Author

Christina Floristean

Columbia UniversityORCID 0009-0004-6057-0985Unclaimed 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:protein structure prediction· 2 Approach:deep learning· 1 Assay:protein sequence· 1 Assay:protein structure· 1 Approach:statistical model· 1 Approach:transformer / foundation model· 1

Frequent Co-Authors

Gustaf AhdritziD· 2 shared Mohammed AlQuraishiiD· 2 shared Nazim BouattaiD· 2 shared Peter Karl SorgeriD· 2 shared Adegoke A. OjewoleiD· 1 shared Anant Kharkar· 1 shared Andrew M. WatkinsiD· 1 shared Arkadiusz NowaczynskiiD· 1 shared

Activity by Year

2022-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 40 mutual co-author links

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2 shared papersBioinformatics

Gustaf AhdritzORCID

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2 papers

Recent·Most cited

BioinformaticsNature MethodsPeer-reviewedMay 14, 2024

OpenFold: Retraining AlphaFold2 yields new insights into its learning mechanisms and capacity for generalization

Gustaf Ahdritz, Nazim Bouatta, Christina Floristean…·Mohammed AlQuraishi

The paper trains a new version of AlphaFold2, OpenFold, and evaluates its generalization ability and learning mechanisms.

439 citationstop 1%

protein structurestatistical model

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BioinformaticsNature BiotechnologyPeer-reviewedOct 3, 2022

Single-sequence protein structure prediction using language models from deep learning

Ratul Chowdhury, Nazim Bouatta, Surojit Biswas…·Mohammed AlQuraishi

This paper introduces RGN2, a deep learning model that predicts protein structure from single sequences without MSAs, outperforming AlphaFold2 and RoseTTAFold on orphan proteins and achieving faster computation.

455 citationstop 1%

protein sequencedeep learning

𝕏 PostBluesky