Testing Eulerianity and connectivity in directed sparse graphs. - Yaron Orenstein; Dana Ron (Theor. Comput. Sci., 2011)

RAP: Accurate and Fast Motif Finding Based on Protein-Binding Microarray Data. - Yaron Orenstein; Eran Mick; Ron Shamir (J. Comput. Biol., 2013)

Discovering motifs using high-throughput in vitro data - Yaron Orenstein (2014)

Efficient Design of Compact Unstructured RNA Libraries Covering All k-mers. - Yaron Orenstein; Bonnie Berger (WABI, 2015)

Design of shortest double-stranded DNA sequences covering all k-mers with applications to protein-binding microarrays and synthetic enhancers. - Yaron Orenstein; Ron Shamir (Bioinform., 2015)

Compact Universal k-mer Hitting Sets. - Yaron Orenstein; David Pellow; Guillaume Marçais; Ron Shamir; Carl Kingsford (WABI, 2016)

RCK: accurate and efficient inference of sequence- and structure-based protein-RNA binding models from RNAcompete data. - Yaron Orenstein; Yuhao Wang; Bonnie Berger (Bioinform., 2016)

Efficient Design of Compact Unstructured RNA Libraries Covering All k-mers. - Yaron Orenstein; Bonnie Berger (J. Comput. Biol., 2016)

Computational Modeling of Protein-RNA Interactions. - Yaron Orenstein (BCB, 2017)

Joker de Bruijn: Sequence Libraries to Cover All k-mers Using Joker Characters. - Yaron Orenstein; Ryan Kim; Polly Fordyce; Bonnie Berger (RECOMB, 2017)

Improving the performance of minimizers and winnowing schemes. - Guillaume Marçais; David Pellow; Daniel Bork; Yaron Orenstein; Ron Shamir; Carl Kingsford (Bioinform., 2017)

Designing small universal k-mer hitting sets for improved analysis of high-throughput sequencing. - Yaron Orenstein; David Pellow; Guillaume Marçais; Ron Shamir; Carl Kingsford (PLoS Comput. Biol., 2017)

A deep neural network approach for learning intrinsic protein-RNA binding preferences. - Ilan Ben-Bassat; Benny Chor; Yaron Orenstein (Bioinform., 2018)

Joker de Bruijn: Covering k-Mers Using Joker Characters. - Yaron Orenstein; Yun William Yu; Bonnie Berger (J. Comput. Biol., 2018)

Predicting G-quadruplexes from DNA Sequences Using Multi-Kernel Convolutional Neural Networks. - Mira Barshai; Yaron Orenstein (BCB, 2019)

A Randomized Parallel Algorithm for Efficiently Finding Near-Optimal Universal Hitting Sets. - Baris Ekim; Bonnie Berger; Yaron Orenstein (RECOMB, 2020)

DeepSELEX: inferring DNA-binding preferences from HT-SELEX data using multi-class CNNs. - Maor Asif; Yaron Orenstein (Bioinform., 2020)

DeCoDe: degenerate codon design for complete protein-coding DNA libraries. - Tyler Shimko; Polly Fordyce; Yaron Orenstein (Bioinform., 2020)

Reverse de Bruijn: Utilizing Reverse Peptide Synthesis to Cover All Amino Acid k-mers. - Yaron Orenstein (J. Comput. Biol., 2020)

Improving the efficiency of de Bruijn graph construction using compact universal hitting sets. - Yael Ben-Ari; Dan Flomin; Lianrong Pu; Yaron Orenstein; Ron Shamir (BCB, 2021)

MultiRBP: multi-task neural network for protein-RNA binding prediction. - Jonathan Karin; Hagai Michel; Yaron Orenstein (BCB, 2021)

A comparative analysis of RNA-binding proteins binding models learned from RNAcompete, RNA Bind-n-Seq and eCLIP data. - Eitamar Tripto; Yaron Orenstein (Briefings Bioinform., 2021)

rG4detector: convolutional neural network to predict RNA G-quadruplex propensity based on rG4-seq data. - Maor Turner; Mira Barshai; Yaron Orenstein (BCB, 2022)

A systematic evaluation of data processing and problem formulation of CRISPR off-target site prediction. - Ofir Yaish; Maor Asif; Yaron Orenstein (Briefings Bioinform., 2022)

DeepZF: improved DNA-binding prediction of C2H2-zinc-finger proteins by deep transfer learning. - Sofia Aizenshtein-Gazit; Yaron Orenstein (Bioinform., 2022)

Computational modeling of mRNA degradation dynamics using deep neural networks. - Ofir Yaish; Yaron Orenstein (Bioinform., 2022)

Predicting the pathogenicity of bacterial genomes using widely spread protein families. - Shaked Naor-Hoffmann; Dina Svetlitsky; Neta Sal-Man; Yaron Orenstein; Michal Ziv-Ukelson (BMC Bioinform., 2022)

G4detector: Convolutional Neural Network to Predict DNA G-Quadruplexes. - Mira Barshai; Alice Aubert; Yaron Orenstein (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

G4mismatch: Deep neural networks to predict G-quadruplex propensity based on G4-seq data. - Mira Barshai; Barak Engel; Idan Haim; Yaron Orenstein (PLoS Comput. Biol., 2023)

An overview on nucleic-acid G-quadruplex prediction: from rule-based methods to deep neural networks. - Karin Elimelech-Zohar; Yaron Orenstein (Briefings Bioinform., 2023)

FiSSC: Finding smallest sequence covers to sets of degenerate reads with applications to RNA editing. - Ido Tziony; Jonathan Mandl; Kobi Shapira; Eli Eisenberg; Ely Porat; Yaron Orenstein (BCB, 2024)