Author

Allan dos Santos Costa

Massachusetts Institute of TechnologyORCID 0000-0001-8061-339XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Synthetic Biology· 2 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:protein structure prediction· 3 Approach:deep learning· 2 Assay:protein sequence· 2 Approach:graph neural network· 1 Research Focus:protein design· 1 Assay:protein structure· 1 Approach:transformer / foundation model· 1

Frequent Co-Authors

Alexander W. RivesiD· 2 shared Halil AkiniD· 2 shared Robert VerkuiliD· 2 shared Roshan RaoiD· 2 shared Salvatore CandidoiD· 2 shared Tom SercuiD· 2 shared Zeming LiniD· 2 shared Alexander DerryiD· 1 shared

Activity by Year

2021-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioinformatics

Alexander W. RivesORCID

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3 papers

Recent·Most cited

BioinformaticsbioRxivPreprintJun 4, 2026

Language Modeling Materializes a World Model of Protein Biology

Salvatore Candido, Thomas Hayes, Alexander Derry…·Alexander W. Rives

The paper uses language modeling to create a comprehensive representation of protein biology, enabling structure prediction and discovery of high-affinity protein interactions.

35 citations

protein sequencedeep learning

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Synthetic BiologySciencePeer-reviewedMar 16, 2023

Evolutionary-scale prediction of atomic level protein structure with a language model

Zeming Lin, Halil Akin, Roshan Rao…·Alexander W. Rives

Protein language models scaled to 15B parameters predict atomic-resolution structures from sequence up to 60x faster than the state of the art, producing over 617 million metagenomic structures.

5,592 citationstop 1%

protein structuredeep learning

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Synthetic BiologybioRxivPreprintJun 2, 2021

Distillation of MSA Embeddings to Folded Protein Structures with Graph Transformers

Allan dos Santos Costa, Manvitha R. Ponnapati, Joseph M. Jacobson, Pranam Chatterjee

The paper introduces a graph transformer architecture that uses MSA embeddings to predict protein structures directly from sequences.

5 citations

protein sequencegraph neural network

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