Author

Joy Buongiorno

Maryville CollegeORCID 0000-0002-7442-0599Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:machine learning (classical)· 1 Assay:protein sequence· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

Ariel Alejandro AptekmanniD· 1 shared Diego Ulises FerreiroiD· 1 shared Donato GiovannelliiD· 1 shared Mihaela GlamoclijaiD· 1 shared Yana BrombergiD· 1 shared

Activity by Year

2022-2022 · peak 1/yr

Co-Author Collaboration Network

5 top collaborators · 10 mutual co-author links

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1 shared paperBioinformatics

Ariel Alejandro AptekmannORCID

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1 paper

Recent·Most cited

mebipred: identifying metal-binding potential in protein sequences.

Ariel Alejandro Aptekmann, Joy Buongiorno, Donato Giovannelli, Mihaela Glamoclija, Diego Ulises Ferreiro, Yana Bromberg

The paper introduces mebipred, a machine learning tool for predicting metal-binding proteins from sequence data, achieving 90% accuracy and outperforming existing methods.

Bioinformatics · May 27, 2022Peer-reviewedBioinformatics