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Iscience|September 23, 2024
Deep neural networks for predicting the affinity landscape of protein-protein interactionsReut Meiri, Shay-Lee Aharoni Lotati, Yaron Orenstein, et al.
Cell Systems|September 29, 2017
Optimized Sequence Library Design for Efficient In Vitro Interaction MappingYaron Orenstein, Robert Puccinelli, Ryan Kim, et al.
Bioinformatics (Oxford, England)|July 15, 2025
GreedyMini: generating low-density DNA minimizersShay Golan, Ido Tziony, Matan Kraus, et al.
Cancers|June 18, 2020
Quantitative Analysis of Differential Expression of HOX Genes in Multiple CancersOrit Adato, Yaron Orenstein, Juri Kopolovic, et al.
Frontiers in Cell and Developmental Biology|March 9, 2023
Deciphering transcription factors and their corresponding regulatory elements during inhibitory interneuron differentiation using deep neural networksRawan Alatawneh, Yahel Salomon, Reut Eshel, et al.
Bioinformatics (Oxford, England)|September 9, 2017
Improving the performance of minimizers and winnowing schemesGuillaume Marçais, David Pellow, Daniel Bork, et al.
BMC Bioinformatics|June 24, 2022
Predicting the pathogenicity of bacterial genomes using widely spread protein familiesShaked Naor-Hoffmann, Dina Svetlitsky, Neta Sal-Man, et al.
FEBS Letters|October 23, 2024
Mapping the sclerostin-LRP4 binding interface identifies critical interaction hotspots in loops 1 and 3 of sclerostinSvetlana Katchkovsky, Reut Meiri, Shiran Lacham-Hartman, et al.
Protein Science : a Publication of the Protein Society|July 21, 2026
Engineering selective amyloid precursor protein inhibitors by machine learning and deep mutational scanningReut Meiri, Oz Reuveni, Michal Levi, et al.
Nucleic Acids Research|December 5, 2015
Integrated microfluidic approach for quantitative high-throughput measurements of transcription factor binding affinitiesYair Glick, Yaron Orenstein, Dana Chen, et al.
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