Author

Lawrence Lee

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 Assay:protein sequence· 2 Research Focus:clustering· 1 Research Focus:dimensionality reduction· 1 Approach:graph neural network· 1 Approach:machine learning (classical)· 1 Research Focus:protein structure prediction· 1 Approach:statistical model· 1

Frequent Co-Authors

Eyal AkivaiD· 2 shared Geoffroy Dubourg-Felonneau· 2 shared Arash Abbasi· 1 shared Shahab Shams· 1 shared

Activity by Year

2021-2022 · peak 1/yr

Co-Author Collaboration Network

4 top collaborators · 5 mutual co-author links

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2 shared papersBioinformatics

Eyal AkivaORCID

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2 papers

Recent·Most cited

Improving Protein Subcellular Localization Prediction with Structural Prediction & Graph Neural Networks

Geoffroy Dubourg-Felonneau, Arash Abbasi, Eyal Akiva, Lawrence Lee

The paper improves protein subcellular localization prediction by combining sequence-based language models and structure-based graph neural networks, achieving better performance with lower computational cost.

bioRxiv · Nov 29, 2022 · PreprintBioinformatics

Protein Organization with Manifold Exploration and Spectral Clustering

Geoffroy Dubourg-Felonneau, Shahab Shams, Eyal Akiva, Lawrence Lee

The paper introduces an unsupervised method using Transformer models, UMAP, and spectral clustering to organize protein sequences into biologically meaningful clusters.

bioRxiv · Dec 8, 2021 · PreprintBioinformatics