Pupko, Tal

ConSurf 2016: An improved methodology to estimate and visualize evolutionary conservation in macromolecules

Ashkenazy, H., Abadi, S., Martz, E., Chay, O., Mayrose, I., Pupko, T., & Ben-Tal, N. (2016) · Nucleic Acids Research

Genomics and Phylogenetic StudiesProtein Structure and Dynamics

Cited by 3,163

GUIDANCE2: accurate detection of unreliable alignment regions accounting for the uncertainty of multiple parameters

Sela, I., Ashkenazy, H., Katoh, K., & Pupko, T. (2015) · Nucleic Acids Research

Genomics and Phylogenetic StudiesFractal and DNA sequence analysis

Cited by 835

Differential GC content between exons and introns establishes distinct strategies of splice-site recognition

Amit, M., Donyo, M., Hollander, D., Goren, A., Kim, E., Gelfman, S., Lev-Maor, G., Burstein, D., Schwartz, S., Postolsky, B., et al. (2012) · Cell Reports

RNA Research and SplicingRNA and protein synthesis mechanisms

Cited by 338

Effect of Tokenization on Transformers for Biological Sequences

Dotan, E., Jaschek, G., Pupko, T., & Belinkov, Y. (2023) · Bioinformatics

Machine Learning in BioinformaticsGenomics and Phylogenetic Studies

Cited by 50

Effect of tokenization on transformers for biological sequences

Dotan, E., Jaschek, G., Pupko, T., & Belinkov, Y. (2024) · Bioinformatics

Machine Learning in BioinformaticsGenomics and Phylogenetic Studies

Cited by 49

Evaluation of the Ability of AlphaFold to Predict the Three-Dimensional Structures of Antibodies and Epitopes

Polonsky, K., Pupko, T., & Freund, N. T. (2023) · The Journal of Immunology

Protein Structure and Dynamicsvaccines and immunoinformatics approaches

Cited by 41

Evaluation of the Ability of AlphaFold to Predict the Three-Dimensional Structures of Antibodies and Epitopes

Polonsky, K., Pupko, T., & Freund, N. T. (2023) · The Journal of Immunology

Protein Structure and Dynamicsvaccines and immunoinformatics approaches

Cited by 40

An integrated model of phenotypic trait changes and site-specific sequence evolution

Levy Karin, E., Wicke, S., Pupko, T., & Mayrose, I. (2017) · Systematic Biology

Genomics and Phylogenetic StudiesPlant Diversity and Evolution

Cited by 37

Harnessing machine learning to unravel protein degradation in Escherichia coli

Nagar, N., Ecker, N., Loewenthal, G., Avram, O., Ben-Meir, D., Biran, D., Ron, E., & Pupko, T. (2020) · mSystems

Bacterial Genetics and BiotechnologyMachine Learning in Bioinformatics

Cited by 31

Harnessing Machine Learning To Unravel Protein Degradation in Escherichia coli

Nagar, N., Ecker, N., Loewenthal, G., Avram, O., Ben-Meir, D., Biran, D., Ron, E., & Pupko, T. (2021) · mSystems

Bacterial Genetics and BiotechnologyMachine Learning in Bioinformatics

Cited by 31

Evolutionary Insights from the Mitochondrial Genome of Oikopleura dioica : Sequencing Challenges, RNA Editing, Gene Transfers to the Nucleus, and tRNA Loss

Klirs, Y., Novosolov, M., Gissi, C., Garić, R., Pupko, T., Stach, T., & Huchon, D. (2024) · Genome Biology and Evolution

Genomics and Phylogenetic StudiesProtist diversity and phylogeny

Cited by 7

Evolutionary Insights from the Mitochondrial Genome of Oikopleura dioica : Sequencing Challenges, RNA Editing, Gene Transfers to the Nucleus, and tRNA Loss

Klirs, Y., Novosolov, M., Gissi, C., Garic, R., Pupko, T., Stach, T., & Huchon, D. (2024) · Genome Biology and Evolution

Genomics and Phylogenetic StudiesProtist diversity and phylogeny

Cited by 7