Author

O. Avram

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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Evolutionary Biology· 2 Microbiology· 1

Signature Assays, Organisms & Methods

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Approach:machine learning (classical)· 2 Approach:deep learning· 1 Research Focus:differential expression· 1 Organism:E. coli· 1 Research Focus:phylogenetics / evolution· 1 Research Focus:protein folding & dynamics· 1 Assay:proteomics· 1 Research Focus:sequence-to-function modeling· 1

Frequent Co-Authors

T. Pupko· 3 shared G. Loewenthal· 2 shared N. Ecker· 2 shared D. Ben-Meir· 1 shared D. Biran· 1 shared E. Dotan· 1 shared E. Ron· 1 shared E. Wygoda· 1 shared

Activity by Year

2020-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 28 mutual co-author links

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3 shared papersEvolutionary Biology

T. Pupko

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3 papers

Recent·Most cited

Harnessing machine translation methods for sequence alignment

E. Dotan, Y. Belinkov, O. Avram, E. Wygoda, N. Ecker, M. Alburquerque, O. Keren, G. Loewenthal, T. Pupko

This paper introduces BetaAlign, a sequence alignment method using NLP techniques, which outperforms existing tools like MAFFT and MUSCLE.

bioRxiv · Jul 22, 2022 · PreprintEvolutionary Biology

Harnessing machine learning to unravel protein degradation in Escherichia coli

T. Pupko, N. Nagar, N. Ecker, G. Loewenthal, O. Avram, D. Ben-Meir, D. Biran, E. Ron

The paper uses a combination of experimental and machine learning methods to identify fast-degrading proteins in E. coli and explore factors influencing protein half-lives.

bioRxiv · Oct 4, 2020Microbiology

ModelTeller: model selection for optimal phylogenetic reconstruction using machine learning

S. Abadi, O. Avram, S. Rosset, T. Pupko, I. Mayrose

ModelTeller uses machine learning to select phylogenetic models for accurate branch-length estimation, outperforming traditional statistical methods on complex datasets.

bioRxiv · Jan 9, 2020Evolutionary Biology