Author

Farzana Rahman

Kingston University LondonORCID 0000-0002-4785-5845Unclaimed ORCID profile · follow to get notified of new preprints

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Farzana Rahman1 paper

Biology Disciplines

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Bioinformatics· 1

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Approach:deep learning· 1 Assay:protein sequence· 1 Research Focus:protein structure prediction· 1 Approach:transformer / foundation model· 1

Frequent Co-Authors

Bishnu SarkeriD· 1 shared Fairuz Shadmani ShishiriD· 1 shared Sumaiya ShomajiiD· 1 shared

Activity by Year

2023-2023 · peak 1/yr

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3 top collaborators · 3 mutual co-author links

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1 shared paperBioinformatics

Bishnu SarkerORCID

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1 paper

Recent·Most cited

MetaLLM: Residue-wise Metal ion Prediction UsingDeep Transformer Model

Fairuz Shadmani Shishir, Bishnu Sarker, Farzana Rahman, Sumaiya Shomaji

MetaLLM predicts metal binding sites in proteins using a transformer-based model trained on protein sequences, achieving over 90% precision for common metal ions.

Lecture notes in computer science · Jan 1, 2023Peer-reviewedBioinformatics