Author

Mark Rozanov

Tel Aviv University

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Assay:protein structure· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

Haim J. WolfsoniD· 1 shared

Activity by Year

2023-2023 · peak 1/yr

1 paper

Recent·Most cited

BioinformaticsIEEE International Conference on Bioinformatics and Biomedicine (BIBM)Peer-reviewedDec 5, 2023

SegmA: Residue Segmentation of cryo-EM density maps

Mark Rozanov, Haim J. Wolfson

SegmA is a deep learning model that segments cryo-EM density maps into residue types, achieving 80% accuracy for nucleotides and improved amino acid detection after removing low-confidence regions.

2 citationstop 2%

protein structuredeep learning

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