Author

Namrata Anand

Stanford UniversityORCID 0000-0002-2766-8954Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:protein design· 2 Assay:protein sequence· 2 Organism:multiple species· 1 Approach:transformer / foundation model· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Po‐Ssu HuangiD· 2 shared Raphael R. EguchiiD· 2 shared Alexander DerryiD· 1 shared Ali MadaniiD· 1 shared Bryan McCann· 1 shared Carla P. PereziD· 1 shared Irimpan I. MathewsiD· 1 shared Nikhil NaikiD· 1 shared

Activity by Year

2020-2020 · peak 2/yr

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10 top collaborators · 30 mutual co-author links

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2 shared papersSynthetic Biology

Po‐Ssu HuangORCID

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2 papers

Recent·Most cited

Synthetic BiologybioRxivPreprintMar 7, 2020

✦ In-depth digest

ProGen: Language Modeling for Protein Generation

Ali Madani, Bryan McCann, Nikhil Naik…·Richard Socher

A 1.2B-parameter autoregressive model trained on 280M tagged sequences completes held-out proteins with near-native Rosetta energies and ranks high-fitness GB1 variants without any GB1 training.

223 citations

multiple speciesprotein sequence

𝕏 PostBluesky

BioinformaticsbioRxivPreprintJan 6, 2020

Protein sequence design with a learned potential

Namrata Anand, Raphael R. Eguchi, Irimpan I. Mathews…·Po‐Ssu Huang

This paper designs protein sequences using a deep neural network trained on crystal structures, producing stable designs that match high-resolution structures.

40 citations

protein sequencedeep learning

𝕏 PostBluesky