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ORCIDYaron Orenstein
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2020 – today
- 2024
[c13]Ido Tziony
, Jonathan Mandl, Kobi Shapira, Eli Eisenberg, Ely Porat, Yaron Orenstein:
FiSSC: Finding smallest sequence covers to sets of degenerate reads with applications to RNA editing. BCB 2024: 13:1-13:10- 2023
- [j19]Karin Elimelech-Zohar, Yaron Orenstein:
An overview on nucleic-acid G-quadruplex prediction: from rule-based methods to deep neural networks. Briefings Bioinform. 24(4) (2023) - [j18]Mira Barshai, Barak Engel, Idan Haim, Yaron Orenstein:
G4mismatch: Deep neural networks to predict G-quadruplex propensity based on G4-seq data. PLoS Comput. Biol. 19(3) (2023) - 2022
- [j17]Ofir Yaish, Maor Asif, Yaron Orenstein:
A systematic evaluation of data processing and problem formulation of CRISPR off-target site prediction. Briefings Bioinform. 23(5) (2022) - [j16]Ofir Yaish, Yaron Orenstein:
Computational modeling of mRNA degradation dynamics using deep neural networks. Bioinform. 38(4): 1087-1101 (2022) - [j15]Shaked Naor-Hoffmann, Dina Svetlitsky, Neta Sal-Man, Yaron Orenstein, Michal Ziv-Ukelson:
Predicting the pathogenicity of bacterial genomes using widely spread protein families. BMC Bioinform. 23(1): 253 (2022) - [j14]Mira Barshai, Alice Aubert, Yaron Orenstein:
G4detector: Convolutional Neural Network to Predict DNA G-Quadruplexes. IEEE ACM Trans. Comput. Biol. Bioinform. 19(4): 1946-1955 (2022) - [c12]Maor Turner, Mira Barshai, Yaron Orenstein:
rG4detector: convolutional neural network to predict RNA G-quadruplex propensity based on rG4-seq data. BCB 2022: 22:1-22:9 - 2021
- [j13]Eitamar Tripto, Yaron Orenstein:
A comparative analysis of RNA-binding proteins binding models learned from RNAcompete, RNA Bind-n-Seq and eCLIP data. Briefings Bioinform. 22(6) (2021) - [c11]Yael Ben-Ari, Dan Flomin, Lianrong Pu, Yaron Orenstein, Ron Shamir:
Improving the efficiency of de Bruijn graph construction using compact universal hitting sets. BCB 2021: 4:1-4:9 - [c10]Jonathan Karin, Hagai Michel, Yaron Orenstein:
MultiRBP: multi-task neural network for protein-RNA binding prediction. BCB 2021: 11:1-11:9 - 2020
- [j12]Tyler Shimko, Polly Fordyce, Yaron Orenstein:
DeCoDe: degenerate codon design for complete protein-coding DNA libraries. Bioinform. 36(11): 3357-3364 (2020) - [j11]Yaron Orenstein:
Reverse de Bruijn: Utilizing Reverse Peptide Synthesis to Cover All Amino Acid k-mers. J. Comput. Biol. 27(3): 376-385 (2020) - [c9]Tyler C. Shimko, Polly M. Fordyce, Yaron Orenstein:
DeCoDe: degenerate codon design for complete protein-coding DNA libraries. BCB 2020: 51:1 - [c8]Baris Ekim, Bonnie Berger, Yaron Orenstein:
A Randomized Parallel Algorithm for Efficiently Finding Near-Optimal Universal Hitting Sets. RECOMB 2020: 37-53
2010 – 2019
- 2019
- [c7]Mira Barshai, Yaron Orenstein:
Predicting G-Quadruplexes from DNA Sequences Using Multi-Kernel Convolutional Neural Networks. BCB 2019: 357-365 - [c6]Mira Barshai, Yaron Orenstein:
Predicting G-quadruplexes from DNA Sequences Using Multi-Kernel Convolutional Neural Networks. BCB 2019: 539 - 2018
- [j10]Ilan Ben-Bassat, Benny Chor, Yaron Orenstein:
A deep neural network approach for learning intrinsic protein-RNA binding preferences. Bioinform. 34(17): i638-i646 (2018) - [j9]Yaron Orenstein, Yun William Yu, Bonnie Berger:
Joker de Bruijn: Covering k-Mers Using Joker Characters. J. Comput. Biol. 25(11): 1171-1178 (2018) - [c5]Yaron Orenstein:
Reverse de Bruijn: Utilizing Reverse Peptide Synthesis to Cover All Amino Acid k-mers. RECOMB 2018: 154-166 - 2017
- [j8]Guillaume Marçais, David Pellow, Daniel Bork, Yaron Orenstein, Ron Shamir, Carl Kingsford:
Improving the performance of minimizers and winnowing schemes. Bioinform. 33(14): i110-i117 (2017) - [j7]Yaron Orenstein, David Pellow, Guillaume Marçais, Ron Shamir, Carl Kingsford:
Designing small universal k-mer hitting sets for improved analysis of high-throughput sequencing. PLoS Comput. Biol. 13(10) (2017) - [c4]Yaron Orenstein:
Computational Modeling of Protein-RNA Interactions. BCB 2017: 629 - [c3]Yaron Orenstein, Ryan Kim, Polly Fordyce, Bonnie Berger:
Joker de Bruijn: Sequence Libraries to Cover All k-mers Using Joker Characters. RECOMB 2017: 389-390 - 2016
- [j6]Yaron Orenstein, Yuhao Wang, Bonnie Berger:
RCK: accurate and efficient inference of sequence- and structure-based protein-RNA binding models from RNAcompete data. Bioinform. 32(12): 351-359 (2016) - [j5]Yaron Orenstein, Bonnie Berger:
Efficient Design of Compact Unstructured RNA Libraries Covering All k-mers. J. Comput. Biol. 23(2): 67-79 (2016) - [c2]Yaron Orenstein, David Pellow, Guillaume Marçais, Ron Shamir, Carl Kingsford:
Compact Universal k-mer Hitting Sets. WABI 2016: 257-268 - 2015
- [j4]Yaron Orenstein, Ron Shamir:
Design of shortest double-stranded DNA sequences covering all k-mers with applications to protein-binding microarrays and synthetic enhancers. Bioinform. 31(8): 1340 (2015) - [c1]Yaron Orenstein, Bonnie Berger:
Efficient Design of Compact Unstructured RNA Libraries Covering All k-mers. WABI 2015: 308-325 - 2014
- [b1]Yaron Orenstein:
Discovering motifs using high-throughput in vitro data. Tel Aviv University, Israel, 2014 - 2013
- [j3]Yaron Orenstein, Ron Shamir:
Design of shortest double-stranded DNA sequences covering all k-mers with applications to protein-binding microarrays and synthetic enhancers. Bioinform. 29(13): 71-79 (2013) - [j2]Yaron Orenstein, Eran Mick, Ron Shamir:
RAP: Accurate and Fast Motif Finding Based on Protein-Binding Microarray Data. J. Comput. Biol. 20(5): 375-382 (2013) - 2011
- [j1]Yaron Orenstein, Dana Ron:
Testing Eulerianity and connectivity in directed sparse graphs. Theor. Comput. Sci. 412(45): 6390-6408 (2011)
Coauthor Index
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