graph neural network to predict the effect of pharmacotherapy on the cancer cell growth

Manali Singha, Limeng Pu, Abd-El-Monsif Shawky, Konstantin Busch, Hsiao‐Chun Wu, Jagannathan Ramanujam, Michał Bryliński

GraphGR predicts the effect of kinase inhibitors on cancer cell growth using a graph neural network that integrates heterogeneous data, achieving high accuracy on unseen data.

bioRxiv · May 20, 2020 · PreprintBioinformatics