Orenstein Lab

Computational modeling of mRNA degradation dynamics using deep neural networks

O. Yaish and Y. Orenstein

Bioinformatics (2022)

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

J. Karin, H. Michel and Y. Orenstein

Proceedings of the 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (2021)

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

Y. Ben-Ari, D. Flomin, L. Pu, Y. Orenstein and R. Shamir

Proceedings of the 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (2021)

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

E. Tripto and Y. Orenstein

Briefings in Bioinformatics (2021)

G4detector: Convolutional Neural Network to Predict DNA G-quadruplexes

M. Barshai*, A. Aubert* and Y. Orenstein

IEEE/ACM Transactions on Computational Biology and Bioinformatics (2021)

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

N. Katz, E. Tripto, N. Granik, S. Goldberg, O. Atar, Z. Yakhini, Y. Orenstein and R. Amit

Nature Communications (2021)

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

Y. Orenstein

Methods in Molecular Biology (2021)

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

M. Asif, Y. Orenstein

Bioinformatics (2020)

Identifying Regulatory Elements via Deep Learning

M. Barshai*, E. Tripto*, Y. Orenstein

Annual Review of Biomedical Data Science (2020)

Quantitative Analysis of Differential Expression of HOX Genes in Multiple Cancers

O. Adato, Y. Orenstein, J. Kopolovich, T. Juven-Gershon and R. Unger

Cancers 2020

A Randomized Parallel Algorithm for Efficiently Finding Near-Optimal Universal Hitting Sets

B. Ekim, B. Berger and Y. Orenstein

Proceedings of the International Conference on Research in Computational Molecular Biology (RECOMB) 2020

Custom DNA microarrays reveal diverse binding preferences of proteins and small molecules to thousands of G-quadruplexes

S. Ray, D. Tillo, R.E. Boer, N. Assad, M. Barshai, G. Wu, Y. Orenstein, D. Yang, J.S. Schneeklot and C. Vinson

ACS Chemical Biology (2020)

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

T. Shimko, P. Fordyce and Y. Orenstein

Bioinformatics (2020)

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

Y. Orenstein

Journal of Computational Biology (2020)

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

M. Barshai and Y. Orenstein

Proceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (2019)

Joker de Bruijn: covering k-mers using joker characters

Y. Orenstein, Y. W. Yu and B. Berger

Journal of Computational Biology (2018)

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

I. Ben-Bassat, B. Chor and Y. Orenstein

Bioinformatics (2018)

Reverse de Bruijn: utilizing reverse peptide synthesis to cover all amino acid k-mers

Y. Orenstein

Proceedings of the International Conference on Research in Computational Molecular Biology (RECOMB) 2018

Comprehensive, high-resolution binding energy landscapes reveal context dependencies of transcription factor binding

D. Le, T. Shimko, A. Aditham, A. Keys, S. Longwell, Y. Orenstein and P. Forydce

Proceedings of the National Academy of Sciences (2018)

Finding RNA structure in the unstructured RBPome

Y. Orenstein, U. Ohler and B. Berger

BMC Genomics (2018)

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

Y. Orenstein*, D. Pellow*, G. Marcais, R. Shamir and C. Kingsford

* Equal contribution

PLoS Computational Biology (2017)

Improving the performance of minimizers and winnowing schemes

G. Marcais, D. Pellow, D. Bork, Y. Orenstein, R. Shamir and C. Kingsford

Bioinformatics (2017)

Optimized sequence library design for efficient in vitro interaction mapping

Y. Orenstein, R. Puccinelli, R. Kim, P. Fordyce and B. Berger

Cell Systems (2017)

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

L. Yang*, Y. Orenstein*, A. Jolma, Y. Yimeng, J. Taipale, R. Shamir and R. Rohs

* Equal contribution

Molecular Systems Biology (2017), Top 10 papers reading list in Regulatory and Systems Genomics

SELMAP - SELEX Affinity Landscape Mapping of transcription factor binding sites using integrated microfluidics

D. Chen*, Y. Orenstein*, R. Golodnitsky, M. Pellach, D. Avrahami, C. Wachtel, A. Ovadia-Shochat, H. Shir-Shapira, A. Kedmi, T. Juven-Gershon, R. Shamir, and D. Gerber

* Equal contribution

Scientific Reports (2016)

Modeling protein-DNA binding via high throughput in vitro technologies

Y. Orenstein and R. Shamir

Briefings in Functional Genomics (2016)

Compact universal k-mer hitting sets

Y. Orenstein, D. Pellow, G. Marcais, R. Shamir and C. Kingsford

Proceedings of the 15th Annual Workshop on Algorithms in Bioinformatics (WABI) (2016)

Efficient design of compact unstructured RNA libraries covering all k-mers

Y. Orenstein and B. Berger

Journal of Computational Biology (2016)

Quantitative protein interaction with DNA - an integrated microfluidic application for high-throughput measurements of transcription factor affinities

Y. Glick*, Y. Orenstein*, D. Chen, D. Avrahami, T. Zor, R. Shamir and D. Gerber

* Equal contribution

Nucleic Acids Research (2015)

Efficient design of compact unstructured RNA libraries covering all k-mers

Y. Orenstein and B. Berger

Proceedings of the 14th Annual Workshop on Algorithms in Bioinformatics (WABI) (2015)

ElemeNT: A computational tool for detecting core promoter elements

A. Sloutskin, Y. Danino, Y. Orenstein, Y. Zehavi, T. Doniger, R. Shamir and T. Gershon

Transcription (2015)

Drosophila TRF2 is a preferential core promoter regulator

A. Kedmi, Y. Zehavi, Y. Glick, Y. Orenstein, D. Ideses, C. Wachtel, T. Doniger, H. Waldman, N. Muster, J. Thompson, S. Anderson, D. Avrahami, J.R. Yates III, R. Shamir, D. Gerber and T. Gershon

Genes and Development (2014)

A comparative analysis of transcription factor binding models learned from PBM, HT-SELEX and ChIP data

Y. Orenstein and R. Shamir

Nucleic Acids Research (2014)

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

Y. Orenstein and R. Shamir

Bioinformatics (2013)

RAP: Accurate and fast motif finding based on protein binding microarray data

Y. Orenstein, E. Mick and R. Shamir

Journal of Computational Biology (2013)

Evaluation of methods for modeling transcription factor sequence specificity

Matthew T Weirauch, Atina Cote, Raquel Norel, Matti Annala, Yue Zhao, Todd R Riley, Julio Saez-Rodriguez, Thomas Cokelaer, Anastasia Vedenko, Shaheynoor Talukder, DREAM5 Consortium (including Y. Orenstein, C. Linhart, R. Shamir), Harmen J Bussemaker, Quaid D Morris, Martha L Bulyk, Gustavo Stolovitzky and Timothy R Hughes

Nature Biotechnology (2013)

Assessment of algorithms for inferring positional weight matrix motifs of transcription factor binding sites using protein binding microarray data

Y. Orenstein, C. Linhart and R. Shamir

PLoS ONE (2012)

Testing Eulerianity and connectivity in directed sparse graphs

Y. Orenstein and D. Ron

Theoretical Computer Science (2011)