Yaron Orenstein

Yaron Orenstein, Mira Barshai, Maor Turner, 2022, Proceedings of the 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics.

rG4detector: convolutional neural network to predict RNA G-quadruplex propensity based on rG4-seq data

Yaron Orenstein, Mira Barshai, Maor Turner, 2022, BCB.

A comparative analysis of TF binding models learned from PBM, HT-SELEX and ChIP Data

R. Shamir, Yaron Orenstein, 2014 .

Optimized Sequence Library Design for Efficient In Vitro Interaction Mapping.

Bonnie Berger, Yaron Orenstein, Polly Fordyce, 2017, Cell systems.

SELMAP - SELEX affinity landscape MAPping of transcription factor binding sites using integrated microfluidics

R. Shamir, Yaron Orenstein, Dana Chen, 2016, Scientific Reports.

Drosophila TRF2 is a preferential core promoter regulator

R. Shamir, J. Yates, Scott D. Anderson, 2014, Genes & development.

Identifying Regulatory Elements via Deep Learning

Yaron Orenstein, Mira Barshai, Eitamar Tripto, 2020, Annual Review of Biomedical Data Science.

Assessment of Algorithms for Inferring Positional Weight Matrix Motifs of Transcription Factor Binding Sites Using Protein Binding Microarray Data

Ron Shamir, Yaron Orenstein, Chaim Linhart, 2012, PloS one.

HTS-IBIS: fast and accurate inference of binding site motifs from HT-SELEX data

Ron Shamir, Yaron Orenstein, R. Shamir, 2015, bioRxiv.

Deciphering transcription factors and their corresponding regulatory elements during inhibitory interneuron differentiation using deep neural networks

Yaron Orenstein, R. Birnbaum, Reut Eshel, 2023, Frontiers in Cell and Developmental Biology.

Improving the performance of minimizers and winnowing schemes

Ron Shamir, Carl Kingsford, Guillaume Marçais, 2017, bioRxiv.

Efficient Design of Compact Unstructured RNA Libraries Covering All k-mers

Bonnie Berger, Yaron Orenstein, B. Berger, 2015, WABI.

Overcoming the design, build, test bottleneck for synthesis of nonrepetitive protein-RNA cassettes

Z. Yakhini, Yaron Orenstein, R. Amit, 2021, Nature Communications.

Retracted: DeepCRISTL: deep transfer learning to predict CRISPR/Cas9 functional and endogenous on-target editing efficiency

Yaron Orenstein, Shai Elkayam, 2022, Bioinformatics.

DeCoDe: degenerate codon design for complete protein-coding DNA libraries

Polly M. Fordyce, Yaron Orenstein, Tyler C. Shimko, 2019, bioRxiv.

Testing Eulerianity and connectivity in directed sparse graphs

Dana Ron, Yaron Orenstein, D. Ron, 2011, Theor. Comput. Sci..

Reverse de Bruijn: Utilizing Reverse Peptide Synthesis to Cover All Amino Acid k-mers

Yaron Orenstein, Yaron Orenstein, 2018, RECOMB.

Design of shortest double-stranded DNA sequences covering all k-mers with applications to protein-binding microarrays and synthetic enhancers

Ron Shamir, Yaron Orenstein, R. Shamir, 2013, Bioinform..

rG4detector, a novel RNA G-quadruplex predictor, uncovers their impact on stress granule formation

Ron Rotkopf, T. Olender, Yaron Orenstein, 2022, Nucleic acids research.

G4mismatch: Deep neural networks to predict G-quadruplex propensity based on G4-seq data

Yaron Orenstein, Mira Barshai, Barak Engel, 2023, PLoS Comput. Biol..

Predicting G-Quadruplexes from DNA Sequences Using Multi-Kernel Convolutional Neural Networks

Yaron Orenstein, Mira Barshai, Yaron Orenstein, 2019, BCB.

G4detector: Convolutional Neural Network to Predict DNA G-Quadruplexes

Yaron Orenstein, A. Aubert, Mira Barshai, 2021, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Predicting G-quadruplexes from DNA Sequences Using Multi-Kernel Convolutional Neural Networks

Yaron Orenstein, Mira Barshai, Yaron Orenstein, 2019, BCB.

Quantitative Analysis of Differential Expression of HOX Genes in Multiple Cancers

R. Unger, Yaron Orenstein, T. Juven-Gershon, 2020, Cancers.

Compact Universal k-mer Hitting Sets

Ron Shamir, Carl Kingsford, Guillaume Marçais, 2016, WABI.

DeepSELEX: inferring DNA-binding preferences from HT-SELEX data using multi-class CNNs.

Yaron Orenstein, Maor Asif, 2020, Bioinformatics.

A deep neural network approach for learning intrinsic protein‐RNA binding preferences

Benny Chor, Yaron Orenstein, Ilan Ben-Bassat, 2018, Bioinform..

An overview on nucleic-acid G-quadruplex prediction: from rule-based methods to deep neural networks.

Yaron Orenstein, Karin Elimelech-Zohar, 2023, Briefings in bioinformatics.

RCK: accurate and efficient inference of sequence- and structure-based protein–RNA binding models from RNAcompete data

Bonnie Berger, Yuhao Wang, Yaron Orenstein, 2016, Bioinform..

Transcription factor family‐specific DNA shape readout revealed by quantitative specificity models

R. Shamir, Lin Yang, R. Rohs, 2017, Molecular systems biology.

Designing small universal k-mer hitting sets for improved analysis of high-throughput sequencing

Ron Shamir, Carl Kingsford, Guillaume Marçais, 2017, PLoS Comput. Biol..

A Deep Learning Approach for Learning Intrinsic Protein-RNA Binding Preferences

Benny Chor, Yaron Orenstein, Ilan Ben-Bassat, 2018, bioRxiv.

Improved Analysis of High-Throughput Sequencing Data Using Small Universal k-Mer Hitting Sets.

Yaron Orenstein, 2021, Methods in molecular biology.

A randomized parallel algorithm for efficiently finding near-optimal universal hitting sets

Bonnie Berger, Yaron Orenstein, Barış Ekim, 2020, bioRxiv.

A comparative analysis of RNA-binding proteins binding models learned from RNAcompete, RNA Bind-n-Seq and eCLIP data

Yaron Orenstein, Eitamar Tripto, 2021, Briefings Bioinform..

RAP: Accurate and Fast Motif Finding Based on Protein-Binding Microarray Data

Ron Shamir, Yaron Orenstein, Eran Mick, 2013, J. Comput. Biol..

Generating, modeling, and evaluating a large-scale set of CRISPR/Cas9 off-target sites with bulges

Yaron Orenstein, Ofir Yaish, 2023, bioRxiv.

SWOffinder: Efficient and versatile search of CRISPR off-targets with bulges by Smith-Waterman alignment

Yaron Orenstein, Ofir Yaish, Amichai Malle, 2023, iScience.

Improving the efficiency of de Bruijn graph construction using compact universal hitting sets

Ron Shamir, Yaron Orenstein, Lianrong Pu, 2020, bioRxiv.

MultiRBP: multi-task neural network for protein-RNA binding prediction

Yaron Orenstein, Jonathan Karin, Hagai Michel, 2021, BCB.

Finding RNA structure in the unstructured RBPome

Bonnie Berger, Uwe Ohler, Yaron Orenstein, 2018, BMC Genomics.

Sequence biases in CLIP experimental data are incorporated in protein RNA-binding models

Bonnie Berger, Yaron Orenstein, Raghavendra Hosur, 2016, bioRxiv.